Publisher: Sage Publications   (Total: 1166 journals)

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Showing 1 - 200 of 1166 Journals sorted alphabetically
AADE in Practice     Hybrid Journal   (Followers: 6)
Abstracts in Anthropology     Full-text available via subscription   (Followers: 29)
Academic Pathology     Open Access   (Followers: 6)
Accounting History     Hybrid Journal   (Followers: 18, SJR: 0.527, CiteScore: 1)
Acta Radiologica     Hybrid Journal   (Followers: 1, SJR: 0.754, CiteScore: 2)
Acta Radiologica Open     Open Access   (Followers: 2)
Acta Sociologica     Hybrid Journal   (Followers: 39, SJR: 0.939, CiteScore: 2)
Action Research     Hybrid Journal   (Followers: 53, SJR: 0.308, CiteScore: 1)
Active Learning in Higher Education     Hybrid Journal   (Followers: 398, SJR: 1.397, CiteScore: 2)
Adaptive Behavior     Hybrid Journal   (Followers: 9, SJR: 0.288, CiteScore: 1)
Administration & Society     Hybrid Journal   (Followers: 18, SJR: 0.675, CiteScore: 1)
Adoption & Fostering     Hybrid Journal   (Followers: 25, SJR: 0.313, CiteScore: 0)
Adsorption Science & Technology     Open Access   (Followers: 9, SJR: 0.258, CiteScore: 1)
Adult Education Quarterly     Hybrid Journal   (Followers: 262, SJR: 0.566, CiteScore: 2)
Adult Learning     Hybrid Journal   (Followers: 51)
Advances in Dental Research     Hybrid Journal   (Followers: 11, SJR: 1.791, CiteScore: 4)
Advances in Developing Human Resources     Hybrid Journal   (Followers: 35, SJR: 0.614, CiteScore: 2)
Advances in Mechanical Engineering     Open Access   (Followers: 156, SJR: 0.272, CiteScore: 1)
Advances in Methods and Practices in Psychological Science     Full-text available via subscription   (Followers: 20)
Advances in Structural Engineering     Full-text available via subscription   (Followers: 51, SJR: 0.599, CiteScore: 1)
AERA Open     Open Access   (Followers: 14)
Affilia     Hybrid Journal   (Followers: 6, SJR: 0.496, CiteScore: 1)
Africa Spectrum     Open Access   (Followers: 17)
Agrarian South : J. of Political Economy     Hybrid Journal   (Followers: 3)
Air, Soil & Water Research     Open Access   (Followers: 13, SJR: 0.214, CiteScore: 1)
Alexandria : The J. of National and Intl. Library and Information Issues     Full-text available via subscription   (Followers: 68)
Allergy & Rhinology     Open Access   (Followers: 5)
AlterNative : An Intl. J. of Indigenous Peoples     Full-text available via subscription   (Followers: 39, SJR: 0.194, CiteScore: 0)
Alternative Law J.     Hybrid Journal   (Followers: 12, SJR: 0.176, CiteScore: 0)
Alternatives : Global, Local, Political     Hybrid Journal   (Followers: 12, SJR: 0.351, CiteScore: 1)
Alternatives to Laboratory Animals     Full-text available via subscription   (Followers: 11, SJR: 0.297, CiteScore: 1)
American Behavioral Scientist     Hybrid Journal   (Followers: 26, SJR: 0.982, CiteScore: 2)
American Economist     Hybrid Journal   (Followers: 7)
American Educational Research J.     Hybrid Journal   (Followers: 260, SJR: 2.913, CiteScore: 3)
American J. of Alzheimer's Disease and Other Dementias     Hybrid Journal   (Followers: 23, SJR: 0.67, CiteScore: 2)
American J. of Cosmetic Surgery     Hybrid Journal   (Followers: 9)
American J. of Evaluation     Hybrid Journal   (Followers: 18, SJR: 0.646, CiteScore: 2)
American J. of Health Promotion     Hybrid Journal   (Followers: 35, SJR: 0.807, CiteScore: 1)
American J. of Hospice and Palliative Medicine     Hybrid Journal   (Followers: 47, SJR: 0.65, CiteScore: 1)
American J. of Law & Medicine     Full-text available via subscription   (Followers: 12, SJR: 0.204, CiteScore: 1)
American J. of Lifestyle Medicine     Hybrid Journal   (Followers: 7, SJR: 0.431, CiteScore: 1)
American J. of Medical Quality     Hybrid Journal   (Followers: 13, SJR: 0.777, CiteScore: 1)
American J. of Men's Health     Open Access   (Followers: 9, SJR: 0.595, CiteScore: 2)
American J. of Rhinology and Allergy     Hybrid Journal   (Followers: 11, SJR: 0.972, CiteScore: 2)
American J. of Sports Medicine     Hybrid Journal   (Followers: 249, SJR: 3.949, CiteScore: 6)
American Politics Research     Hybrid Journal   (Followers: 36, SJR: 1.313, CiteScore: 1)
American Review of Public Administration     Hybrid Journal   (Followers: 28, SJR: 2.062, CiteScore: 2)
American Sociological Review     Hybrid Journal   (Followers: 358, SJR: 6.333, CiteScore: 6)
American String Teacher     Full-text available via subscription   (Followers: 3)
Analytical Chemistry Insights     Open Access   (Followers: 26, SJR: 0.224, CiteScore: 1)
Angiology     Hybrid Journal   (Followers: 5, SJR: 0.849, CiteScore: 2)
Animation     Hybrid Journal   (Followers: 15, SJR: 0.197, CiteScore: 0)
Annals of Clinical Biochemistry     Hybrid Journal   (Followers: 10, SJR: 0.634, CiteScore: 1)
Annals of Otology, Rhinology & Laryngology     Hybrid Journal   (Followers: 20, SJR: 0.807, CiteScore: 1)
Annals of Pharmacotherapy     Hybrid Journal   (Followers: 59, SJR: 1.096, CiteScore: 2)
Annals of the American Academy of Political and Social Science     Hybrid Journal   (Followers: 51, SJR: 1.225, CiteScore: 3)
Annals of the ICRP     Hybrid Journal   (Followers: 4, SJR: 0.548, CiteScore: 1)
Anthropocene Review     Hybrid Journal   (Followers: 8, SJR: 3.341, CiteScore: 7)
Anthropological Theory     Hybrid Journal   (Followers: 48, SJR: 0.739, CiteScore: 1)
Antitrust Bulletin     Hybrid Journal   (Followers: 14)
Antiviral Chemistry and Chemotherapy     Open Access   (Followers: 2, SJR: 0.635, CiteScore: 2)
Antyajaa : Indian J. of Women and Social Change     Hybrid Journal   (Followers: 1)
Applied Biosafety     Hybrid Journal   (Followers: 1, SJR: 0.131, CiteScore: 0)
Applied Psychological Measurement     Hybrid Journal   (Followers: 21, SJR: 1.17, CiteScore: 1)
Applied Spectroscopy     Full-text available via subscription   (Followers: 27, SJR: 0.489, CiteScore: 2)
Armed Forces & Society     Hybrid Journal   (Followers: 25, SJR: 0.29, CiteScore: 1)
Arthaniti : J. of Economic Theory and Practice     Full-text available via subscription  
Arts and Humanities in Higher Education     Hybrid Journal   (Followers: 49, SJR: 0.305, CiteScore: 1)
Asia Pacific Media Educator     Hybrid Journal   (Followers: 1, SJR: 0.23, CiteScore: 0)
Asia-Pacific J. of Management Research and Innovation     Full-text available via subscription   (Followers: 3)
Asia-Pacific J. of Public Health     Hybrid Journal   (Followers: 15, SJR: 0.558, CiteScore: 1)
Asia-Pacific J. of Rural Development     Hybrid Journal   (Followers: 2)
Asian and Pacific Migration J.     Full-text available via subscription   (Followers: 8, SJR: 0.324, CiteScore: 1)
Asian Cardiovascular and Thoracic Annals     Hybrid Journal   (Followers: 2, SJR: 0.305, CiteScore: 0)
Asian J. of Comparative Politics     Hybrid Journal   (Followers: 5)
Asian J. of Legal Education     Full-text available via subscription   (Followers: 4)
Asian J. of Management Cases     Hybrid Journal   (Followers: 6, SJR: 0.101, CiteScore: 0)
ASN Neuro     Open Access   (Followers: 2, SJR: 1.534, CiteScore: 3)
Assessment     Hybrid Journal   (Followers: 19, SJR: 1.519, CiteScore: 3)
Assessment for Effective Intervention     Hybrid Journal   (Followers: 15, SJR: 0.578, CiteScore: 1)
Australasian J. of Early Childhood     Hybrid Journal   (Followers: 7, SJR: 0.535, CiteScore: 1)
Australasian Psychiatry     Hybrid Journal   (Followers: 18, SJR: 0.433, CiteScore: 1)
Australian & New Zealand J. of Psychiatry     Hybrid Journal   (Followers: 30, SJR: 1.801, CiteScore: 2)
Australian and New Zealand J. of Criminology     Hybrid Journal   (Followers: 547, SJR: 0.612, CiteScore: 1)
Australian J. of Career Development     Hybrid Journal   (Followers: 5)
Australian J. of Education     Hybrid Journal   (Followers: 51, SJR: 0.403, CiteScore: 1)
Australian J. of Management     Hybrid Journal   (Followers: 13, SJR: 0.497, CiteScore: 1)
Autism     Hybrid Journal   (Followers: 358, SJR: 1.739, CiteScore: 4)
Autism & Developmental Language Impairments     Open Access   (Followers: 17)
Avian Biology Research     Hybrid Journal   (Followers: 6, SJR: 0.401, CiteScore: 1)
Behavior Modification     Hybrid Journal   (Followers: 14, SJR: 0.877, CiteScore: 2)
Behavioral and Cognitive Neuroscience Reviews     Hybrid Journal   (Followers: 27)
Behavioral Disorders     Hybrid Journal   (Followers: 2)
Beyond Behavior     Hybrid Journal   (Followers: 2)
Bible Translator     Hybrid Journal   (Followers: 13)
Biblical Theology Bulletin     Hybrid Journal   (Followers: 24, SJR: 0.184, CiteScore: 0)
Big Data & Society     Open Access   (Followers: 55)
Biochemistry Insights     Open Access   (Followers: 7)
