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BIOTECHNOLOGY (244 journals)                  1 2 | Last

Showing 1 - 200 of 244 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 8)
Advanced Biomedical Research     Open Access  
Advances in Bioscience and Biotechnology     Open Access   (Followers: 17)
Advances in Genetic Engineering & Biotechnology     Hybrid Journal   (Followers: 9)
Advances in Regenerative Medicine     Open Access   (Followers: 3)
African Journal of Biotechnology     Open Access   (Followers: 6)
Algal Research     Partially Free   (Followers: 11)
American Journal of Biochemistry and Biotechnology     Open Access   (Followers: 69)
American Journal of Bioinformatics Research     Open Access   (Followers: 7)
American Journal of Polymer Science     Open Access   (Followers: 33)
Amylase     Open Access  
Anadolu University Journal of Science and Technology : C Life Sciences and Biotechnology     Open Access  
Animal Biotechnology     Hybrid Journal   (Followers: 8)
Annales des Sciences Agronomiques     Full-text available via subscription  
Applied Biochemistry and Biotechnology     Hybrid Journal   (Followers: 45)
Applied Biosafety     Hybrid Journal  
Applied Food Biotechnology     Open Access   (Followers: 3)
Applied Microbiology and Biotechnology     Hybrid Journal   (Followers: 67)
Applied Mycology and Biotechnology     Full-text available via subscription   (Followers: 4)
Arthroplasty Today     Open Access   (Followers: 1)
Artificial Cells, Nanomedicine and Biotechnology     Hybrid Journal   (Followers: 1)
Asia Pacific Biotech News     Hybrid Journal   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 9)
Asian Pacific Journal of Tropical Biomedicine     Open Access   (Followers: 2)
Australasian Biotechnology     Full-text available via subscription   (Followers: 1)
Banat's Journal of Biotechnology     Open Access  
BBR : Biochemistry and Biotechnology Reports     Open Access   (Followers: 5)
Beitr?ge zur Tabakforschung International/Contributions to Tobacco Research     Open Access   (Followers: 3)
Bio-Algorithms and Med-Systems     Hybrid Journal   (Followers: 2)
Bio-Research     Full-text available via subscription   (Followers: 4)
Bioactive Materials     Open Access   (Followers: 1)
Biocatalysis and Agricultural Biotechnology     Hybrid Journal   (Followers: 4)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 5)
Bioethics UPdate     Hybrid Journal   (Followers: 1)
Biofuels     Hybrid Journal   (Followers: 11)
Biofuels Engineering     Open Access   (Followers: 1)
Biological & Pharmaceutical Bulletin     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomarkers and Genomic Medicine     Open Access   (Followers: 3)
Biomaterials Research     Open Access   (Followers: 4)
BioMed Research International     Open Access   (Followers: 4)
Biomédica     Open Access  
Biomedical and Biotechnology Research Journal     Open Access  
Biomedical Engineering Research     Open Access   (Followers: 6)
Biomedical Glasses     Open Access  
Biomedical Reports     Full-text available via subscription  
BioMedicine     Open Access  
Biomedika     Open Access  
Bioprinting     Hybrid Journal   (Followers: 1)
Bioresource Technology Reports     Hybrid Journal   (Followers: 1)
Bioscience, Biotechnology, and Biochemistry     Hybrid Journal   (Followers: 21)
Biosensors Journal     Open Access  
Biosimilars     Open Access   (Followers: 1)
Biosurface and Biotribology     Open Access  
Biotechnic and Histochemistry     Hybrid Journal   (Followers: 1)
BioTechniques : The International Journal of Life Science Methods     Full-text available via subscription   (Followers: 28)
Biotechnologia Acta     Open Access   (Followers: 1)
Biotechnologie, Agronomie, Société et Environnement     Open Access   (Followers: 2)
Biotechnology     Open Access   (Followers: 8)
Biotechnology & Biotechnological Equipment     Open Access   (Followers: 4)
Biotechnology Advances     Hybrid Journal   (Followers: 34)
Biotechnology and Applied Biochemistry     Hybrid Journal   (Followers: 44)
Biotechnology and Bioengineering     Hybrid Journal   (Followers: 160)
Biotechnology and Bioprocess Engineering     Hybrid Journal   (Followers: 6)
Biotechnology and Genetic Engineering Reviews     Hybrid Journal   (Followers: 13)
Biotechnology and Health Sciences     Open Access   (Followers: 1)
Biotechnology and Molecular Biology Reviews     Open Access   (Followers: 2)
Biotechnology Annual Review     Full-text available via subscription   (Followers: 5)
Biotechnology for Biofuels     Open Access   (Followers: 10)
Biotechnology Frontier     Open Access   (Followers: 2)
Biotechnology Journal     Hybrid Journal   (Followers: 17)
Biotechnology Law Report     Hybrid Journal   (Followers: 4)
Biotechnology Letters     Hybrid Journal   (Followers: 34)
Biotechnology Progress     Hybrid Journal   (Followers: 41)
Biotechnology Reports     Open Access  
Biotechnology Research International     Open Access   (Followers: 1)
Biotechnology Techniques     Hybrid Journal   (Followers: 10)
