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  Subjects -> BIOLOGY (Total: 3190 journals)
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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
Computational and Structural Biotechnology Journal
Journal Prestige (SJR): 1.517
Citation Impact (citeScore): 4
Number of Followers: 2  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2001-0370 - ISSN (Online) 2001-0370
Published by Elsevier Homepage  [3155 journals]
  • In silico prediction of large-scale microbial production performance:
           Constraints for getting proper data-driven models

    • Abstract: Publication date: Available online 6 July 2018Source: Computational and Structural Biotechnology JournalAuthor(s): Julia Zieringer, Ralf Takors Industrial bioreactors range from 10.000 to 700.000 L and characteristically show different zones of substrate availabilities, dissolved gas concentrations and pH values reflecting physical, technical and economic constraints of scale-up. Microbial producers are fluctuating inside the bioreactors thereby experiencing frequently changing micro-environmental conditions. The external stimuli induce responses on microbial metabolism and on transcriptional regulation programs. Both may deteriorate the expected microbial production performance in large scale compared to expectations deduced from ideal, well-mixed lab-scale conditions. Accordingly, predictive tools are needed to quantify large-scale impacts considering bioreactor heterogeneities. The review shows that the time is right to combine simulations of microbial kinetics with calculations of large-scale environmental conditions to predict the bioreactor performance. Accordingly, basic experimental procedures and computational tools are presented to derive proper microbial models and hydrodynamic conditions, and to link both for bioreactor modeling. Particular emphasis is laid on the identification of gene regulatory networks as the implementation of such models will surely gain momentum in future studies.
       
  • Blockchain Technology for Healthcare: Facilitating the Transition to
           Patient-Driven Interoperability

    • Abstract: Publication date: Available online 30 June 2018Source: Computational and Structural Biotechnology JournalAuthor(s): William J. Gordon, Christian Catalini Interoperability in healthcare has traditionally been focused around data exchange between business entities, for example, different hospital systems. However, there has been a recent push towards patient-driven interoperability, in which health data exchange is patient-mediated and patient-driven. Patient-centered interoperability, however, brings with it new challenges and requirements around security and privacy, technology, incentives, and governance that must be addressed for this type of data sharing to succeed at scale. In this paper, we look at how blockchain technology might facilitate this transition through five mechanisms: (1) digital access rules, (2) data aggregation, (3) data liquidity, (4) patient identity, and (5) data immutability. We then look at barriers to blockchain-enabled patient-driven interoperability, specifically clinical data transaction volume, privacy and security, patient engagement, and incentives. We conclude by noting that while patient-driving interoperability is an exciting trend in healthcare, given these challenges, it remains to be seen whether blockchain can facilitate the transition from institution-centric to patient-centric data sharing.
       
  • Following Ribosome Footprints to Understand Translation at a Genome Wide
           Level

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Guillermo Eastman, Pablo Smircich, José R. Sotelo-Silveira Protein translation is a key step in gene expression. The development of Ribosome Profiling has allowed the global analysis of this process at sub-codon resolution. In the last years the method has been applied to several models ranging from bacteria to mammalian cells yielding a surprising amount of insight on the mechanism and the regulation of translation. In this review we describe the key aspects of the experimental protocol and comment on the main conclusions raised in different models.
       
  • Highlighting Clinical Metagenomics for Enhanced Diagnostic
           Decision-making: A Step Towards Wider Implementation

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Jessica D. Forbes, Natalie C. Knox, Christy-Lynn Peterson, Aleisha R. Reimer Clinical metagenomics (CMg) is the discipline that refers to the sequencing of all nucleic acid material present within a clinical specimen with the intent to recover clinically relevant microbial information. From a diagnostic perspective, next-generation sequencing (NGS) offers the ability to rapidly identify putative pathogens and predict their antimicrobial resistance profiles to optimize targeted treatment regimens. Since the introduction of metagenomics nearly a decade ago, numerous reports have described successful applications in an increasing variety of biological specimens, such as respiratory secretions, cerebrospinal fluid, stool, blood and tissue. Considerable advancements in sequencing and computational technologies in recent years have made CMg a promising tool in clinical microbiology laboratories. Moreover, costs per sample and turnaround time from specimen receipt to clinical management continue to decrease, making the prospect of CMg more feasible. Many difficulties, however, are associated with CMg and warrant further improvements such as the informatics infrastructure and analytical pipelines. Thus, the current review focuses on comprehensively assessing applications of CMg for diagnostic and subtyping purposes.
       