Bioinformatics and Biology Insights     Open Access   (Followers: 12, SJR: 1.141, CiteScore: 2)
Biological Research for Nursing     Hybrid Journal   (Followers: 7, SJR: 0.685, CiteScore: 2)
Biomarker Insights     Open Access   (Followers: 1, SJR: 0.81, CiteScore: 2)
Biomarkers in Cancer     Open Access   (Followers: 11)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Informatics Insights     Open Access   (Followers: 8)
Bioscope: South Asian Screen Studies     Hybrid Journal   (Followers: 4, SJR: 0.235, CiteScore: 0)
BMS: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique     Hybrid Journal   (Followers: 4, SJR: 0.226, CiteScore: 0)
Body & Society     Hybrid Journal   (Followers: 29, SJR: 1.531, CiteScore: 3)
Bone and Tissue Regeneration Insights     Open Access   (Followers: 2)
Brain and Neuroscience Advances     Open Access  
Brain Science Advances     Open Access  
Breast Cancer : Basic and Clinical Research     Open Access   (Followers: 12, SJR: 0.823, CiteScore: 2)
British J. of Music Therapy     Hybrid Journal   (Followers: 9)
British J. of Occupational Therapy     Hybrid Journal   (Followers: 253, SJR: 0.323, CiteScore: 1)
British J. of Pain     Hybrid Journal   (Followers: 31, SJR: 0.579, CiteScore: 2)
British J. of Politics and Intl. Relations     Hybrid Journal   (Followers: 39, SJR: 0.91, CiteScore: 2)
British J. of Visual Impairment     Hybrid Journal   (Followers: 14, SJR: 0.337, CiteScore: 1)
British J.ism Review     Hybrid Journal   (Followers: 18)
BRQ Business Review Quarterly     Open Access   (Followers: 1)
Building Acoustics     Hybrid Journal   (Followers: 4, SJR: 0.215, CiteScore: 1)
Building Services Engineering Research & Technology     Hybrid Journal   (Followers: 3, SJR: 0.583, CiteScore: 1)
Bulletin of Science, Technology & Society     Hybrid Journal   (Followers: 9)
Business & Society     Hybrid Journal   (Followers: 15)
Business and Professional Communication Quarterly     Hybrid Journal   (Followers: 9, SJR: 0.348, CiteScore: 1)
Business Information Review     Hybrid Journal   (Followers: 17, SJR: 0.279, CiteScore: 0)
Business Perspectives and Research     Hybrid Journal   (Followers: 3)
Cahiers Élisabéthains     Hybrid Journal   (Followers: 1, SJR: 0.111, CiteScore: 0)
Calcutta Statistical Association Bulletin     Hybrid Journal   (Followers: 1)
California Management Review     Hybrid Journal   (Followers: 37, SJR: 2.209, CiteScore: 4)
Canadian Association of Radiologists J.     Full-text available via subscription   (Followers: 2, SJR: 0.463, CiteScore: 1)
Canadian J. of Kidney Health and Disease     Open Access   (Followers: 8, SJR: 1.007, CiteScore: 2)
Canadian J. of Nursing Research (CJNR)     Hybrid Journal   (Followers: 15)
Canadian J. of Occupational Therapy     Hybrid Journal   (Followers: 168, SJR: 0.626, CiteScore: 1)
Canadian J. of Psychiatry     Hybrid Journal   (Followers: 28, SJR: 1.769, CiteScore: 3)
Canadian J. of School Psychology     Hybrid Journal   (Followers: 12, SJR: 0.266, CiteScore: 1)
Canadian Pharmacists J. / Revue des Pharmaciens du Canada     Hybrid Journal   (Followers: 3, SJR: 0.536, CiteScore: 1)
Cancer Control     Open Access   (Followers: 2)
Cancer Growth and Metastasis     Open Access   (Followers: 1)
Cancer Informatics     Open Access   (Followers: 4, SJR: 0.64, CiteScore: 1)
Capital and Class     Hybrid Journal   (Followers: 10, SJR: 0.282, CiteScore: 1)
Cardiac Cath Lab Director     Full-text available via subscription   (Followers: 1)
Cardiovascular and Thoracic Open     Open Access   (Followers: 1)
Career Development and Transition for Exceptional Individuals     Hybrid Journal   (Followers: 10, SJR: 0.44, CiteScore: 1)
Cartilage     Hybrid Journal   (Followers: 6, SJR: 0.889, CiteScore: 3)
Cell Transplantation     Open Access   (Followers: 5, SJR: 1.023, CiteScore: 3)
Cephalalgia     Hybrid Journal   (Followers: 8, SJR: 1.581, CiteScore: 3)
Cephalalgia Reports     Open Access   (Followers: 4)
Child Language Teaching and Therapy     Hybrid Journal   (Followers: 34, SJR: 0.501, CiteScore: 1)
Child Maltreatment     Hybrid Journal   (Followers: 11, SJR: 1.22, CiteScore: 3)
Child Neurology Open     Open Access   (Followers: 6)
Childhood     Hybrid Journal   (Followers: 19, SJR: 0.894, CiteScore: 2)
Childhood Obesity and Nutrition     Open Access   (Followers: 12)
China Information     Hybrid Journal   (Followers: 9, SJR: 0.767, CiteScore: 2)
China Report     Hybrid Journal   (Followers: 11, SJR: 0.221, CiteScore: 0)
Chinese J. of Sociology     Full-text available via subscription   (Followers: 5)
Christian Education J. : Research on Educational Ministry     Hybrid Journal   (Followers: 1)
Chronic Illness     Hybrid Journal   (Followers: 6, SJR: 0.672, CiteScore: 2)
Chronic Respiratory Disease     Hybrid Journal   (Followers: 12, SJR: 0.808, CiteScore: 2)
Chronic Stress     Open Access  
Citizenship, Social and Economics Education     Full-text available via subscription   (Followers: 6, SJR: 0.145, CiteScore: 0)
Cleft Palate-Craniofacial J.     Hybrid Journal   (Followers: 8, SJR: 0.757, CiteScore: 1)
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical and Applied Thrombosis/Hemostasis     Open Access   (Followers: 32, SJR: 0.49, CiteScore: 1)
Clinical and Translational Neuroscience     Open Access   (Followers: 1)
Clinical Case Studies     Hybrid Journal   (Followers: 3, SJR: 0.364, CiteScore: 1)
Clinical Child Psychology and Psychiatry     Hybrid Journal   (Followers: 45, SJR: 0.73, CiteScore: 2)
Clinical EEG and Neuroscience     Hybrid Journal   (Followers: 8, SJR: 0.552, CiteScore: 2)
Clinical Ethics     Hybrid Journal   (Followers: 13, SJR: 0.296, CiteScore: 1)
Clinical Medicine Insights : Arthritis and Musculoskeletal Disorders     Open Access   (Followers: 3, SJR: 0.537, CiteScore: 2)
Clinical Medicine Insights : Blood Disorders     Open Access   (Followers: 1, SJR: 0.314, CiteScore: 2)
Clinical Medicine Insights : Cardiology     Open Access   (Followers: 8, SJR: 0.686, CiteScore: 2)
Clinical Medicine Insights : Case Reports     Open Access   (Followers: 1, SJR: 0.283, CiteScore: 1)
Clinical Medicine Insights : Circulatory, Respiratory and Pulmonary Medicine     Open Access   (Followers: 4, SJR: 0.425, CiteScore: 2)
Clinical Medicine Insights : Ear, Nose and Throat     Open Access   (Followers: 2)
Clinical Medicine Insights : Endocrinology and Diabetes     Open Access   (Followers: 34, SJR: 0.63, CiteScore: 2)
Clinical Medicine Insights : Oncology     Open Access   (Followers: 3, SJR: 1.129, CiteScore: 3)
Clinical Medicine Insights : Pediatrics     Open Access   (Followers: 3)
Clinical Medicine Insights : Psychiatry     Open Access   (Followers: 10)
Clinical Medicine Insights : Reproductive Health     Open Access   (Followers: 1, SJR: 0.776, CiteScore: 0)
Clinical Medicine Insights : Therapeutics     Open Access   (Followers: 1, SJR: 0.172, CiteScore: 0)
Clinical Medicine Insights : Trauma and Intensive Medicine     Open Access   (Followers: 4)
Clinical Medicine Insights : Urology     Open Access   (Followers: 3)
Clinical Medicine Insights : Women's Health     Open Access   (Followers: 4)
Clinical Nursing Research     Hybrid Journal   (Followers: 34, SJR: 0.471, CiteScore: 1)
Clinical Pathology     Open Access   (Followers: 5)
Clinical Pediatrics     Hybrid Journal   (Followers: 25, SJR: 0.487, CiteScore: 1)
Clinical Psychological Science     Hybrid Journal   (Followers: 16, SJR: 3.281, CiteScore: 5)
Clinical Rehabilitation     Hybrid Journal   (Followers: 78, SJR: 1.322, CiteScore: 3)
Clinical Risk     Hybrid Journal   (Followers: 5, SJR: 0.133, CiteScore: 0)
Clinical Trials     Hybrid Journal   (Followers: 22, SJR: 2.399, CiteScore: 2)
Clothing and Textiles Research J.     Hybrid Journal   (Followers: 28, SJR: 0.36, CiteScore: 1)
Collections : A J. for Museum and Archives Professionals     Full-text available via subscription   (Followers: 3)
Common Law World Review     Full-text available via subscription   (Followers: 17)
Communication & Sport     Hybrid Journal   (Followers: 8, SJR: 0.385, CiteScore: 1)
Communication and the Public     Hybrid Journal   (Followers: 2)
Communication Disorders Quarterly     Hybrid Journal   (Followers: 15, SJR: 0.458, CiteScore: 1)
Communication Research     Hybrid Journal   (Followers: 24, SJR: 2.171, CiteScore: 3)
Community College Review     Hybrid Journal   (Followers: 8, SJR: 1.451, CiteScore: 1)
Comparative Political Studies     Hybrid Journal   (Followers: 293, SJR: 3.772, CiteScore: 3)
Compensation & Benefits Review     Hybrid Journal   (Followers: 8)
Competition & Change     Hybrid Journal   (Followers: 12, SJR: 0.843, CiteScore: 2)