Biotecnología Aplicada     Open Access  
Bioteknologi (Biotechnological Studies)     Open Access  
BIOTIK : Jurnal Ilmiah Biologi Teknologi dan Kependidikan     Open Access  
Biotribology     Hybrid Journal   (Followers: 1)
BMC Biotechnology     Open Access   (Followers: 17)
Cell Biology and Development     Open Access  
Chinese Journal of Agricultural Biotechnology     Full-text available via subscription   (Followers: 4)
Communications in Mathematical Biology and Neuroscience     Open Access  
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computer Methods and Programs in Biomedicine     Hybrid Journal   (Followers: 8)
Copernican Letters     Open Access   (Followers: 1)
Critical Reviews in Biotechnology     Hybrid Journal   (Followers: 20)
Crop Breeding and Applied Biotechnology     Open Access   (Followers: 3)
Current Bionanotechnology     Hybrid Journal  
Current Biotechnology     Hybrid Journal   (Followers: 4)
Current Opinion in Biomedical Engineering     Hybrid Journal   (Followers: 1)
Current Opinion in Biotechnology     Hybrid Journal   (Followers: 55)
Current Pharmaceutical Biotechnology     Hybrid Journal   (Followers: 9)
Current Research in Bioinformatics     Open Access   (Followers: 13)
Current Trends in Biotechnology and Chemical Research     Open Access   (Followers: 3)
Current trends in Biotechnology and Pharmacy     Open Access   (Followers: 8)
DNA and RNA Nanotechnology     Open Access  
EBioMedicine     Open Access  
Electronic Journal of Biotechnology     Open Access  
Entomologia Generalis     Full-text available via subscription   (Followers: 1)
Environmental Science : Processes & Impacts     Full-text available via subscription   (Followers: 4)
Experimental Biology and Medicine     Hybrid Journal   (Followers: 3)
Folia Medica Indonesiana     Open Access  
Food Bioscience     Hybrid Journal  
Food Biotechnology     Hybrid Journal   (Followers: 9)
Food Science and Biotechnology     Hybrid Journal   (Followers: 8)
Frontiers in Bioengineering and Biotechnology     Open Access   (Followers: 6)
Frontiers in Systems Biology     Open Access   (Followers: 2)
Fungal Biology and Biotechnology     Open Access   (Followers: 2)
GM Crops and Food: Biotechnology in Agriculture and the Food Chain     Full-text available via subscription   (Followers: 1)
GSTF Journal of BioSciences     Open Access  
HAYATI Journal of Biosciences     Open Access  
Horticultural Biotechnology Research     Open Access  
Horticulture, Environment, and Biotechnology     Hybrid Journal   (Followers: 11)
IEEE Transactions on Molecular, Biological and Multi-Scale Communications     Hybrid Journal   (Followers: 1)
IET Nanobiotechnology     Hybrid Journal   (Followers: 2)
IN VIVO     Full-text available via subscription   (Followers: 4)
Indian Journal of Biotechnology (IJBT)     Open Access   (Followers: 2)
Indonesia Journal of Biomedical Science     Open Access   (Followers: 2)
Indonesian Journal of Biotechnology     Open Access   (Followers: 1)
Indonesian Journal of Medicine     Open Access  
Industrial Biotechnology     Hybrid Journal   (Followers: 18)
International Biomechanics     Open Access  
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 14)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 4)
International Journal of Biomedical Research     Open Access   (Followers: 2)
International Journal of Biotechnology     Hybrid Journal   (Followers: 5)
International Journal of Biotechnology and Molecular Biology Research     Open Access   (Followers: 4)
International Journal of Biotechnology for Wellness Industries     Partially Free   (Followers: 1)
International Journal of Environment, Agriculture and Biotechnology     Open Access   (Followers: 5)
International Journal of Functional Informatics and Personalised Medicine     Hybrid Journal   (Followers: 4)
International Journal of Medicine and Biomedical Research     Open Access   (Followers: 1)
International Journal of Nanotechnology and Molecular Computation     Full-text available via subscription   (Followers: 3)
International Journal of Radiation Biology     Hybrid Journal   (Followers: 4)
Iranian Journal of Biotechnology     Open Access  
ISABB Journal of Biotechnology and Bioinformatics     Open Access  
Italian Journal of Food Science     Open Access   (Followers: 1)
JMIR Biomedical Engineering     Open Access  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 3)
Journal of Bioterrorism & Biodefense     Open Access   (Followers: 6)
Journal of Petroleum & Environmental Biotechnology     Open Access   (Followers: 1)
Journal of Advanced Therapies and Medical Innovation Sciences     Open Access  
Journal of Advances in Biotechnology     Open Access   (Followers: 5)
Journal Of Agrobiotechnology     Open Access  
Journal of Analytical & Bioanalytical Techniques     Open Access   (Followers: 7)
Journal of Animal Science and Biotechnology     Open Access   (Followers: 4)
Journal of Applied Biomedicine     Open Access   (Followers: 2)