  • A Review of Matched-pairs Feature Selection Methods for Gene Expression
           Data Analysis

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Sen Liang, Anjun Ma, Sen Yang, Yan Wang, Qin Ma With the rapid accumulation of gene expression data from various technologies, e.g., microarray, RNA-sequencing (RNA-seq), and single-cell RNA-seq, it is necessary to carry out dimensional reduction and feature (signature genes) selection in support of making sense out of such high dimensional data. These computational methods significantly facilitate further data analysis and interpretation, such as gene function enrichment analysis, cancer biomarker detection, and drug targeting identification in precision medicine. Although numerous methods have been developed for feature selection in bioinformatics, it is still a challenge to choose the appropriate methods for a specific problem and seek for the most reasonable ranking features. Meanwhile, the paired gene expression data under matched case-control design (MCCD) is becoming increasingly popular, which has often been used in multi-omics integration studies and may increase feature selection efficiency by offsetting similar distributions of confounding features. The appropriate feature selection methods specifically designed for the paired data, which is named as matched-pairs feature selection (MPFS), however, have not been maturely developed in parallel. In this review, we compare the performance of 10 feature-selection methods (eight MPFS methods and two traditional unpaired methods) on two real datasets by applied three classification methods, and analyze the algorithm complexity of these methods through the running of their programs. This review aims to induce and comprehensively present the MPFS in such a way that readers can easily understand its characteristics and get a clue in selecting the appropriate methods for their analyses.
       
  • Interplay Between Virulence and Variability Factors as a Potential Driver
           of Invasive Meningococcal Disease

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Emilio Siena, Margherita Bodini, Duccio Medini
       
  • A review of somatic single nucleotide variant calling algorithms for
           next-generation sequencing data

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Chang Xu Detection of somatic mutations holds great potential in cancer treatment and has been a very active research field in the past few years, especially since the breakthrough of the next-generation sequencing technology. A collection of variant calling pipelines have been developed with different underlying models, filters, input data requirements, and targeted applications. This review aims to enumerate these unique features of the state-of-the-art variant callers, in the hope to provide a practical guide for selecting the appropriate pipeline for specific applications. We will focus on the detection of somatic single nucleotide variants, ranging from traditional variant callers based on whole genome or exome sequencing of paired tumor-normal samples to recent low-frequency variant callers designed for targeted sequencing protocols with unique molecular identifiers. The variant callers have been extensively benchmarked with inconsistent performances across these studies. We will review the reference materials, datasets, and performance metrics that have been used in the benchmarking studies. In the end, we will discuss emerging trends and future directions of the variant calling algorithms.
       
  • Taxonomy and evolution of Aspergillus, Penicillium and Talaromyces in the
           omics era – Past, present and future

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Chi-Ching Tsang, James Y.M. Tang, Susanna K.P. Lau, Patrick C.Y. Woo Aspergillus, Penicillium and Talaromyces are diverse, phenotypically polythetic genera encompassing species important to the environment, economy, biotechnology and medicine, causing significant social impacts. Taxonomic studies on these fungi are essential since they could provide invaluable information on their evolutionary relationships and define criteria for species recognition. With the advancement of various biological, biochemical and computational technologies, different approaches have been adopted for the taxonomy of Aspergillus, Penicillium and Talaromyces; for example, from traditional morphotyping, phenotyping to chemotyping (e.g. lipotyping, proteotypingand metabolotyping) and then mitogenotyping and/or phylotyping. Since different taxonomic approaches focus on different sets of characters of the organisms, various classification and identification schemes would result. In view of this, the consolidated species concept, which takes into account different types of characters, is recently accepted for taxonomic purposes and, together with the lately implemented ‘One Fungus – One Name’ policy, is expected to bring a more stable taxonomy for Aspergillus, Penicillium and Talaromyces, which could facilitate their evolutionary studies. The most significant taxonomic change for the three genera was the transfer of Penicillium subgenus Biverticillium to Talaromyces (e.g. the medically important thermally dimorphic ‘P. marneffei’ endemic in Southeast Asia is now named T. marneffei), leaving both Penicillium and Talaromyces as monophyletic genera. Several distantly related Aspergillus-like fungi were also segregated from Aspergillus, making this genus, containing members of both sexual and asexual morphs, monophyletic as well. In the current omics era, application of various state-of-the-art omics technologies is likely to provide comprehensive information on the evolution of Aspergillus, Penicillium and Talaromyces and a stable taxonomy will hopefully be achieved.
       