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Similar Journals
Journal Cover
Bioinformatics and Biology Insights
Journal Prestige (SJR): 1.141
Citation Impact (citeScore): 2
Number of Followers: 12  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1177-9322
Published by Sage Publications Homepage  [1166 journals]
  • Expression, Interaction, and Role of Pseudogene Adh6-ps1 in Cancer
           Phenotypes

    • Authors: Martin C Nwadiugwu
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Pseudogenes have been classified as functionless and their annotation is an ongoing problem. The Adh6-ps1—a mouse pseudogene belonging to the alcohol dehydrogenase gene complex (Adh) was analyzed to review the conservation, homology, expression, and interactions and identify any role it plays in disease phenotypes using bioinformatics databases. Results showed that Adh6-ps1 have 2 transcripts (processed and unprocessed) which may have emerged from a transposition and duplication event, respectively, and that induced inversions (Uox gene, In(3)11Rk) involving gene complexes associated with Adh6-ps1 have been implicated in a diverse range of diseases. Adh6-ps1 is highly conserved in vertebrates particularly rodents and expressed in the liver. The top 5 MirRNA targets were Mir455, Mir511, Mir1903, Mir361, and Mir669o markers. While much is unknown about Mir1903 and Mir669o, the silencing of Mir455 and Mir511 is linked with hepatocellular carcinoma (HCC), and Mir361 is implicated in endometrial cancers. Given the identified MirRNA interactions with Adh6-ps1 and its expression in HCC and reproductive systems, it may well have a role in tumorigenesis and disease phenotypes. Nonetheless, further studies are required to establish these facts to add to the growing efforts to understand pseudogenes and their potential involvement in disease conditions.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-08-14T07:10:31Z
      DOI: 10.1177/11779322211040591
      Issue No: Vol. 15 (2021)
       
  • Deep Learning Approach for Quantification of Fluorescently Labeled Blood
           Cells in Danio rerio (Zebrafish)

    • Authors: Samrat Thapa, David L Stachura
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Neutrophils are a type of white blood cell essential for the function of the innate immune system. To elucidate mechanisms of neutrophil biology, many studies are performed in vertebrate animal model systems. In Danio rerio (zebrafish), in vivo imaging of neutrophils is possible due to transgenic strains that possess fluorescently labeled leukocytes. However, due to the relative abundance of neutrophils, the counting process is laborious and subjective. In this article, we propose the use of a custom trained “you only look once” (YOLO) machine learning algorithm to automate the identification and counting of fluorescently labeled neutrophils in zebrafish. Using this model, we found the correlation coefficient between human counting and the model equals r = 0.8207 with an 8.65% percent error, while variation among human counters was 5% to 12%. Importantly, the model was able to correctly validate results of a previously published article that quantitated neutrophils manually. While the accuracy can be further improved, this model notably achieves these results in mere minutes compared with hours via standard manual counting protocols and can be performed by anyone with basic programming knowledge. It further supports the use of deep learning models for high throughput analysis of fluorescently labeled blood cells in the zebrafish model system.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-08-07T09:51:46Z
      DOI: 10.1177/11779322211037770
      Issue No: Vol. 15 (2021)
       
  • Genome Plasticity by Insertion Sequences Learned From a Case of
           Radiation-Resistant Bacterium Deinococcus geothermalis

    • Authors: Chanjae Lee, Min K Bae, Nakjun Choi, Su Jeong Lee, Sung-Jae Lee
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      The genome of the radiation-resistant bacterium Deinococcus geothermalis contains 19 types of insertion sequences (ISs), including 93 total transposases (Tpases) in 73 full-length ISs from the main chromosome and 2 mega plasmids. In this study, 68 ISs from the D. geothermalis genome were extracted to implicate the earlier genome before its mutation by transposition of ISs. The total size of eliminated ISs from genome was 78.85 kb. From these in silico corrections of mutation by the ISs, we have become aware of some bioinformatics factualness as follows: (1) can reassemble the disrupted genes if the exact IS region was eliminated, (2) can configure the schematic clustering of major DDE type Tpases, (3) can determine IS integration order across multiple hot spots, and (4) can compare genetic relativeness by the partial synteny analysis between D. geothermalis and Deinococcus strain S9. Recently, we found that several IS elements actively transferred to other genomic sites under hydrogen peroxide-induced oxidative stress conditions, resulting in the inactivation of functional genes. Therefore, the single species genome’s mobilome study provides significant support to define bacterial genome plasticity and molecular evolution from past and present progressive transposition events.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-08-05T04:53:18Z
      DOI: 10.1177/11779322211037437
      Issue No: Vol. 15 (2021)
       
  • Cloud Computing Enabled Big Multi-Omics Data Analytics

    • Authors: Saraswati Koppad, Annappa B, Georgios V Gkoutos, Animesh Acharjee
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      High-throughput experiments enable researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Challenges for such high-dimensional data sets include storage, analyses, and sharing. Recent innovations in computational technologies and approaches, especially in cloud computing, offer a promising, low-cost, and highly flexible solution in the bioinformatics domain. Cloud computing is rapidly proving increasingly useful in molecular modeling, omics data analytics (eg, RNA sequencing, metabolomics, or proteomics data sets), and for the integration, analysis, and interpretation of phenotypic data. We review the adoption of advanced cloud-based and big data technologies for processing and analyzing omics data and provide insights into state-of-the-art cloud bioinformatics applications.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-07-28T12:29:13Z
      DOI: 10.1177/11779322211035921
      Issue No: Vol. 15 (2021)
       