Journal of Applied Biotechnology     Open Access   (Followers: 2)
Journal of Applied Biotechnology Reports     Open Access   (Followers: 2)
Journal of Applied Mathematics & Bioinformatics     Open Access   (Followers: 5)
Journal of Biologically Active Products from Nature     Hybrid Journal   (Followers: 1)
Journal of Biomaterials and Nanobiotechnology     Open Access   (Followers: 6)
Journal of Biomedical Photonics & Engineering     Open Access  
Journal of Biomedical Practitioners     Open Access  
Journal of Bioprocess Engineering and Biorefinery     Full-text available via subscription  
Journal of Bioprocessing & Biotechniques     Open Access  
Journal of BioScience and Biotechnology     Open Access  
Journal of Biosecurity Biosafety and Biodefense Law     Hybrid Journal   (Followers: 3)
Journal of Biotechnology     Hybrid Journal   (Followers: 63)
Journal of Biotechnology and Strategic Health Research     Open Access   (Followers: 1)
Journal of Chemical and Biological Interfaces     Full-text available via subscription   (Followers: 1)
Journal of Chemical Technology & Biotechnology     Hybrid Journal   (Followers: 9)
Journal of Chitin and Chitosan Science     Full-text available via subscription   (Followers: 1)
Journal of Colloid Science and Biotechnology     Full-text available via subscription  
Journal of Commercial Biotechnology     Full-text available via subscription   (Followers: 6)
Journal of Crop Science and Biotechnology     Hybrid Journal   (Followers: 3)
Journal of Ecobiotechnology     Open Access  
Journal of Essential Oil Research     Hybrid Journal   (Followers: 2)
Journal of Experimental Biology     Full-text available via subscription   (Followers: 25)
Journal of Genetic Engineering and Biotechnology     Open Access   (Followers: 5)
Journal of Ginseng Research     Open Access  
Journal of Industrial Microbiology and Biotechnology     Hybrid Journal   (Followers: 18)
Journal of Integrative Bioinformatics     Open Access  
Journal of Medical Imaging and Health Informatics     Full-text available via subscription  
Journal of Molecular Biology and Biotechnology     Open Access  
Journal of Molecular Microbiology and Biotechnology     Full-text available via subscription   (Followers: 13)
Journal of Nano Education     Full-text available via subscription  
Journal of Nanobiotechnology     Open Access   (Followers: 4)
Journal of Nanofluids     Full-text available via subscription   (Followers: 1)
Journal of Organic and Biomolecular Simulations     Open Access  
Journal of Plant Biochemistry and Biotechnology     Hybrid Journal   (Followers: 4)
Journal of Science and Applications : Biomedicine     Open Access  
Journal of the Mechanical Behavior of Biomedical Materials     Hybrid Journal   (Followers: 13)
Journal of Trace Elements in Medicine and Biology     Hybrid Journal   (Followers: 1)
Journal of Tropical Microbiology and Biotechnology     Full-text available via subscription  
Journal of Yeast and Fungal Research     Open Access   (Followers: 1)
Marine Biotechnology     Hybrid Journal   (Followers: 4)
Meat Technology     Open Access  
Messenger     Full-text available via subscription  
Metabolic Engineering Communications     Open Access   (Followers: 4)
Metalloproteinases In Medicine     Open Access  
Microbial Biotechnology     Open Access   (Followers: 10)
MicroMedicine     Open Access   (Followers: 3)
Molecular and Cellular Biomedical Sciences     Open Access   (Followers: 1)
Molecular Biotechnology     Hybrid Journal   (Followers: 13)
Molecular Genetics and Metabolism Reports     Open Access   (Followers: 3)
Nanobiomedicine     Open Access  
Nanobiotechnology     Hybrid Journal   (Followers: 2)

        1 2 | Last

Journal Cover
Network Modeling and Analysis in Health Informatics and Bioinformatics
Journal Prestige (SJR): 0.201
Citation Impact (citeScore): 1
Number of Followers: 3  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2192-6662 - ISSN (Online) 2192-6670
Published by Springer-Verlag Homepage  [2352 journals]
  • Probing the structural requirements for angiotensin II receptor: molecular
           modeling studies
    • Authors: M. C. Sharma; Dharm V. Kohli
      Abstract: The present study describes the development of 3D-QSAR studies on angiotensin II receptor based on the selected pharmacophore model. A four-point pharmacophore with one hydrogen bond acceptor (A), one hydrophobic (H), and two aromatic ring features (R) as pharmacophore features was developed by PHASE module. The pharmacophore hypothesis yielded a statistically significant model with good partial least-squares results. Thus, obtained 3D-QSAR model with partial least-squares (PLS) factor regression coefficient value (r2 = 0.9547) for training set and high value of cross-validated correlation coefficient Q2 = 0.7418, root-mean-squared error RMSE = 0.1257. This model was found to yield reliable clues for the further optimization of benzimidazole derivatives in the dataset, which plays an important role in molecular drug design approach.