  • Current Perspectives of the Chicken Gastrointestinal Tract and Its
           Microbiome

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Daniel Borda-Molina, Jana Seifert, Amélia Camarinha-Silva The microbial communities inhabiting the gastrointestinal tract (GIT) of chickens are essential for the gut homeostasis, the host metabolism and affect the animals' physiology and health. They play an important role in nutrient digestion, pathogen inhibition and interact with the gut-associated immune system.Throughout the last years high-throughput sequencing technologies have been used to analyze the bacterial communities that colonize the different sections of chickens' gut. The most common methodologies are targeted amplicon sequencing followed by metagenome shotgun sequencing as well as metaproteomics aiming at a broad range of topics such as dietary effects, animal diseases, bird performance and host genetics. However, the respective analyses are still at the beginning and currently there is a lack of information in regard to the activity and functional characterization of the gut microbial communities. In the future, the use of multi-omics approaches may enhance research related to chicken production, animal and also public health. Furthermore, combinations with other disciplines such as genomics, immunology and physiology may have the potential to elucidate the definition of a “healthy” gut microbiota.
       
  • An Artificial Neural Network Integrated Pipeline for Biomarker Discovery
           Using Alzheimer's Disease as a Case Study

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Dimitrios Zafeiris, Sergio Rutella, Graham Roy Ball The field of machine learning has allowed researchers to generate and analyse vast amounts of data using a wide variety of methodologies. Artificial Neural Networks (ANN) are some of the most commonly used statistical models and have been successful in biomarker discovery studies in multiple disease types. This review seeks to explore and evaluate an integrated ANN pipeline for biomarker discovery and validation in Alzheimer's disease, the most common form of dementia worldwide with no proven cause and no available cure. The proposed pipeline consists of analysing public data with a categorical and continuous stepwise algorithm and further examination through network inference to predict gene interactions. This methodology can reliably generate novel markers and further examine known ones and can be used to guide future research in Alzheimer's disease.
       
  • Discovery of Novel Functional Centers With Rationally Designed Amino Acid
           Motifs

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Aloysius Wong, Xuechen Tian, Chris Gehring, Claudius Marondedze Plants are constantly exposed to environmental stresses and in part due to their sessile nature, they have evolved signal perception and adaptive strategies that are distinct from those of other eukaryotes. This is reflected at the cellular level where receptors and signalling molecules cannot be identified using standard homology-based searches querying with proteins from prokaryotes and other eukaryotes. One of the reasons for this is the complex domain architecture of receptor molecules. In order to discover hidden plant signalling molecules, we have developed a motif-based approach designed specifically for the identification of functional centers in plant molecules. This has made possible the discovery of novel components involved in signalling and stimulus-response pathways; the molecules include cyclic nucleotide cyclases, a nitric oxide sensor and a novel target for the hormone abscisic acid. Here, we describe the major steps of the method and illustrate it with recent and experimentally confirmed molecules as examples. We foresee that carefully curated search motifs supported by structural and bioinformatic assessments will uncover many more structural and functional aspects, particularly of signalling molecules.
       
  • Computational Methods for Assessing Chromatin Hierarchy

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Pearl Chang, Moloya Gohain, Ming-Ren Yen, Pao-Yang Chen The hierarchical organization of chromatin is known to associate with diverse cellular functions; however, the precise mechanisms and the 3D structure remain to be determined. With recent advances in high-throughput next generation sequencing (NGS) techniques, genome-wide profiling of chromatin structures is made possible. Here, we provide a comprehensive overview of NGS-based methods for profiling “higher-order” and “primary-order” chromatin structures from both experimental and computational aspects. Experimental requirements and considerations specific for each method were highlighted. For computational analysis, we summarized a common analysis strategy for both levels of chromatin assessment, focusing on the characteristic computing steps and the tools. The recently developed single-cell level techniques based on Hi-C and ATAC-seq present great potential to reveal cell-to-cell variability in chromosome architecture. A brief discussion on these methods in terms of experimental and data analysis features is included. We also touch upon the biological relevance of chromatin organization and how the combination with other techniques uncovers the underlying mechanisms. We conclude with a summary and our prospects on necessary improvements of currently available methods in order to advance understanding of chromatin hierarchy. Our review brings together the analyses of both higher- and primary-order chromatin structures, and serves as a roadmap when choosing appropriate experimental and computational methods for assessing chromatin hierarchy.
       
  • Machine Learning Methods for Histopathological Image Analysis

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Daisuke Komura, Shumpei Ishikawa Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems specific to such analysis, and propose possible solutions.
       