  • DEELIG: A Deep Learning Approach to Predict Protein-Ligand Binding
           Affinity

    • Authors: Asad Ahmed, Bhavika Mam, Ramanathan Sowdhamini
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Protein-ligand binding prediction has extensive biological significance. Binding affinity helps in understanding the degree of protein-ligand interactions and is a useful measure in drug design. Protein-ligand docking using virtual screening and molecular dynamic simulations are required to predict the binding affinity of a ligand to its cognate receptor. Performing such analyses to cover the entire chemical space of small molecules requires intense computational power. Recent developments using deep learning have enabled us to make sense of massive amounts of complex data sets where the ability of the model to “learn” intrinsic patterns in a complex plane of data is the strength of the approach. Here, we have incorporated convolutional neural networks to find spatial relationships among data to help us predict affinity of binding of proteins in whole superfamilies toward a diverse set of ligands without the need of a docked pose or complex as user input. The models were trained and validated using a stringent methodology for feature extraction. Our model performs better in comparison to some existing methods used widely and is suitable for predictions on high-resolution protein crystal (⩽2.5 Å) and nonpeptide ligand as individual inputs. Our approach to network construction and training on protein-ligand data set prepared in-house has yielded significant insights. We have also tested DEELIG on few COVID-19 main protease-inhibitor complexes relevant to the current public health scenario. DEELIG-based predictions can be incorporated in existing databases including RSCB PDB, PDBMoad, and PDBbind in filling missing binding affinity data for protein-ligand complexes.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-07-08T03:40:08Z
      DOI: 10.1177/11779322211030364
      Issue No: Vol. 15 (2021)
       
  • In Silico Integrative Approach Revealed Key MicroRNAs and Associated
           Target Genes in Cardiorenal Syndrome

    • Authors: Mohd Murshad Ahmed, Romana Ishrat, Safia Tazyeen, Aftab Alam, Anam Farooqui, Rafat Ali, Nikhat Imam, Naaila Tamkeen, Shahnawaz Ali, Md Zubbair Malik, Armiya Sultan
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Cardiorenal syndromes constellate primary dysfunction of either heart or kidney whereby one organ dysfunction leads to the dysfunction of another. The role of several microRNAs (miRNAs) has been implicated in number of diseases, including hypertension, heart failure, and kidney diseases. Wide range of miRNAs has been identified as ideal candidate biomarkers due to their stable expression. Current study was aimed to identify crucial miRNAs and their target genes associated with cardiorenal syndrome and to explore their interaction analysis. Three differentially expressed microRNAs (DEMs), namely, hsa-miR-4476, hsa-miR-345-3p, and hsa-miR-371a-5p, were obtained from GSE89699 and GSE87885 microRNA data sets, using R/GEO2R tools. Furthermore, literature mining resulted in the retrieval of 15 miRNAs from scientific research and review articles. The miRNAs-gene networks were constructed using miRNet (a Web platform of miRNA-centric network visual analytics). CytoHubba (Cytoscape plugin) was adopted to identify the modules and the top-ranked nodes in the network based on Degree centrality, Closeness centrality, Betweenness centrality, and Stress centrality. The overlapped miRNAs were further used in pathway enrichment analysis. We found that hsa-miR-21-5p was common in 8 pathways out of the top 10. Based on the degree, 5 miRNAs, namely, hsa-mir-122-5p, hsa-mir-222-3p, hsa-mir-21-5p, hsa-mir-146a-5p, and hsa-mir-29b-3p, are considered as key influencing nodes in a network. We suggest that the identified miRNAs and their target genes may have pathological relevance in cardiorenal syndrome (CRS) and may emerge as potential diagnostic biomarkers.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-30T11:21:51Z
      DOI: 10.1177/11779322211027396
      Issue No: Vol. 15 (2021)
       
  • In Silico Identification and Functional Characterization of Conserved
           miRNAs in the Genome of Cryptosporidium parvum

    • Authors: Md. Irtija Ahsan, Md. Shahidur Rahman Chowdhury, Moumita Das, Sharmin Akter, Sawrab Roy, Binayok Sharma, Rubaiat Nazneen Akhand, Mahmudul Hasan, Md Bashir Uddin, Syed Sayeem Uddin Ahmed
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Cryptosporidium parvum, a predominant causal agent of a fatal zoonotic protozoan diarrhoeal disease called cryptosporidiosis, bears a worldwide public health concern for childhood mortality and poses a key threat to the dairy and water industries. MicroRNAs (miRNAs), small but powerful posttranscriptional gene silencing RNA molecules, regulate a variety of molecular, biological, and cellular processes in animals and plants. As to the present date, there is a paucity of information regarding miRNAs of C. parvum; hence, this study was used to identify miRNAs in the organism using a comprehensible expressed sequence tag–based homology search approach consisting of a series of computational screening process from the identification of putative miRNA candidates to the functional annotation of the important gene targets in C. parvum. The results revealed a conserved miRNA that targeted 487 genes in the model organism (Drosophila melanogaster) and 85 genes in C. parvum, of which 11 genes had direct involvements in several crucial virulence factors such as environmental oocyst protection, excystation, locomotion, adhesion, invasion, stress protection, intracellular growth, and survival. Besides, 20 genes showed their association with various major pathways dedicated for the ribosomal biosynthesis, DNA repair, transportation, protein production, gene expression, cell cycle, cell proliferation, development, immune response, differentiation, and nutrient metabolism of the organism in the host. Thus, this study provides a strong evidence of great impact of identified miRNA on the biology, virulence, and pathogenesis of C. parvum. Furthermore, the study suggests that the detected miRNA could be a potential epigenomic tool for controlling the protozoon through silencing those virulent and pathway-related target genes.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-28T06:31:05Z
      DOI: 10.1177/11779322211027665
      Issue No: Vol. 15 (2021)
       
  • Performance of Regression Models as a Function of Experiment Noise

    • Authors: Gang Li, Jan Zrimec, Boyang Ji, Jun Geng, Johan Larsbrink, Aleksej Zelezniak, Jens Nielsen, Martin KM Engqvist
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Background:A challenge in developing machine learning regression models is that it is difficult to know whether maximal performance has been reached on the test dataset, or whether further model improvement is possible. In biology, this problem is particularly pronounced as sample labels (response variables) are typically obtained through experiments and therefore have experiment noise associated with them. Such label noise puts a fundamental limit to the metrics of performance attainable by regression models on the test dataset.Results:We address this challenge by deriving an expected upper bound for the coefficient of determination (R2) for regression models when tested on the holdout dataset. This upper bound depends only on the noise associated with the response variable in a dataset as well as its variance. The upper bound estimate was validated via Monte Carlo simulations and then used as a tool to bootstrap performance of regression models trained on biological datasets, including protein sequence data, transcriptomic data, and genomic data.Conclusions:The new method for estimating upper bounds for model performance on test data should aid researchers in developing ML regression models that reach their maximum potential. Although we study biological datasets in this work, the new upper bound estimates will hold true for regression models from any research field or application area where response variables have associated noise.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-28T05:55:10Z
      DOI: 10.1177/11779322211020315
      Issue No: Vol. 15 (2021)
       
  • In Silico Exploration of Phytoconstituents From Phyllanthus emblica and
           Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp

    • Authors: Khushboo Pandey, Kiran Bharat Lokhande, K Venkateswara Swamy, Shuchi Nagar, Manjusha Dake
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100 ns molecular dynamics (MD) simulation followed by post-simulation analysis. Furthermore, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that EBDGp possesses a stronger binding affinity (−23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (−19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity toward SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-24T09:52:34Z
      DOI: 10.1177/11779322211027403
      Issue No: Vol. 15 (2021)
       