      PubDate: 2018-04-24
      DOI: 10.1007/s13721-018-0167-z
      Issue No: Vol. 7, No. 1 (2018)
  • Cancer drug target identification and node-level analysis of the network
           of MAPK pathways
    • Authors: V. K. MD Aksam; V. M. Chandrasekaran; Sundaramurthy Pandurangan
      Abstract: Mitogen-activated protein kinase (MAPK) pathways extensively studied in cancer and governing intertwined biological process challenges to identify the efficient drug target strategy. Cross-talks among ERK1/2, ERK5, JNK, and p38 amplify signaling flow and lead to the construction of the network of MAPK pathways. A topological analysis reveals that the network exponentially fits the degree distributions and targeting hub proteins causes detrimental to the network. We aim to identify novel drug targets controlling pathological consequences in the signaling flow than killing the cell. Intra-pathway node inhibition causes less perturbation in the network. We set the strategy of considering low degree (< 5) and intra-pathway nodes free from the intertwined regulations as preliminary isolation. Furthermore, nodes with less functionally diverse and significantly contributing to the cancer are isolated using GO annotations. Elements in the network of the MAPK pathways catalogued and analyzed using protein types, subcellular localization, cancerous/non-cancerous nature, target/non-targeted status, and inter- and intra-pathway properties to illustrate their roles in the complex mechanism of cancer. Over a decade of kinases as promising drug targets for cancer, other signal transduction supporting proteins also found to be equally competent. However, kinases interact with various other proteins to gain the higher degree. Similarly, translocation proteins interact with their partners in diverse location to gain the degree and functionally vital. Inhibition of kinases and translocation proteins may draw unexpected side effects. Non-targeted nodes Mos, PAC1, MKP4, 4EBP1, LAD, M3/6, RNPK, and SRF identified as cancer drug targets.
      PubDate: 2018-03-23
      DOI: 10.1007/s13721-018-0165-1
      Issue No: Vol. 7, No. 1 (2018)
  • A hybrid analytic approach for understanding patient demand for mental
           health services
    • Authors: Stephan Kudyba
      Abstract: The increase in digital/data resources available in the healthcare sector has heightened the emphasis of applying analytics to extract information to provide solutions to problems. However, the process of providing analytic-based healthcare solutions may introduce factors that require multiple analytic techniques or a hybrid approach. Data resources can involve complexities including formatting and volume issues or multiplicity of sub-tasks in achieving a full problem solution. This work extends the previous research on AI in forecasting patient demand and adds clustering methods to identify the types of ailments that need to be treated according to diagnostic codes. The hybrid approach is applied to data from a US-based psychiatry/behavioral health center and the results indicate clustering can add value to demand forecasts established by AI by identifying the type of ailments that patients require treatment for. With this information, care providers can better optimize staffing resources to meet demand in a cost-effective and efficient way by better understanding not only the amount of patient demand, but also the type of treatment that is required for select ailments.
      PubDate: 2018-03-14
      DOI: 10.1007/s13721-018-0164-2
      Issue No: Vol. 7, No. 1 (2018)
  • Trifluorophenyl-based inhibitors of dipeptidyl peptidase-IV as
           antidiabetic agents: 3D-QSAR COMFA, CoMSIA methodologies
    • Authors: M. C. Sharma; S. Jain; R. Sharma
      Abstract: 3D-QSAR CoMFA and CoMSIA studies were performed on a set of trifluorophenyl derivatives as dipeptidyl peptidase IV inhibitors. Based on the results, predictive QSAR models were established, with cross-validated coefficient values (q 2) up to 0.879 for CoMFA. CoMSIA model developed using combination of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor features has shown q 2 (cross-validated) 0.875. These developed models may be useful in the identification and optimization of novel scaffolds with potent dipeptidyl peptidase IV activity.
      PubDate: 2017-12-18
      DOI: 10.1007/s13721-017-0163-8
      Issue No: Vol. 7, No. 1 (2017)
  • Systems biology approach deciphering the biochemical signaling pathway and
           pharmacokinetic study of PI3K/mTOR/p53-Mdm2 module involved in neoplastic
    • Authors: Devender Arora; Ajeet Singh
      Abstract: Cancer is a serious health concern growing at a rapid speed where normal cells take neoplastic transformation. Different pathway is tightly regulated with each other to maintain the harmony and sudden changes in single protein leads to aberrant changes in the whole system. Development of drugs to target these proteins aimed to block the signaling route that leads to cell death. Here, in this study, we performed in silico expression analysis of these potential proteins using system biological approach by mimicking the cell and understanding the behavior of different proteins in drugging condition. We performed in silico biomolecular interaction analysis for exploring the potential plant-derived compounds that can be served as an anticancerous drug with least toxicity by comparing with reference drug approved by FDA. Our results suggest that PI3K, p53-Mdm2 proteins are ideal proteins for targeting cancer cells, while overexpression of mTOR protein was observed when drug targeted this receptor. We state that PI3K family protein plays important role in drug discovery, and compounds obtained from in silico analysis can be served as a potential anticancerous drug for treating different cancer types.