  • FoldX as Protein Engineering Tool: Better Than Random Based
           Approaches'

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Oliver Buß, Jens Rudat, Katrin Ochsenreither Improving protein stability is an important goal for basic research as well as for clinical and industrial applications but no commonly accepted and widely used strategy for efficient engineering is known. Beside random approaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico approaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algorithm FoldX is more accurate than random based approaches is addressed.Graphical Unlabelled Image
       
  • DNA Methylation in Stroke. Update of Latest Advances

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Jerzy Krupinski, Caty Carrera, Elena Muiño, Nuria Torres, Raid Al-Baradie, Natalia Cullell, Israel Fernandez-Cadenas Epigenetic modifications are hereditable and modifiable factors that do not alter the DNA sequence. These epigenetic factors include DNA methylation, acetylation of histones and non-coding RNAs. Epigenetic factors have mainly been associated with cancer but also with other diseases and conditions such as diabetes or obesity. In addition, epigenetic modifications could play an important role in cardiovascular diseases, including stroke. We review the latest advances in stroke epigenetics, focusing on DNA methylation studies and the future perspectives in this field.
       
  • Corrigendum to “A Gene Module-Based eQTL Analysis Prioritizing Disease
           Genes and Pathways in Kidney Cancer”

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): M.Q. Yang, D. Li, W. Yang, Y. Zhang, J. Liu, W. Tong
       
  • Protein Sequences Recapitulate Genetic Code Evolution

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Hervé Seligmann Several hypotheses predict ranks of amino acid assignments to genetic code's codons. Analyses here show that average positions of amino acid species in proteins correspond to assignment ranks, in particular as predicted by Juke's neutral mutation hypothesis for codon assignments. In all tested protein groups, including co- and post-translationally folding proteins, ‘recent’ amino acids are on average closer to gene 5′ extremities than ‘ancient’ ones. Analyses of pairwise residue contact energies matrices suggest that early amino acids stereochemically selected late ones that stablilize residue interactions within protein cores, presumably producing 5′-late-to-3′-early amino acid protein sequence gradients. The gradient might reduce protein misfolding, also after mutations, extending principles of neutral mutations to protein folding. Presumably, in self-perpetuating and self-correcting systems like the genetic code, initial conditions produce similarities between evolution of the process (the genetic code) and ‘ontogeny’ of resulting structures (here proteins), producing apparent teleonomy between process and product.
       
  • Functional Prediction of Hypothetical Transcription Factors of Escherichia
           coli K-12 Based on Expression Data

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Emanuel Flores-Bautista, Carenne Ludeña Cronick, Anny Rodriguez Fersaca, Mario Alberto Martinez-Nuñez, Ernesto Perez-Rueda The repertoire of 304 DNA-binding transcription factors (TFs) in Escherichia coli K-12 has been described recently, with 196 TFs experimentally characterized and 108 proteins predicted by sequence comparisons. Based on 303 expression profile patterns retrieved from the Colombos database 12 clusters were identified, including hypothetical and experimentally characterized TFs, using a spectral clustering algorithm based on a 3NN graph built using 14 principal components that represent 65% of the variance of the expression data. In a posterior step, clusters were characterized in terms of their associated overrepresented functions, based on KEGG, Supfam annotations and Pfam assignments among other functional categories using an enrichment test, reinforcing the notion that the identified clusters are functionally similar among them. Based on these data, the we identified 12 clusters in which hypothetical and known TFs share similar regulatory and physiological functions, such as module associations of toxin-antitoxin (TA) systems with DNA repair mechanisms, amino acid biosynthesis, and carbon metabolism/transport, among others. This analysis has increased our knowledge about gene regulation in E. coli K-12 and can be further expanded to other organisms.
       