  • Structure and Function of Major SARS-CoV-2 and SARS-CoV Proteins

    • Authors: Ritesh Gorkhali, Prashanna Koirala, Sadikshya Rijal, Ashmita Mainali, Adesh Baral, Hitesh Kumar Bhattarai
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      SARS-CoV-2 virus, the causative agent of COVID-19 pandemic, has a genomic organization consisting of 16 nonstructural proteins (nsps), 4 structural proteins, and 9 accessory proteins. Relative of SARS-CoV-2, SARS-CoV, has genomic organization, which is very similar. In this article, the function and structure of the proteins of SARS-CoV-2 and SARS-CoV are described in great detail. The nsps are expressed as a single or two polyproteins, which are then cleaved into individual proteins using two proteases of the virus, a chymotrypsin-like protease and a papain-like protease. The released proteins serve as centers of virus replication and transcription. Some of these nsps modulate the host’s translation and immune systems, while others help the virus evade the host immune system. Some of the nsps help form replication-transcription complex at double-membrane vesicles. Others, including one RNA-dependent RNA polymerase and one exonuclease, help in the polymerization of newly synthesized RNA of the virus and help minimize the mutation rate by proofreading. After synthesis of the viral RNA, it gets capped. The capping consists of adding GMP and a methylation mark, called cap 0 and additionally adding a methyl group to the terminal ribose called cap1. Capping is accomplished with the help of a helicase, which also helps remove a phosphate, two methyltransferases, and a scaffolding factor. Among the structural proteins, S protein forms the receptor of the virus, which latches on the angiotensin-converting enzyme 2 receptor of the host and N protein binds and protects the genomic RNA of the virus. The accessory proteins found in these viruses are small proteins with immune modulatory roles. Besides functions of these proteins, solved X-ray and cryogenic electron microscopy structures related to the function of the proteins along with comparisons to other coronavirus homologs have been described in the article. Finally, the rate of mutation of SARS-CoV-2 residues of the proteome during the 2020 pandemic has been described. Some proteins are mutated more often than other proteins, but the significance of these mutation rates is not fully understood.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-22T09:50:46Z
      DOI: 10.1177/11779322211025876
      Issue No: Vol. 15 (2021)
       
  • Reconstructing Draft Genomes Using Genome Resolved Metagenomics Reveal
           Arsenic Metabolizing Genes and Secondary Metabolites in Fresh Water Lake
           in Eastern India

    • Authors: Samrat Ghosh, Aditya Narayan Sarangi, Mayuri Mukherjee, Deeksha Singh, Madduluri Madhavi, Sucheta Tripathy
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Rabindra Sarovar lake is an artificial freshwater lake in the arsenic infested eastern region of India. In this study, using the genome resolved metagenomics approach; we have deciphered the taxonomic diversity as well as the functional insights of the gene pools specific to this region. Initially, a total of 113 Metagenome Assembled Genomes (MAGs) were recovered from the two predominant seasons, that is, rainy (n = 50) and winter (n = 63). After bin refinement and de-replication, 27 MAGs (18 from Winter season and 9 from Rainy season) were reconstructed. These MAGs were either of high-quality (n = 10) or of medium quality (n = 17) that was determined based on genome completeness and contamination. These 27 MAGs spanning across 6 bacterial phyla and the most predominant ones were Proteobacteria, Bacteroidetes, and Cyanobacteria regardless of the season. Functional annotation across the MAGs suggested the existence of all known types of arsenic resistance and metabolism genes. Besides, important secondary metabolites such as zoocin_A, prochlorosin, and microcin were also abundantly present in these genomes. The metagenomic study of this lake provides the first insights into the microbiome composition and functional classification of the gene pools in two predominant seasons. The presence of arsenic metabolism and resistance genes in the recovered genomes is a sign of adaptation of the microbes to the arsenic contamination in this region. The presence of secondary metabolite genes in the lake microbiome has several implications including the potential use of these for the pharmaceutical industry.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-22T07:30:49Z
      DOI: 10.1177/11779322211025332
      Issue No: Vol. 15 (2021)
       
  • Comparison of Hyaluronic Acid Biosynthetic Genes From Different Strains of
           Pasteurella multocida

    • Authors: Pailin Pasomboon, Pramote Chumnanpuen, Teerasak E-kobon
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Pasteurella multocida produces a capsule composed of different polysaccharides according to the capsular serotype (A, B, D, E, and F). Hyaluronic acid (HA) is a component of certain capsular types of this bacterium, especially capsular type A. Previously, 2 HA biosynthetic genes from a capsular type A strain were studied for the industrial-scale improvement of HA production. Molecular comparison of these genes across different capsular serotypes of P multocida has not been reported. This study aimed to compare 8 HA biosynthetic genes (pgi, pgm, galU, hyaC, glmS, glmM, glmU, and hyaD) of 22 P multocida strains (A:B:D:F = 6:6:6:4) with those of other organisms using sequence and structural bioinformatics analyses. These 8 genes showed a high level of within-species similarity (98%-99%) compared with other organisms. Only the last gene of 4 strains with capsular type F (HN07, PM70, HNF01, and HNF02) significantly differed from those of other strains (82%). Analysis of amino acid patterns together with phylogenetic results showed that the HA biosynthetic genes of the type A were closely related within the group. The genes in the capsular type F strain were notably similar to those of the capsular type A strain. Protein structural analysis supported structural similarities of the encoded enzymes between the strains of capsular types A, B, D, and F, except for the Pgm, GlmS, GlmU, and HyaD proteins. Our bioinformatics analytic workflow proposed that variations observed within these genes could be useful for genetic engineering–based improvement of hyaluronic acid–producing enzymes.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-21T11:07:40Z
      DOI: 10.1177/11779322211027406
      Issue No: Vol. 15 (2021)
       
  • A Computational-Based Drug Repurposing Method Targeting SARS-CoV-2 and its
           Neurological Manifestations Genes and Signaling Pathways

    • Authors: Ali Sepehrinezhad, Fariborz Rezaeitalab, Ali Shahbazi, Sajad Sahab-Negah
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a global concern involves infections in multiple organs. Much of the research up to now has been descriptive on neurological manifestations followed by SARS-CoV-2 infection. Despite considerable efforts on effective SARS-CoV-2 vaccine, novel therapeutic options for COVID-19 comorbidities are warranted. One of the fast ways to introduce possible effective drugs for clinical trials is bioinformatics methods. We have conducted a comprehensive enrichment analysis of genes involved in SARS-CoV-2 and neurological disorders associated with COVID-19. For this purpose, gene sets were extracted from the GeneWeaver database. To find out some significant enriched findings for common genes between SARS-CoV-2 and its neurological disorders, several practical databases were used. Finally, to repurpose an efficient drug, DrugBank databases were used. Overall, we detected 139 common genes concerning SARS-CoV-2 and their neurological disorders. Interestingly, our study predicted around 6 existing drugs (ie, carvedilol, andrographolide, 2-methoxyestradiol, etanercept, polaprezinc, and arsenic trioxide) that can be used for repurposing. We found that polaprezinc (zinc l-carnosine) drug is not investigated in the context of COVID-19 till now and it could be used for the treatment of COVID-19 and its neurological manifestations. To summarize, enrichment and network data get us a coherent picture to predict drug repurposing to speed up clinical trials.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-18T08:22:04Z
      DOI: 10.1177/11779322211026728
      Issue No: Vol. 15 (2021)
       
  • Prediction of Human-Plasmodium vivax Protein Associations From
           Heterogeneous Network Structures Based on Machine-Learning Approach

    • Authors: Apichat Suratanee, Teerapong Buaboocha, Kitiporn Plaimas
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Malaria caused by Plasmodium vivax can lead to severe morbidity and death. In addition, resistance has been reported to existing drugs in treating this malaria. Therefore, the identification of new human proteins associated with malaria is urgently needed for the development of additional drugs. In this study, we established an analysis framework to predict human-P. vivax protein associations using network topological profiles from a heterogeneous network structure of human and P. vivax, machine-learning techniques and statistical analysis. Novel associations were predicted and ranked to determine the importance of human proteins associated with malaria. With the best-ranking score, 411 human proteins were identified as promising proteins. Their regulations and functions were statistically analyzed, which led to the identification of proteins involved in the regulation of membrane and vesicle formation, and proteasome complexes as potential targets for the treatment of P. vivax malaria. In conclusion, by integrating related data, our analysis was efficient in identifying potential targets providing an insight into human-parasite protein associations. Furthermore, generalizing this model could allow researchers to gain further insights into other diseases and enhance the field of biomedical science.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-16T07:32:45Z
      DOI: 10.1177/11779322211013350
      Issue No: Vol. 15 (2021)
       
  • Inhibitory Potential of Phytochemicals on Interleukin-6-Mediated T-Cell
           Reduction in COVID-19 Patients: A Computational Approach

