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  Subjects -> COMPUTER SCIENCE (Total: 2002 journals)
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COMPUTER SCIENCE (1160 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 13)
Abakós     Open Access   (Followers: 3)
Academy of Information and Management Sciences Journal     Full-text available via subscription   (Followers: 73)
ACM Computing Surveys     Hybrid Journal   (Followers: 22)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 11)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 4)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 13)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 4)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 1)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 20)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 11)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 22)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 26)
Advanced Science Letters     Full-text available via subscription   (Followers: 7)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15)
Advances in Computer Science : an International Journal     Open Access   (Followers: 13)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Sciences     Open Access   (Followers: 16)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 37)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 2)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 7)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 8)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 4)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 7)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 9)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 6)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 2)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 14)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 1)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 128)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 6)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access  
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 3)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 9)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Bioinformatics     Hybrid Journal   (Followers: 308)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 32)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 44)
British Journal of Educational Technology     Hybrid Journal   (Followers: 124)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 2)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal  
Cell Communication and Signaling     Open Access   (Followers: 1)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access  
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 12)
Circuits and Systems     Open Access   (Followers: 16)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Communication Methods and Measures     Hybrid Journal   (Followers: 11)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 53)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access  
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 14)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 4)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 13)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 31)
Computer     Full-text available via subscription   (Followers: 85)
Computer Aided Surgery     Hybrid Journal   (Followers: 3)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 7)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 22)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 10)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 1)
Computer Music Journal     Hybrid Journal   (Followers: 16)
Computer Physics Communications     Hybrid Journal   (Followers: 6)
Computer Science - Research and Development     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computer Science and Information Technology     Open Access   (Followers: 11)
Computer Science Education     Hybrid Journal   (Followers: 12)
Computer Science Journal     Open Access   (Followers: 20)
Computer Science Master Research     Open Access   (Followers: 10)
Computer Science Review     Hybrid Journal   (Followers: 10)

        1 2 3 4 5 6 | Last

Journal Cover Briefings in Bioinformatics
  [SJR: 4.086]   [H-I: 73]   [44 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1467-5463 - ISSN (Online) 1477-4054
   Published by Oxford University Press Homepage  [370 journals]
  • Notions of similarity for systems biology models
    • Authors: Henkel R; Hoehndorf R, Kacprowski T, et al.
      First page: 902
      Abstract: Briefings in Bioinformatics (2016). doi: 10.1093/bib/bbw090
      PubDate: 2017-01-17
      DOI: 10.1093/bib/bbw146
  • A review of connectivity map and computational approaches in
    • Authors: Musa A; Ghoraie L, Zhang S, et al.
      First page: 903
      Abstract: Briefings in Bioinformatics (2017) doi: 10.1093/bib/bbw112
      PubDate: 2017-02-23
      DOI: 10.1093/bib/bbx023
  • miRandb: a resource of online services for miRNA research
    • Authors: Aghaee-Bakhtiari S; Arefian E, Lau P.
      First page: 904
      Abstract: Briefings in Bioinformatics (2016) doi: 10.1093/bib/bbw109
      PubDate: 2017-03-01
      DOI: 10.1093/bib/bbx027
  • How the strengths of Lisp-family languages facilitate building complex and
           flexible bioinformatics applications
    • Authors: Khomtchouk BB; Weitz E, Karp PD, et al.
      First page: 905
      Abstract: Briefings in Bioinformatics (2016) doi: 10.1093/bib/bbw130
      PubDate: 2017-03-01
      DOI: 10.1093/bib/bbx016
  • Methodological implementation of mixed linear models in multi-locus
           genome-wide association studies
    • Authors: Wen Y; Zhang H, Ni Y, et al.
      First page: 906
      Abstract: Briefings in Bioinformatics (2016) doi: 10.1093/bib/bbw145
      PubDate: 2017-03-08
      DOI: 10.1093/bib/bbx028
  • OpenGeneMed: a portable, flexible and customizable informatics hub for the
           coordination of next-generation sequencing studies in support of precision
           medicine trials
    • Authors: Palmisano A; Zhao Y, Li M, et al.
      First page: 723
      Abstract: AbstractTrials involving genomic-driven treatment selection require the coordination of many teams interacting with a great variety of information. The need of better informatics support to manage this complex set of operations motivated the creation of OpenGeneMed. OpenGeneMed is a stand-alone and customizable version of GeneMed (Zhao et al. GeneMed: an informatics hub for the coordination of next-generation sequencing studies that support precision oncology clinical trials. Cancer Inform 2015;14(Suppl 2):45), a web-based interface developed for the National Cancer Institute Molecular Profiling-based Assignment of Cancer Therapy (NCI-MPACT) clinical trial coordinated by the NIH. OpenGeneMed streamlines clinical trial management and it can be used by clinicians, lab personnel, statisticians and researchers as a communication hub. It automates the annotation of genomic variants identified by sequencing tumor DNA, classifies the actionable mutations according to customizable rules and facilitates quality control in reviewing variants. The system generates summarized reports with detected genomic alterations that a treatment review team can use for treatment assignment. OpenGeneMed allows collaboration to happen seamlessly along the clinical pipeline; it helps reduce errors made transferring data between groups and facilitates clear documentation along the pipeline. OpenGeneMed is distributed as a stand-alone virtual machine, ready for deployment and use from a web browser; its code is customizable to address specific needs of different clinical trials and research teams. Examples on how to change the code are provided in the technical documentation distributed with the virtual machine. In summary, OpenGeneMed offers an initial set of features inspired by our experience with GeneMed, a system that has been proven to be efficient and successful for coordinating the application of next-generation sequencing in the NCI-MPACT trial.