      PubDate: 2017-12-18
      DOI: 10.1007/s13721-017-0162-9
      Issue No: Vol. 7, No. 1 (2017)
  • Pharmadoop: a tool for pharmacophore searching using Hadoop framework
    • Authors: Rahul Semwal; Imlimaong Aier; Utkarsh Raj; Pritish Kumar Varadwaj
      Abstract: The term pharmacophore is used to define the important features of one or more molecules having the same biological activity. Pharmacophores are selected based on several common features, such as the type of functional groups present, the distance between each atom or group of atoms and the angle between such groups or an individual atom. In this paper, we present the design and implementation of a pharmacophore searching tool, Pharmadoop, using the Hadoop framework. Due to its Hadoop implementation, Pharmadoop is a faster approach as compared to the existing standalone pharmacophore search tools. It utilizes the MapReduce algorithm to support the comparison of millions of conformers in a short time span. We further demonstrated and compared the utility of Pharmadoop on ten distinct chemical datasets of ligand molecules by running common substructure searching job on standalone and multi-system Hadoop platforms. These results were further used to perform pharmacophore searching applications on standalone and multi-node Hadoop distributions. The performance, speed and accuracy of the tool were evaluated through time-scale analysis and receiver operating curve. The Pharmadoop tool can be accessed at
      PubDate: 2017-11-01
      DOI: 10.1007/s13721-017-0161-x
      Issue No: Vol. 6, No. 1 (2017)
  • Prediction of structural requirements of AT 1 receptor through application
           of pharmacophore-based 3D-QSAR studies
    • Authors: M. C. Sharma; D. V. Kohli
      Abstract: In the present study, two/three-dimensional quantitative structure activity relationship models using 2D QSAR and pharmacophore approaches were developed for a series of benzimidazole derivatives as angiotensin II receptor AT1 receptor antagonists. The 2D QSAR model was developed using partial least square analysis in VLife MDS and helps in identifying the descriptors. The best 2D QSAR equation has squared correlation coefficient (r 2) 0.8162. Pharmacophore hypothesis significant 3D-QSAR model with partial least square factor (r 2 = 0.9391) and (Q 2 = 0.7155), for the set of compounds. The study provides new compounds designing of more potent antihypertensive agents in the future before their synthesis.
      PubDate: 2017-10-17
      DOI: 10.1007/s13721-017-0160-y
      Issue No: Vol. 6, No. 1 (2017)
  • On adverse drug event extractions using twitter sentiment analysis
    • Authors: Melody Moh; Teng-Sheng Moh; Yang Peng; Liang Wu
      Abstract: Extensive clinical trials are required before a drug is placed on the market. It is, however, difficult to discover all the side effects, or adverse drug effects (ADE), for any approved drugs due to the limited number of required clinical trials before a drug is approved. The pervasive online social networks, such as Twitter, can provide additional information on ADE. Concurrently, advancements in social media technology have resulted in the booming of massive public data; the availability of these huge datasets offers numerous research opportunities for extracting ADEs. Towards this purpose, in this paper two effective computation pipelines are proposed, which use drug-related classification and sentiment analysis to extract ADEs on Twitter. The two pipelines are described in detail, and are implemented into automatic processes. Both pipelines are first separately evaluated, and then compared in parallel. Based on 25 days of Twitter data, the first pipeline has successfully predicted 79.4% of drug-related tweets with user opinions. The second pipeline, with its much simpler design, is able to identify much more ADE, as well as discover more new ADE. Based on 4 months of Twitter data collected, the second design is able to successfully capture 5 times more valid ADE than the first design, with 12 times more new ADEs discovered. We believe that these two proposed pipelines are promising methods for extracting ADEs in social networks, and may be applied to additional areas such as food, beverages, and other daily consumer products for identifying side effects and user opinions.
      PubDate: 2017-09-18
      DOI: 10.1007/s13721-017-0159-4
      Issue No: Vol. 6, No. 1 (2017)
  • Topology of protein–protein interaction network and edge reduction
           co-efficiency in VEGF signaling of breast cancer
    • Authors: Sharath Belenahalli Shekarappa; Shivananda Kandagalla; Pavan Gollapalli; Bharath Basavapattana Rudresh; Thriveni Hanumanthappa; Manjunatha Hanumanthappa
      Abstract: Here, we summarize the identification of possible hub protein in the core VEGF-induced interactome in breast cancer by the application of centrality measures. This approach has been extended to investigate the role of subnetworks in the core interactome. For the identification of subnetworks, we applied a protein network-based approach to find the novel insight in the function of pathways involved in breast cancer. A PPI network was constructed and the complexity of network was simplified to modules using molecular complex detection algorithm. Topological analysis of PPI network was performed to assess the functional significance of selected genes using KEGG and PubAngioGen database. Globally accepted centrality measure, Betweenness centrality, Degree distribution and Clustering co-efficient metrics were used to find the hub protein by scale-free network analysis. The bottleneck nodes in the subnetworks were found to be involved in regulating endothelial cell proliferation, central carbon metabolism, signal complex assembly, Phosphatidylinositol 3-kinase (PI3K), Vascular endothelial growth factor (VEGF), Erb-B receptor tyrosine kinase (ErbB) and prolactin signaling pathway. Wherein, main interconnecting hub nodes find their predominant distribution. Moreover, these main hub nodes were subjected to power graph analysis to further reduce the number of edges to 80% without losing the basic biological information, as it helps us to understand much better about highly interconnected nodes.