    • Authors: Arif Malik, Anam Naz, Sajjad Ahmad, Mansoor Hafeez, Faryal Mehwish Awan, Tassadaq Hussain Jafar, Ayesha Zahid, Aqsa Ikram, Bisma Rauff, Mubashir Hassan
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Background:A recent COVID-19 pandemic has resulted in a large death toll rate globally and even no cure or vaccine has been successfully employed to combat this disease. Patients have been reported with multi-organ dysfunction along with acute respiratory distress syndrome which implies a critical situation for patients and made them difficult to breathe and survive. Moreover, pathology of COVID-19 is also related to cytokine storm which indicates the elevated levels of interleukin (IL)-1, IL-6, IL-12, and IL-18 along with tumor necrosis factor (TNF)-α. Among them, the proinflammatory cytokine IL-6 has been reported to be induced via binding of severe acute respiratory syndrome coronavirus 2 (SARS)-CoV-2 to the host receptors.Methodology:Interleukin-6 blockade has been proposed to constitute novel therapeutics against COVID-19. Thus, in this study, 15 phytocompounds with known antiviral activity have been subjected to test for their inhibitory effect on IL-6. Based on the affinity prediction, top 3 compounds (isoorientin, lupeol, and andrographolide) with best scores were selected for 50 ns molecular dynamics simulation and MMGB/PBSA binding free energy analysis.Results:Three phytocompounds including isoorientin, lupeol, and andrographolide have shown strong interactions with the targeted protein IL-6 with least binding energies (−7.1 to −7.7 kcal/mol). Drug-likeness and ADMET profiles of prioritized phytocompounds are also very prominsing and can be further tested to be potential IL-6 blockers and thus benficial for COVID-19 treatment. The moelcular dynamics simulation couple with MMGB/PBSA binding free energy estimation validated conformational stability of the ligands and stronger intermolecular binding. The mean RMSD of the complexes is as: IL6-isoorientin complex (3.97 Å ± 0.77), IL6-lupeol (3.97 Å ± 0.76), and IL6-andrographolide complex (3.96 Å ± 0.77). In addition, the stability observation was affirmed by compounds mean RMSD: isoorientin (0.72 Å ± 0.32), lupeol (mean 0.38 Å ± 0.08), and andrographolide (1.09 Å ± 0.49). A similar strong agreement on systems stability was unraveled by MMGB/PBSA that found net binding net ~ −20 kcal/mol for the complexes dominated by van der Waal interaction energy.Conclusion:It has been predicted that proposing potential IL-6 inhibitors with less side effects can help critical COVID-19 patients because it may control the cytokine storm, a major responsible factor of its pathogenesis. In this study, 3 potential phytocompounds have been proposed to have inhibitory effect on IL-6 that can be tested as potential therapeutic options against SARS-CoV-2.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-08T12:52:19Z
      DOI: 10.1177/11779322211021430
      Issue No: Vol. 15 (2021)
       
  • Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal

    • Authors: Sergio Diaz-del-Pino, Esteban Perez-Wohlfeil, Oswaldo Trelles
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computational methods that are able to compare large genomic sequences, thus enabling large-scale studies of genome evolution. The field of comparative genomics has proven itself invaluable for studying the evolutionary mechanisms and the forces driving genome evolution. In this line, a full genome comparison study between 2 species requires a quadratic number of comparisons in terms of the number of sequences (around 400 chromosome comparisons in the case of mammalian genomes); however, when studying conserved syntenies or evolutionary rearrangements, many sequence comparisons can be skipped for not all will contain significant signals. Subsequently, the scientific community has developed fast heuristics to perform multiple pairwise comparisons between large sequences to determine whether significant sets of conserved similarities exist. The data generation problem is no longer an issue, yet the limitations have shifted toward the analysis of such massive data. Therefore, we present XCout, a Web-based visual analytics application for multiple genome comparisons designed to improve the analysis of large-scale evolutionary studies using novel techniques in Web visualization. XCout enables to work on hundreds of comparisons at once, thus reducing the time of the analysis by identifying significant signals between chromosomes across multiple species. Among others, XCout introduces several techniques to aid in the analysis of large-scale genome rearrangements, particularly (1) an interactive heatmap interface to display comparisons using automatic color scales based on similarity thresholds to ease detection at first sight, (2) an overlay system to detect individual signal contributions between chromosomes, (3) a tracking tool to trace conserved blocks across different species to perform evolutionary studies, and (4) a search engine to search annotations throughout different species.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-08T12:47:39Z
      DOI: 10.1177/11779322211021422
      Issue No: Vol. 15 (2021)
       
  • DGraph Clusters Flaviviruses and β-Coronaviruses According to Their
           Hosts, Disease Type, and Human Cell Receptors

    • Authors: Benjamin A Braun, Catherine H Schein, Werner Braun
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Motivation:There is a need for rapid and easy-to-use, alignment-free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is an application developed to generate 2-dimensional (2D) maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such “PD-graphs” show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities.Results:Property distance graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors, and disease phenotypes. Property distance graphs separate the tick- from the mosquito-borne FV, cluster viruses that infect bats, camels, seabirds, and humans separately. The clusters correlate with disease phenotype. The PD method segregates the β-CoV spike proteins of severe acute respiratory syndrome (SARS), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and Middle East respiratory syndrome (MERS) sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-07T11:25:26Z
      DOI: 10.1177/11779322211020316
      Issue No: Vol. 15 (2021)
       
  • Bioinformatics Analysis Unveils Certain Mutations Implicated in Spike
           Structure Damage and Ligand-Binding Site of Severe Acute Respiratory
           Syndrome Coronavirus 2

    • Authors: Emre Aktas
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      There are certain mutations related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In addition to these known mutations, other new mutations have been found across regions in this study. Based on the results, in which 4,326 SARS-CoV-2 whole sequences were used, some mutations are found to be peculiar with certain regions, while some other mutations are found in all regions. In Asia, mutations (3 different mutations in QLA46612 isolated from South Korea) were found in the same sequence. Although huge number of mutations are detected (more than 70 in Asia) by regions, according to bioinformatics tools, some of them which are G75V (isolated from North America), T95I (isolated from South Korea), G143V (isolated from North America), M177I (isolated from Asia), L293M (isolated from Asia), P295H (isolated from Asia), T393P (isolated from Europe), P507S (isolated from Asia), and D614G (isolated from all regions) (These color used only make correct) predicted a damage to spike’ protein structure. Furthermore, this study also aimed to reveal how binding sites of ligands change if the spike protein structure is damaged, and whether more than one mutation affects ligand binding. Mutations that were predicted to damage the structure did not affect the ligand-binding sites, whereas ligands’ binding sites were affected in those with multiple mutations. It is thought that this study will give a different perspective to both the vaccine SARS-CoV studies and the change in the structure of the spike protein belonging to this virus against mutations.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-06-02T08:23:34Z
      DOI: 10.1177/11779322211018200
      Issue No: Vol. 15 (2021)
       
  • Significance of African Diets in Biotherapeutic Modulation of the Gut
           Microbiome

    • Authors: PO Isibor, PA Akinduti, OS Aworunse, JO Oyewale, O Oshamika, HU Ugboko, OS Taiwo, EF Ahuekwe, YD Obafemi, EA Onibokun, O Oziegbe, MI Oniha, BK Olopade, OM Atolagbe, BT Adekeye, IB Ajiboye, OA Bello, JO Popoola, OI Ayanda, OO Akinnola, GI Olasehinde, AO Eni, OC Nwinyi, CA Omonhinmin, SU Oranusi, OO Obembe
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Diet plays an essential role in human development and growth, contributing to health and well-being. The socio-economic values, cultural perspectives, and dietary formulation in sub-Saharan Africa can influence gut health and disease prevention. The vast microbial ecosystems in the human gut frequently interrelate to maintain a healthy, well-coordinated cellular and humoral immune signalling to prevent metabolic dysfunction, pathogen dominance, and induction of systemic diseases. The diverse indigenous diets could differentially act as biotherapeutics to modulate microbial abundance and population characteristics. Such modulation could prevent stunted growth, malnutrition, induction of bowel diseases, attenuated immune responses, and mortality, particularly among infants. Understanding the associations between specific indigenous African diets and the predictability of the dynamics of gut bacteria genera promises potential biotherapeutics towards improving the prevention, control, and treatment of microbiome-associated diseases such as cancer, inflammatory bowel disease, obesity, type 2 diabetes, and cardiovascular disease. The dietary influence of many African diets (especially grain-base such as millet, maize, brown rice, sorghum, soya, and tapioca) promotes gut lining integrity, immune tolerance towards the microbiota, and its associated immune and inflammatory responses. A fibre-rich diet is a promising biotherapeutic candidate that could effectively modulate inflammatory mediators’ expression associated with immune cell migration, lymphoid tissue maturation, and signalling pathways. It could also modulate the stimulation of cytokines and chemokines involved in ensuring balance for long-term microbiome programming. The interplay between host and gut microbial digestion is complex; microbes using and competing for dietary and endogenous proteins are often attributable to variances in the comparative abundances of Enterobacteriaceae taxa. Many auto-inducers could initiate the process of quorum sensing and mammalian epinephrine host cell signalling system. It could also downregulate inflammatory signals with microbiota tumour taxa that could trigger colorectal cancer initiation, metabolic type 2 diabetes, and inflammatory bowel diseases. The exploitation of essential biotherapeutic molecules derived from fibre-rich indigenous diet promises food substances for the downregulation of inflammatory signalling that could be harmful to gut microbiota ecological balance and improved immune response modulation.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-04-28T06:39:39Z
      DOI: 10.1177/11779322211012697
      Issue No: Vol. 15 (2021)
       