  • Ordering Protein Contact Matrices

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Chuan Xu, Guillaume Bouvier, Benjamin Bardiaux, Michael Nilges, Thérèse Malliavin, Abdel Lisser Numerous biophysical approaches provide information about residues spatial proximity in proteins. However, correct assignment of the protein fold from this proximity information is not straightforward if the spatially close protein residues are not assigned to residues in the primary sequence. Here, we propose an algorithm to assign such residue numbers by ordering the columns and lines of the raw protein contact matrix directly obtained from proximity information between unassigned amino acids. The ordering problem is formatted as the search of a trail within a graph connecting protein residues through the nonzero contact values. The algorithm performs in two steps: (i) finding the longest trail of the graph using an original dynamic programming algorithm, (ii) clustering the individual ordered matrices using a self-organizing map (SOM) approach. The combination of the dynamic programming and self-organizing map approaches constitutes a quite innovative point of the present work. The algorithm was validated on a set of about 900 proteins, representative of the sizes and proportions of secondary structures observed in the Protein Data Bank. The algorithm was revealed to be efficient for noise levels up to 40%, obtaining average gaps of about 20% at maximum between ordered and initial matrices. The proposed approach paves the ways toward a method of fold prediction from noisy proximity information, as TM scores larger than 0.5 have been obtained for ten randomly chosen proteins, in the case of a noise level of 10%. The methods has been also validated on two experimental cases, on which it performed satisfactorily.
       
  • Prediction of dyslipidemia using gene mutations, family history of
           diseases and anthropometric indicators in children and adolescents: The
           CASPIAN-III study

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Hamid R. Marateb, Mohammad Reza Mohebian, Shaghayegh Haghjooy Javanmard, Amir Ali Tavallaei, Mohammad Hasan Tajadini, Motahar Heidari-Beni, Miguel Angel Mañanas, Mohammad Esmaeil Motlagh, Ramin Heshmat, Marjan Mansourian, Roya Kelishadi Dyslipidemia, the disorder of lipoprotein metabolism resulting in high lipid profile, is an important modifiable risk factor for coronary heart diseases. It is associated with more than four million worldwide deaths per year. Half of the children with dyslipidemia have hyperlipidemia during adulthood, and its prediction and screening are thus critical. We designed a new dyslipidemia diagnosis system. The sample size of 725 subjects (age 14.66 ± 2.61 years; 48% male; dyslipidemia prevalence of 42%) was selected by multistage random cluster sampling in Iran. Single nucleotide polymorphisms (rs1801177, rs708272, rs320, rs328, rs2066718, rs2230808, rs5880, rs5128, rs2893157, rs662799, and Apolipoprotein-E2/E3/E4), and anthropometric, life-style attributes, and family history of diseases were analyzed. A framework for classifying mixed-type data in imbalanced datasets was proposed. It included internal feature mapping and selection, re-sampling, optimized group method of data handling using convex and stochastic optimizations, a new cost function for imbalanced data and an internal validation. Its performance was assessed using hold-out and 4-foldcross-validation. Four other classifiers namely as supported vector machines, decision tree, and multilayer perceptron neural network and multiple logistic regression were also used. The average sensitivity, specificity, precision and accuracy of the proposed system were 93%, 94%, 94% and 92%, respectively in cross validation. It significantly outperformed the other classifiers and also showed excellent agreement and high correlation with the gold standard. A non-invasive economical version of the algorithm was also implemented suitable for low- and middle-income countries. It is thus a promising new tool for the prediction of dyslipidemia.
       
  • Amplification and bioinformatics analysis of conserved FAD-binding region
           of L-amino acid oxidase (LAAO) genes in gastropods compared to other
           organisms

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Wipawadee Suwannapan, Pramote Chumnanpuen, Teerasak E-kobon This study aimed to investigate the conserved FAD-binding region of the L-amino acid oxidase (LAAO) genes in twelve gastropod genera commonly found in Thailand compared to those in other organisms using molecular cloning, nucleotide sequencing and bioinformatics analysis. Genomic DNA of gastropods and other invertebrates was extracted and screened using primers specific to the conserved FAD-binding region of LAAO. The amplified 143-bp fragments were cloned and sequenced. The obtained nucleotide sequences of 21 samples were aligned and phylogenetically compared to the LAAO-conserved FAD-binding regions of 210 other organisms from the NCBI database. Translated amino acid sequences of these samples were used in phylogenetics and pattern analyses. The phylogenetic trees showed clear separation of the conserved regions in fungi, invertebrates, and vertebrates. Alignment of the conserved 47-amino-acid FAD-binding region of the LAAOs showed 150 unique sequences among the 231 samples and these patterns were different from those of other flavoproteins in the amine oxidase family. An amino acid pattern analysis of five sub-regions (bFAD, FAD, FAD-GG, GG, and aGG) within the FAD-binding sequence showed high variation at the FAD-GG sub-region. Pattern analysis of secondary structures indicated the aGG sub-region as having the highest structural variation. Cluster analysis of these patterns revealed two major clusters representing the mollusc clade and the vertebrate clade. Thus, molecular phylogenetics and pattern analyses of sequence and structural variations could reflect evolutionary relatedness and possible structural conservation to maintain specific function within the FAD-binding region of the LAAOs in gastropods compared to other organisms.
       