      PubDate: 2017-09-15
      DOI: 10.1007/s13721-017-0157-6
      Issue No: Vol. 6, No. 1 (2017)
  • Three-dimensional finite element model to study calcium distribution in
    • Authors: Parvaiz Ahmad Naik; Kamal Raj Pardasani
      Abstract: Calcium is the most universal second messenger in cells and plays an important role in initiation, sustenance and termination of various activities in cells required for maintaining the structure and function of the cell. Calcium signal at fertilization is necessary for egg activation and exhibits specialized spatial and temporal dynamics. The specific calcium concentration distribution patterns in oocytes required for various activities such as egg fertilization and maturation are not well understood. In this paper, a three-dimensional finite element model is proposed to study the spatio-temporal calcium distribution in oocyte. The parameters such as buffers, SERCA pump, RyR calcium channel, point source and line source of calcium are incorporated in the model. The appropriate initial and boundary conditions have been framed on the basis of physical condition of the problem. A program is developed in MATLAB for simulation. The results have been used to study the effect of source geometry, RyR calcium channel, SERCA pump and buffers on cytosolic calcium concentration distribution in oocyte.
      PubDate: 2017-09-13
      DOI: 10.1007/s13721-017-0158-5
      Issue No: Vol. 6, No. 1 (2017)
  • A novel preventative solution for effective asthma management: a practical
    • Authors: Subrata Acharya; Reza Sarraf
      Abstract: In recent years, there has been an increased growth in the use of smart applications to better care and manage various medical conditions. Recent studies have concluded that the daily management via an application improves asthma control compared to manual or paper-based monitoring (Fonseca et al. in Allergy 61(3):389–390, 2006). To this effect, this research aims to study existing asthma applications and propose a holistic approach to asthma care and management by developing a novel Android application that provides a real-time, multi-way communication between patients and providers (healthcare, insurance, food, drug, etc.). The current state-of-the-art smart applications are able to aid users send information to their physicians typically via email; however, healthcare providers still need to contact patients through the traditional methods (phone, email, or face-to-face appointments). Our proposed multi-way communication can eliminate phone calls, emails, and appointment scheduling to save time and provide real-time feedback to the patients. Furthermore, providers can monitor the health status of patients remotely by checking their patient specific journal entry and set new and/or modified action plans and also uploads those to the patient’s smart devices. Providers can also send notifications to patients even if the device is in sleep mode. In case of emergency, patients are able to call 911 or find the nearest hospital and pharmacy via a pre-programmed one-click method. We have conducted extensive evaluation studies (both pre- and post) at a nationally recognized HIMSS Stage 6 regional trauma center (>500 beds) and its affiliated 23 associated clinical practices. The results confirm that the proposed solution has a strong potential to significantly improve the quality of care while reducing the overall cost of care delivery for the target population. In addition, the HIMSS 6 organization has availed meaningful use incentive programs due to these measures. We are also aiding the healthcare organization to conduct analysis of their patient data to provide various training seminars to facilitate effective management of this chronic condition. In the upcoming years, our goal is to continue to collaborate with the provider to help in designing proactive solutions for other chronic conditions, such as diabetes, heart disease, obesity, etc.
      PubDate: 2017-08-28
      DOI: 10.1007/s13721-017-0156-7
      Issue No: Vol. 6, No. 1 (2017)
  • A comparison of soft computing models for Parkinson’s disease diagnosis
           using voice and gait features
    • Authors: Rekh Ram Janghel; Anupam Shukla; Chandra Prakash Rathore; Kshitiz Verma; Swati Rathore
      Abstract: Parkinson’s disease is a widespread disease among elder population worldwide caused by dopamine loss, which reduces quality of life because of motor and non-motor complications. In the current paper, nine soft computing models, i.e., Cubist, Cubist Committees, Random Forests, Kernel Support Vector Machine, Linear Regression, Naïve Bayes, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System, and Hybrid Neuro-Fuzzy Inference System are implemented for Parkinson’s disease diagnosis using voice and gait features. Later, their performances are evaluated based on performance measures, viz., true positive, false positive, false negative, true negative, accuracy, sensitivity, specificity, and RMSE, and finally, a comparison is performed to identify the most efficient model and data set combination. The comparison demonstrated that Random Forest model outperformed others yielding 100% accuracy, 100% sensitivity, 100% specificity, and zero RMSE on voice and gait training data sets both; Cubist Committees model outperformed others yielding 74.00% accuracy, 69.39% sensitivity, 78.43% specificity, and 0.4582 RMSE on voice testing data set; Random Forest model once again outperformed others yielding 81.66% accuracy, 92.39% sensitivity, 66.67% specificity, and 0.4283 RMSE on gait testing data set. Furthermore, these models’ performances are also evaluated on reduced feature vector voice and gait data sets obtained by Principal Component Analysis, and compared with their performances on former data sets. The comparison exhibited that the soft computing models’ performance decreases by reducing feature vector of the data sets.