  • Anticancer Potential of Moringa oleifera on BRCA-1 Gene: Systems Biology

    • Authors: Toheeb A Balogun, Kaosarat D Buliaminu, Onyeka S Chukwudozie, Zainab A Tiamiyu, Taiwo J Idowu
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Breast cancer has consistently been a global challenge that is prevalent among women. There is a continuous increase in the high number of women mortality rates because of breast cancer and affecting nations at all modernization levels. Women with high-risk factors, including hereditary, obesity, and menopause, have the possibility of developing breast cancer growth. With the advent of radiotherapy, chemotherapy, hormone therapy, and surgery in breast cancer treatment, breast cancer survivors have increased. Also, the design and development of drugs targeting therapeutic enzymes effectively treat the tumour cells early. However, long-term use of anticancer drugs has been linked to severe side effects. This research aims to develop potential drug candidates from Moringa oleifera, which could serve as anticancer agents. In silico analysis using Schrödinger Molecular Drug Discovery Suite and SWISS ADME was employed to determine the therapeutic potential of phytochemicals from M oleifera against breast cancer via molecular docking, pharmacokinetic parameters, and drug-like properties. The result shows that rutin, vicenin-2, and quercetin-3-O-glucoside have the highest binding energy of −7.522, −6.808, and −6.635 kcal/mol, respectively, in the active site of BRCA-1. The essential amino acids involved in the protein-ligand interaction following active site analysis are ASN 1678, ASN 1774, GLY 1656, LEU 1657, GLN 1779, LYS 1702, SER 1655, PHE 1662, ARG 1699, GLU 1698, and VAL 1654. Thus, we propose that bioactive compounds from M oleifera may be potential novel drug candidates in the treatment of breast cancer.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-04-28T06:33:39Z
      DOI: 10.1177/11779322211010703
      Issue No: Vol. 15 (2021)
       
  • In Silico Characterization of a Hypothetical Protein from Shigella
           dysenteriae ATCC 12039 Reveals a Pathogenesis-Related Protein of the
           Type-VI Secretion System

    • Authors: Md. Fazley Rabbi, Saiwda Asma Akter, Md. Jaimol Hasan, Al Amin
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Shigellosis caused by Shigella dysenteriae is a major public health concern worldwide, particularly in developing countries. The bacterial genome is known, but there are many hypothetical proteins whose functions are yet to be discovered. A hypothetical protein (accession no. WP_128879999.1, 161 residues) of S. dysenteriae ATCC 12039 strain was selected in this study for comprehensive structural and functional analysis. Subcellular localization and different physicochemical properties of this hypothetical protein were estimated indicating it as a stable, soluble, and extracellular protein. Functional annotation tools, such as NCBI-CD Search, Pfam, and InterProScan, predicted our target protein to be an amidase effector protein 4 (Tae4) of type-VI secretion system (T6SS). Multiple sequence alignment of the homologous sequences coincided with previous findings. Random coil was found to be predominant in secondary structure. Three-dimensional (3D) structure of the protein was obtained using homology modeling method by SWISS-MODEL server using a template protein (PDB ID: 4J30) of 80.12% sequence identity. The 3D structure became more stable after YASARA energy minimization and was validated by several quality assessment tools like PROCHECK, QMEAN, Verify3D, and ERRAT. Superimposition of the target with the template protein by UCSF Chimera generated RMSD value of 0.115 Å, suggesting a reliable 3D structure. The active site of the modeled structure was predicted and visualized by CASTp server and PyMOL. Interestingly, similar binding affinity and key interacting residues were found for the target protein and a Salmonella enterica Tae4 protein with the ligand L-Ala D-Glu-mDAP by molecular docking analysis. Protein-protein docking was also performed between the target protein and hemolysin coregulated protein 1 of T6SS. Finally, the protein was found to be a unique protein of S. dysenteriae nonhomologous to human by comparative genomics approach indicating a potential therapeutic target. Most pathogens harboring T6SS in their system pose a significant threat to the human health. Many T6SSs and their effectors are associated with interbacterial competition, pathogenesis, and virulency; however, relationships between these effectors and pathogenicity of S. dysenteriae are yet to be determined. The study findings provide a lucrative platform for future antibacterial treatment.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-04-22T06:23:45Z
      DOI: 10.1177/11779322211011140
      Issue No: Vol. 15 (2021)
       
  • Prediction of Anti-COVID 19 Therapeutic Power of Medicinal Moroccan Plants
           Using Molecular Docking

    • Authors: Badreddine Nouadi, Abdelkarim Ezaouine, Mariame El Messal, Mohamed Blaghen, Faiza Bennis, Fatima Chegdani
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      The emerging pathogen SARS-CoV2 causing coronavirus disease 2019 (COVID-19) is a global public health challenge. To the present day, COVID-19 had affected more than 40 million people worldwide. The exploration and the development of new bioactive compounds with cost-effective and specific anti-COVID 19 therapeutic power is the prime focus of the current medical research. Thus, the exploitation of the molecular docking technique has become essential in the discovery and development of new drugs, to better understand drug-target interactions in their original environment. This work consists of studying the binding affinity and the type of interactions, through molecular docking, between 54 compounds from Moroccan medicinal plants, dextran sulfate and heparin (compounds not derived from medicinal plants), and 3CLpro-SARS-CoV-2, ACE2, and the post fusion core of 2019-nCoV S2 subunit. The PDB files of the target proteins and prepared herbal compounds (ligands) were subjected for docking to AutoDock Vina using UCSF Chimera, which provides a list of potential complexes based on the criteria of form complementarity of the natural compound with their binding affinities. The results of molecular docking revealed that Taxol, Rutin, Genkwanine, and Luteolin-glucoside have a high affinity with ACE2 and 3CLpro. Therefore, these natural compounds can have 2 effects at once, inhibiting 3CLpro and preventing recognition between the virus and ACE2. These compounds may have a potential therapeutic effect against SARS-CoV2, and therefore natural anti-COVID-19 compounds.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-04-09T06:36:13Z
      DOI: 10.1177/11779322211009199
      Issue No: Vol. 15 (2021)
       
  • In Silico Analysis of Partial Fatty Acid Desaturase 2 cDNA From Reutealis
           trisperma (Blanco) Airy Shaw

    • Authors: Nurul Jadid, Indah Prasetyowati, Nur Laili Alfina Rosidah, Dini Ermavitalini, Sri Nurhatika, Tutik Nurhidayati, Hery Purnobasuki
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Reutealis trisperma oil is a new source for biodiesel production. The predominant fatty acids in this plant are stearic acid (9%), palmitic acid (10%), oleic acid (12%), linoleic acid (19%), and α-eleostearic acid (51%). The presence of polyunsaturated fatty acids (PUFAs), linoleic acid, and α-eleostearic acid decreases the oxidation stability of R. trisperma biodiesel. Although several studies have suggested that the fatty acid desaturase 2 (FAD2) enzyme is involved in the regulation of fatty acid desaturation, little is known about the genetic information of FAD2 in R. trisperma. The objectives of this study were to isolate, characterize, and determine the relationship between the R. trisperma FAD2 fragment and other Euphorbiaceae plants. cDNA fragments were isolated using reverse transcription polymerase chain reaction (PCR). The DNA sequence obtained by sequencing was used for further analysis. In silico analysis identified the fragment identity, subcellular localization, and phylogenetic construction of the R. trisperma FAD2 cDNA fragment and Euphorbiaceae. The results showed that a 923-bp partial sequence of R. trisperma FAD2 was successfully isolated. Based on in silico analysis, FAD2 was predicted to encode 260 amino acids, had a domain similarity with Omega-6 fatty acid desaturase, and was located in the endoplasmic reticulum membrane. The R. trisperma FAD2 fragment was more closely related to Vernicia fordii (HM755946.1).
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-03-27T02:26:21Z
      DOI: 10.1177/11779322211005747
      Issue No: Vol. 15 (2021)
       