      PubDate: 2016-07-14
      DOI: 10.1093/bib/bbw059
  • Comparison of methods to detect differentially expressed genes between
           single-cell populations
    • Authors: Jaakkola MK; Seyednasrollah F, Mehmood A, et al.
      First page: 735
      Abstract: AbstractWe compared five statistical methods to detect differentially expressed genes between two distinct single-cell populations. Currently, it remains unclear whether differential expression methods developed originally for conventional bulk RNA-seq data can also be applied to single-cell RNA-seq data analysis. Our results in three diverse comparison settings showed marked differences between the different methods in terms of the number of detections as well as their sensitivity and specificity. They, however, did not reveal systematic benefits of the currently available single-cell-specific methods. Instead, our previously introduced reproducibility-optimization method showed good performance in all comparison settings without any single-cell-specific modifications.
      PubDate: 2016-07-02
      DOI: 10.1093/bib/bbw057
  • Systematic bias of correlation coefficient may explain negative accuracy
           of genomic prediction
    • Authors: Zhou Y; Vales M, Wang A, et al.
      First page: 744
      Abstract: AbstractAccuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula.
      PubDate: 2016-07-18
      DOI: 10.1093/bib/bbw064
  • Evo-Devo-Epi R : a genome-wide search platform for epistatic control on
           the evolution of development
    • Authors: Jiang L; Zhang M, Sang M, et al.
      First page: 754
      Abstract: AbstractEvo-devo is a theory proposed to study how phenotypes evolve by comparing the developmental processes of different organisms or the same organism experiencing changing environments. It has been recognized that nonallelic interactions at different genes or quantitative trait loci, known as epistasis, may play a pivotal role in the evolution of development, but it has proven difficult to quantify and elucidate this role into a coherent picture. We implement a high-dimensional genome-wide association study model into the evo-devo paradigm and pack it into the R-based Evo-Devo-EpiR, aimed at facilitating the genome-wide landscaping of epistasis for the diversification of phenotypic development. By analyzing a high-throughput assay of DNA markers and their pairs simultaneously, Evo-Devo-EpiR is equipped with a capacity to systematically characterize various epistatic interactions that impact on the pattern and timing of development and its evolution. Enabling a global search for all possible genetic interactions for developmental processes throughout the whole genome, Evo-Devo-EpiR provides a computational tool to illustrate a precise genotype-phenotype map at interface between epistasis, development and evolution.
      PubDate: 2016-07-25
      DOI: 10.1093/bib/bbw062
  • Comparative pan-cancer DNA methylation analysis reveals cancer common and
           specific patterns
    • Authors: Yang X; Gao L, Zhang S.
      First page: 761
      Abstract: AbstractAbnormal DNA methylation is an important epigenetic regulator involving tumorigenesis. Deciphering cancer common and specific DNA methylation patterns is essential for us to understand the mechanisms of tumor development. The Cancer Genome Atlas (TCGA) project provides a large number of samples of different cancers that enable a pan-cancer study of DNA methylation possible. Here we investigate cancer common and specific DNA methylation patterns among 5480 DNA methylation profiles of 15 cancer types from TCGA. We first define differentially methylated CpG sites (DMCs) in each cancer and then identify 5450 hyper- and 4433 hypomethylated pan-cancer DMCs (PDMCs). Intriguingly, three adjacent hypermethylated PDMC constitute an enhancer region, which potentially regulates two tumor suppressor genes BVES and PRDM1 negatively. Moreover, we identify six distinct motif clusters, which are enriched in hyper- or hypomethylated PDMCs and are associated with several well-known cancer hallmarks. We also observe that PDMCs relate to distinct transcriptional groups. Additionally, 55 hypermethylated and 7 hypomethylated PDMCs are significantly associated with patient survival. Lastly, we find that cancer-specific DMCs are enriched in known cancer genes and cell-type-specific super-enhancers. In summary, this study provides a comprehensive investigation and reveals meaningful cancer common and specific DNA methylation patterns.
      PubDate: 2016-07-18
      DOI: 10.1093/bib/bbw063
  • BrowseVCF: a web-based application and workflow to quickly prioritize
           disease-causative variants in VCF files
    • Authors: Salatino S; Ramraj V.