      PubDate: 2017-07-25
      DOI: 10.1007/s13721-017-0155-8
      Issue No: Vol. 6, No. 1 (2017)
  • Disease genes prioritizing mechanisms: a comprehensive and systematic
           literature review
    • Authors: Elaheh Seyyedrazzagi; Nima Jafari Navimipour
      Abstract: Recognition of disease genes and using the computational techniques are considered as the basic issue in biomedical and bioinformatics examines. One of the initial problems in human health is recognizing the most probable disease genes among a huge number of candidates. However, in spite of the significance of computational approaches and their role in recognition of disease gene, there is not any comprehensive, systematic and detailed survey about researching on and analyzing its important techniques. Therefore, in this paper, we analyze these mechanisms in three categories, including network-based, machine learning-based and computation tools. Furthermore, we provide the open issues and guidelines for future research. Also, this paper presents a systematic literature review of disease genes prioritizing literature up to the end of 2016. We identified 238 papers, which are reduced to 19 primary studies using a selection process. Both academics and practicing professionals will be directly supported by this survey through providing state-of-the-art information in their conception of developments in disease genes prioritizing methods.
      PubDate: 2017-07-22
      DOI: 10.1007/s13721-017-0154-9
      Issue No: Vol. 6, No. 1 (2017)
  • On the interpretation of the effects of the Infliximab treatment on
           Crohn’s disease patients from Facebook posts: a human vs. machine
    • Authors: Marco Roccetti; Paola Salomoni; Catia Prandi; Gustavo Marfia; Silvia Mirri
      Abstract: This paper completes an analysis started a few years ago which has exploited Facebook as a tool suitable for collecting and analyzing Crohn’s disease patients’ reactions to the Infliximab treatment. We here finish off such work by comparing the satisfaction recorded with the use of sentiment analysis techniques as provided by intelligent tools for subjectivity analysis (e.g., OpinionFinder) against the satisfaction recorded by human experts (both physicians and non-medical experts). In summary, the following results appear to be of particular interest: (i) the Infliximab treatment confirms its efficacy as a result of the interpretations of Facebook posts given by both automatic tools and human experts, (ii) physicians tend to classify as neutral many posts on Infliximab that non-medical experts classified as negative, and (iii) OpinionFinder is inclined to confirm the evaluations provided by medical experts.
      PubDate: 2017-06-26
      DOI: 10.1007/s13721-017-0152-y
      Issue No: Vol. 6, No. 1 (2017)
  • A pulse wave monitoring system based on a respiratory pacemaker
    • Authors: Yutaka Kameda; Koji Kashihara
      Abstract: We constructed a reasonable healthcare monitoring system with pulse wave and respiratory analysis to assess blood vessel conditions and the autonomic function in daily life. Filter circuits with an infrared sensor were carefully designed to complete the peripheral pulse wave measurement and analysis, considering individual differences to a pulse sensor and the potential for the system to be used as wearable devices and applications. The analyzer for our system is capable of predicting arterial states and stiffness. A user interface with a respiratory pacemaker can assist voluntary breathing, visualize pulse wave features, and regulate them in real time. The user interface software is widely compatible and could be easily applied to mobile healthcare devices. We also evaluated how respiration control reflected pulse rate variability [i.e., fluctuations in peak-to-peak intervals (PPI)] associated with the autonomic nervous system. An experimental study under various breathing rates was performed using the created user interface with a respiratory pacemaker. The transfer gain of the PPI caused resonance at the respiratory rate of 0.1 Hz (p < 0.5), corresponding to the sufficiently stimulated vagal tone of the heart. A simulation study revealed that the fuzzy inference indicates the robustness of respiratory regulation to maximize the amplitude of PPI oscillations under the inclusion of individual difference and unexpected response. As future perspective, the respiratory pacemaker used to regulate the pulse wave feature could be applied to an effective recovery support system especially under blunted autonomic function such as during mental stress and hypoxia.
      PubDate: 2017-06-26
      DOI: 10.1007/s13721-017-0153-x
      Issue No: Vol. 6, No. 1 (2017)
  • Exploration of new scaffolds pyrazole derivatives containing thiourea
           skeleton as anticancer activity using QSAR approach
    • Authors: M. C. Sharma; S. Sharma
      Abstract: A forty six compounds series of potential epidermal growth factor receptor kinase inhibitors of pyrazole derivatives containing thiourea analogs were subjected to quantitative structure–activity relationship analyses. The QSAR model developed gave good predictive correlation coefficient (r 2) of 0.8225, significant cross-validated correlation coefficient (q 2) of 0.7322, r 2 for external test set (pred_r 2) 0.7883 was developed. It will be useful to build a QSAR model to predict and optimize the properties and activities of pyrazole derivatives and determine key structural requirements for their enhanced anticancer activity.