  • Differential Microbial Communities of Omnivorous and Herbivorous Cattle in
           Southern China

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Susanna K.P. Lau, Jade L.L. Teng, Tsz Ho Chiu, Elaine Chan, Alan K.L. Tsang, Gianni Panagiotou, Shao-Lun Zhai, Patrick C.Y. Woo In Hong Kong, cattle were traditionally raised by farmers as draft animals to plough rice fields. Due to urbanization in the 20th century, they were gradually abandoned and became wild cattle straying in suburban Hong Kong. Recently, these cattle were observed to have become omnivorous by eating leftover barbeque food waste in country parks. Microbiome analysis was performed on fecal samples of the omnivorous cattle using deep sequencing and the resulting microbiome was compared with that of traditional herbivorous cattle in Southern China. A more diverse gut microbiome was observed in the omnivorous cattle, suggesting that microbiota diversity increases as diet variation increases. At the genus level, the relative abundance of Anaeroplasma, Anaerovorax, Bacillus, Coprobacillus and Solibacillus significantly increased and those of Anaerofustis, Butyricimonas, Campylobacter, Coprococcus, Dehalobacterium, Phascolarctobacterium, rc4.4, RFN20, Succinivibrio and Turicibacter significantly decreased in the omnivorous group. The increase in microbial community levels of Bacillus and Anaerovorax likely attributes to the inclusion of meat in the diet; while the decrease in relative abundance of Coprococcus, Butyricimonas, Succinivibrio, Campylobacter and Phascolarctobacterium may reflect the reduction in grass intake. Furthermore, an increased consumption of resistant starch likely resulted in the increase in abundance of Anaeroplasma. In conclusion, a significant change in the gut microbial community was observed in the omnivorous cattle, suggesting that diet may be one of the factors that may signal an adaptation response by the cattle to maintain feed efficiency as a consequence of the change in environment.
       
  • Bioinformatic Analysis Reveals Conservation of Intrinsic Disorder in the
           Linker Sequences of Prokaryotic Dual-family Immunophilin Chaperones

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Sailen Barik The two classical immunophilin families, found essentially in all living cells, are: cyclophilin (CYN) and FK506-binding protein (FKBP). We previously reported a novel class of immunophilins that are natural chimera of these two, which we named dual-family immunophilin (DFI). The DFIs were found in either of two conformations: CYN-linker-FKBP (CFBP) or FKBP-3TPR-CYN (FCBP). While the 3TPR domain can serve as a flexible linker between the FKBP and CYN modules in the FCBP-type DFI, the linker sequences in the CFBP-type DFIs are relatively short, diverse in sequence, and contain no discernible motif or signature. Here, I present several lines of computational evidence that, regardless of their primary structure, these CFBP linkers are intrinsically disordered. This report provides the first molecular foundation for the model that the CFBP linker acts as an unstructured, flexible loop, allowing the two flanking chaperone modules function independently while linked in cis, likely to assist in the folding of multisubunit client complexes.Graphical Image 1
       
  • Lung Cancer Therapy Targeting Histone Methylation: Opportunities and
           Challenges

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Yuchen Chen, Xinran Liu, Yangkai Li, Chuntao Quan, Ling Zheng, Kun Huang Lung cancer is one of the most common malignancies. In spite of the progress made in past decades, further studies to improve current therapy for lung cancer are required. Dynamically controlled by methyltransferases and demethylases, methylation of lysine and arginine residues on histone proteins regulates chromatin organization and thereby gene transcription. Aberrant alterations of histone methylation have been demonstrated to be associated with the progress of multiple cancers including lung cancer. Inhibitors of methyltransferases and demethylases have exhibited anti-tumor activities in lung cancer, and multiple lead candidates are under clinical trials. Here, we summarize how histone methylation functions in lung cancer, highlighting most recent progresses in small molecular inhibitors for lung cancer treatment.
       
  • ctDNA and CTCs in Liquid Biopsy – Current Status and Where We Need
           to Progress

    • Abstract: Publication date: 2018Source: Computational and Structural Biotechnology Journal, Volume 16Author(s): Martin H.D. Neumann, Sebastian Bender, Thomas Krahn, Thomas Schlange We discuss the current status of liquid biopsy and its advantages and challenges with a focus on pre-analytical sample handling, technologies and workflows. The potential of circulating tumor cells and circulating tumor DNA is pointed out and an overview of corresponding technologies is given.
       
 
 
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