  • Modeling and Molecular Dynamic Simulation of F(ab′)2 Fragment of
           Nimotuzumab for Lung Cancer Diagnostics

    • Authors: Yurika Sastyarina, Ade Rizqi Ridwan Firdaus, Zuhrotun Nafisah, Ari Hardianto, Muhammad Yusuf, Martalena Ramli, Abdul Mutalib, Ukun MS Soedjanaatmadja
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Lung cancer is one of the leading causes of cancer-related deaths in the world among both men and women. Several studies in the literature report that overexpression and mutation of the epidermal growth factor receptor (EGFR) are implicated in the pathogenesis of some lung cancers. Nimotuzumab is a humanized monoclonal antibody (mAb) that inhibits EGF binding because it binds to the extracellular domain of the EGFR. Nimotuzumab requires bivalent binding for stable attachment to cellular surface, which leads to nimotuzumab selectively binding to cells that express mAbs of moderate to high EGFR levels, and this could explain its low toxicity. This property has an advantage for development of nimotuzumab as a therapeutic and diagnostic agent. Monoclonal antibodies are large in size (150 kDa), thus penetrating slowly and residing in the blood for extended periods of time (from days to weeks); their use in imaging studies can result in low signal-to-background ratios and poor image quality. A reduction in the size of the immunoglobulin molecule has also been proposed as a means for increasing tumor penetration by mAbs. Nevertheless, it is known that the penetration of mAb into tumor cell is slow, due to its high molecular weight. Therefore, mAb is not very attractive to be used for imaging diagnostic purpose because of its kinetics and potential to elicit antibody response. The objective of this research was to study the homology modeling of a simpler functional molecule based on nimotuzumab, which consists of 2 antigen-binding fragments (Fab), namely, F(ab′)2, using MODELER. The crystal structure of Fab of nimotuzumab from protein data bank was used as a template to construct the model of F(ab′)2. Molecular dynamic simulation was performed to evaluate the stability of F(ab′)2 and conformational changes of F(ab′)2 in simulation. The result showed the dynamic behavior of antigen-binding site region of F(ab′)2 throughout simulation. This result is expected to be useful in the further development of F(ab′)2 fragment nimotuzumab as a lung cancer diagnostic.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-03-25T09:42:21Z
      DOI: 10.1177/11779322211002174
      Issue No: Vol. 15 (2021)
       
  • The Relevance of Bioinformatics Applications in the Discovery of Vaccine
           Candidates and Potential Drugs for COVID-19 Treatment

    • Authors: Onyeka S Chukwudozie, Vincent C Duru, Charlotte C Ndiribe, Abdullahi T Aborode, Victor O Oyebanji, Benjamin O Emikpe
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      The application of bioinformatics to vaccine research and drug discovery has never been so essential in the fight against infectious diseases. The greatest combat of the 21st century against a debilitating disease agent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus discovered in Wuhan, China, December 2019, has piqued an unprecedented usage of bioinformatics tools in deciphering the molecular characterizations of infectious pathogens. With the viral genome data of SARS-COV-2 been made available barely weeks after the reported outbreak, bioinformatics platforms have become an all-time critical tool to gain time in the fight against the disease pandemic. Before the outbreak, different platforms have been developed to explore antigenic epitopes, predict peptide-protein docking and antibody structures, and simulate antigen-antibody reactions and lots more. However, the advent of the pandemic witnessed an upsurge in the application of these pipelines with the development of newer ones such as the Coronavirus Explorer in the development of efficacious vaccines, drug repurposing, and/or discovery. In this review, we have explored the various pipelines available for use, their relevance, and limitations in the timely development of useful therapeutic candidates from genomic data knowledge to clinical therapy.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-03-15T10:47:14Z
      DOI: 10.1177/11779322211002168
      Issue No: Vol. 15 (2021)
       
  • Metagenomics Approaches to Investigate the Gut Microbiome of COVID-19
           Patients

    • Authors: Sofia Sehli, Imane Allali, Rajaa Chahboune, Youssef Bakri, Najib Al Idrissi, Salsabil Hamdi, Chakib Nejjari, Saaïd Amzazi, Hassan Ghazal
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Over the last decade, it has become increasingly apparent that the microbiome is a central component in human well-being and illness. However, to establish innovative therapeutic methods, it is crucial to learn more about the microbiota. Thereby, the area of metagenomics and associated bioinformatics methods and tools has become considerable in the study of the human microbiome biodiversity. The application of these metagenomics approaches to studying the gut microbiome in COVID-19 patients could be one of the promising areas of research in the fight against the SARS-CoV-2 infection and disparity. Therefore, understanding how the gut microbiome is affected by or could affect the SARS-CoV-2 is very important. Herein, we present an overview of approaches and methods used in the current published studies on COVID-19 patients and the gut microbiome. The accuracy of these researches depends on the appropriate choice and the optimal use of the metagenomics bioinformatics platforms and tools. Interestingly, most studies reported that COVID-19 patients’ microbiota are enriched with opportunistic microorganisms. The choice and use of appropriate computational tools and techniques to accurately investigate the gut microbiota is therefore critical in determining the appropriate microbiome profile for diagnosis and the most reliable antiviral or preventive microbial composition.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-03-12T07:18:44Z
      DOI: 10.1177/1177932221999428
      Issue No: Vol. 15 (2021)
       
  • Identification and Characterisation of Putative Enhancer Elements in Mouse
           Embryonic Stem Cells

    • Authors: Anna Mantsoki, Karla Parussel, Anagha Joshi
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Enhancer elements control mammalian transcription largely in a cell-type-specific manner. The genome-wide identification of enhancer elements and their activity status in a cellular context is therefore fundamental to understanding cell identity and function. We determined enhancer activity in mouse embryonic stem (ES) cells using chromatin modifications and characterised their global properties. Specifically, we first grouped enhancers into 5 groups using multiple H3K4me1, H3K27ac, and H3K27me3 modification data sets. Active enhancers (simultaneous presence of H3K4me1 and H3K27ac) were enriched for binding of pluripotency factors and were found near pluripotency-related genes. Although both H3K4me1-only and active enhancers were enriched for super-enhancers and a TATA box like motif, active enhancers were preferentially bound by RNA polII (s2) and were enriched for bidirectional transcription, while H3K4me1-only enhancers were enriched for RNA polII (8WG16) suggesting they were likely poised. Bivalent enhancers (simultaneous presence of H3K4me1 and H3K27me3) were preferentially in the vicinity of bivalent genes. They were enriched for binding of components of polycomb complex as well as Tcf3 and Oct4. Moreover, a ‘CTTTCTC’ de-novo motif was enriched at bivalent enhancers, previously identified at bivalent promoters in ES cells. Taken together, 3 histone modifications successfully demarcated active, bivalent, and poised enhancers with distinct sequence and binding features.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-02-09T09:12:51Z
      DOI: 10.1177/1177932220974623
      Issue No: Vol. 15 (2021)
       
  • Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a
           Systems Biology Approach

    • Authors: Mozhdeh Shahmoradi, Zahra Rezvani
      Abstract: Bioinformatics and Biology Insights, Volume 15, Issue , January-December 2021.
      Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding RNAs (lncRNAs) are a new type of noncoding transcripts that their dysregulations are associated with almost all cancers including melanoma. However, the precise functional roles of most of the significantly altered lncRNAs in melanoma have not yet been fully inspected. In this study, a comprehensive list of lncRNAs was interrogated across cutaneous melanoma samples to identify the significantly altered/dysregulated lncRNAs. To this end, lncRNAs were filtered in several steps and the selected lncRNAs projected to a bioinformatic and systems biology analysis using several publicly available databases and tools such as GEPIA and cBioPortal. According to our results, 30 lncRNAs were notably altered/dysregulated in cutaneous melanoma most of which were co-expressed with each other. Also, co-expression/alteration and differential expression analyses led to the selection of 12 out of these 30 lncRNAs as cutaneous melanoma key lncRNAs. Furthermore, functional demonstrated that these 12 lncRNAs might be involved in melanoma-relevant biological processes and pathways. In addition, the end result of our analyses demonstrated that these lncRNAs are associated with the clinicopathological features of melanoma patients. These 12 lncRNAs need to be further investigated in future studies to characterize their exact roles in melanoma development and to identify their potential for being used as drug targets and/or biomarkers for cutaneous melanoma.
      Citation: Bioinformatics and Biology Insights
      PubDate: 2021-02-04T05:50:58Z
      DOI: 10.1177/1177932220988508
      Issue No: Vol. 15 (2021)
       
 
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