      PubDate: 2017-06-08
      DOI: 10.1007/s13721-017-0151-z
      Issue No: Vol. 6, No. 1 (2017)
  • Molecular modeling and molecular dynamics simulation-based structural
           analysis of GPR3
    • Authors: Aman Chandra Kaushik; Shakti Sahi
      Abstract: G protein-coupled receptor 3 (GPR3) is an orphan GPCR; GPR3 has been reported to play a key role in Alzheimer’s disease through modulation of amyloid-beta production. The understanding of molecular mechanism involved has been limited due to unavailability of crystal structure of GPR3 and lack of different specific agonists. In this paper, we report the modeled 3D structure of GPR3 using threading and ab initio techniques with an objective to understand the mechanism underlying its interaction with agonists. The predicted model was optimized through 50 ns molecular dynamics simulation. Molecular dynamics (MD) simulation for 50 ns was performed on the 3D model of GPR3 embedded in 1-hexadecanoyl-2-(9Z-octadecenoyl)-sn-glycero-3-phosphocholine (POPC) lipid bilayer with aqueous system using OPLS (optimized potentials for liquid simulations) force field. The MD trajectories were analyzed to optimize the helical bundle conformations, active site, and 7TM domain variability during production phase of simulation. Binding pocket gave an insight into the size and chemical nature of compounds which could be potential agonists. The optimized structure would be significant in screening potential ligands through virtual screening.
      PubDate: 2017-04-28
      DOI: 10.1007/s13721-017-0150-0
      Issue No: Vol. 6, No. 1 (2017)
  • Block spectral clustering for multiple graphs with inter-relation
    • Authors: Chuan Chen; Michael Ng; Shuqin Zhang
      Abstract: Clustering methods for multiple graphs explore and exploit multiple graphs simultaneously to obtain a more accurate and robust partition of the data than that using single graph clustering methods. In this paper, we study the clustering of multiple graphs with inter-relation among vertices in different graphs. The main contribution is to propose and develop a block spectral clustering method for multiple graphs with inter-relation. Our idea is to construct a block Laplacian matrix for multiple graphs and make use of its eigenvectors to perform clustering very efficiently. Global optimal solutions are obtained in the proposed method and they are solutions of relaxation of multiple graphs ratio cut and normalized cut problems. In contrast, existing clustering methods cannot guarantee optimal solutions and their solutions are dependent on initial guesses. Experimental results on both synthetic and real-world data sets are given to demonstrate that the clustering accuracy achieved and computational time required by the proposed block clustering method are better than those by the testing clustering methods in the literature.
      PubDate: 2017-04-26
      DOI: 10.1007/s13721-017-0149-6
      Issue No: Vol. 6, No. 1 (2017)
  • Toward leveraging big value from data: chronic lymphocytic leukemia cell
    • Authors: Emad A. Mohammed; Mostafa M. A. Mohamed; Christopher Naugler; Behrouz H. Far
      Abstract: The goal of Big Data analysis is delineating hidden patterns from data and leverage them into strategies and plans to support informed decision making in a diversity of situations. Big Data are characterized by large volume, high velocity, wide variety, and high value, which may represent difficulties in storage and processing. Research on Big Data repositories has contributed promising results that primarily address how to efficiently mine a variety of large volume of structured and unstructured data. However, innovative insights can emerge while leveraging the value characteristic of Big Data. In other words, any given data can be big if analytics can draw a big value from it. In this paper, we demonstrate the potential of five machine learning algorithms to leverage the value of medium size microscopic blood smear images to classify patients with chronic lymphocytic leukemia (CLL). The maximum majority voting method is used to fuse the predications made by the five classifier models. To validate this work, 11 CLL patients are refereed by flow cytometry equipment and the results are compared to the proposed classifier model. The proposed method proceeds through a sequence of steps while working with the lymphocyte images: it segments the lymphocyte images, extracts/selects features, classifies the selected features using five classifiers, and calculates the majority class for the test image. The proposed composite classifier model has an accuracy of 87.0%, true-positive rate of 84.95%, and 10.96% false-positive rate and can correctly identify 9 out of 11 patients as positive for CLL.
      PubDate: 2017-02-18
      DOI: 10.1007/s13721-017-0146-9
      Issue No: Vol. 6, No. 1 (2017)
  • Identification of potential transcription factor and protein kinases for
           regulation of differentially expressed genes for fluoride exposure in
           human using Expression2Kinases (X2K) approach
    • Abstract: Fluorosis due to longtime exposure of fluoride with deleterious public health problem is common in developed and developing countries. Researches demonstrated that fluoride induces the gene expression and causes apoptosis. The present study aims to predict potential transcription factor (TF) and associated protein kinase which are responsible for the regulation of gene expression exposure of fluoride. In this study, 60 genes classified into 16 gene families were shorted that show the differential expression (up/down) in human exposure to fluoride; where 47 genes show the decreased expression and other 13 show the increased expression. The TFs SOX2, GATA1 and MYC for down-regulation gene and MYC, GATA1 for up-regulation of genes expression were predicted using the X2K approach. The potential protein kinase MAPK1, MAPK3, CSNK2A1 and CSNK2A2 for down-regulation and MAPK1, MAPK3, MAPK8, IKBKB AKT1, GSK3B and CDK2 for up-regulation of the genes are identified which are connected to a maximum number of intermediate protein and TFs that can be applied to the prediction novel targeting the disease-suppressive potential target in human longtime fluoride exposure.
      PubDate: 2017-04-12
      DOI: 10.1007/s13721-017-0148-7
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