      First page: 774
      Abstract: AbstractFollowing variant calling and annotation, accurate variant filtering is a crucial step to extract meaningful information from sequencing data and to investigate disease aetiology. However, the variant call format (VCF) used to store this information is not easy to handle for non-bioinformaticians. We present BrowseVCF, a flexible and intuitive software to enable researchers to browse and filter millions of variants in a few seconds. Key features include querying user-defined gene lists, grouping samples for family or tumour/normal studies and exporting results in spreadsheet format. BrowseVCF’s significant advantages over most existing tools include the ability to process data from any DNA sequencing experiment (exome, whole-genome and amplicons) and to correctly parse files annotated with Variant Effect Predictor. BrowseVCF can be used either locally on personal computers or as part of automated pipelines. Its user interface has been carefully designed to minimize tunable parameters. BrowseVCF is freely available from
      PubDate: 2016-07-02
      DOI: 10.1093/bib/bbw054
  • Screening and validation of lncRNAs and circRNAs as miRNA sponges
    • Authors: Militello G; Weirick T, John D, et al.
      First page: 780
      Abstract: AbstractIntensive research in past two decades has uncovered the presence and importance of noncoding RNAs (ncRNAs), which includes microRNAs (miRs) and long ncRNAs (lncRNAs). These two classes of ncRNAs interact to a certain extent, as some lncRNAs bind to miRs to sequester them. Such lncRNAs are collectively called ‘competing endogenous RNAs’ or ‘miRNA sponges’. In this study, we screened for lncRNAs that may act as miRNA sponges using the publicly available data sets and databases. To uncover the roles of miRNA sponges, loss-of-function experiments were conducted, which revealed the biological roles as miRNA sponges. LINC00324 is important for the cell survival by binding to miR-615-5p leading to the de-repression of its target BTG2. LOC400043 controls several biological functions via sequestering miR-28-3p and miR-96-5p, thereby changing the expressions of transcriptional regulators. Finally, we also screened for circular RNAs (circRNAs) that may function as miRNA sponges. The results were negative at least for the selected circRNAs in this study. In conclusion, miRNA sponges can be identified by applying a series of bioinformatics techniques and validated with biological experiments.
      PubDate: 2016-07-02
      DOI: 10.1093/bib/bbw053
  • Identification and function annotation of long intervening noncoding RNAs
    • Authors: Luo H; Bu D, Sun L, et al.
      First page: 789
      Abstract: AbstractRNA-seq technology offers the promise of rapid comprehensive discovery of long intervening noncoding RNAs (lincRNAs). Basic tools such as Tophat and Cufflinks have been widely used for RNA-seq assembly. However, advanced bioinformatics methodologies that allow in-depth analysis of lincRNAs are lacking. Here, we describe a computational protocol that is especially designed for the identification of novel lincRNAs and the prediction of the function. The protocol mainly includes two open-access tools, CNCI and ncFANs. CNCI allows users to distinguish noncoding from protein-coding transcripts and to retrieve novel lincRNAs. ncFANs integrates expression profiles of protein-coding and lincRNA genes to construct coexpression networks. Such networks are subsequently used to perform function predictions of unknown lincRNAs. This protocol will allow users to apply these procedures without the need of additional training. All the tools in current protocol are available
      PubDate: 2016-07-20
      DOI: 10.1093/bib/bbw046
  • Protein–protein interactions: detection, reliability assessment and
    • Authors: Peng X; Wang J, Peng W, et al.
      First page: 798
      Abstract: AbstractProtein–protein interactions (PPIs) participate in all important biological processes in living organisms, such as catalyzing metabolic reactions, DNA replication, DNA transcription, responding to stimuli and transporting molecules from one location to another. To reveal the function mechanisms in cells, it is important to identify PPIs that take place in the living organism. A large number of PPIs have been discovered by high-throughput experiments and computational methods. However, false-positive PPIs have been introduced too. Therefore, to obtain reliable PPIs, many computational methods have been proposed. Generally, these methods can be classified into two categories. One category includes the methods that are designed to determine new reliable PPIs. The other one is designed to assess the reliability of existing PPIs and filter out the unreliable ones. In this article, we review the two kinds of methods for detecting reliable PPIs, and then focus on evaluating the performance of some of these typical methods. Later on, we also enumerate several PPI network-based applications with taking a reliability assessment of the PPI data into consideration. Finally, we will discuss the challenges for obtaining reliable PPIs and future directions of the construction of reliable PPI networks. Our research will provide readers some guidance for choosing appropriate methods and features for obtaining reliable PPIs.
      PubDate: 2016-07-21
      DOI: 10.1093/bib/bbw066
  • Computational models for predicting drug responses in cancer research
    • Authors: Azuaje F.
      First page: 820
      Abstract: AbstractThe computational prediction of drug responses based on the analysis of multiple types of genome-wide molecular data is vital for accomplishing the promise of precision medicine in oncology. This will benefit cancer patients by matching their tumor characteristics to the most effective therapy available. As larger and more diverse layers of patient-related data become available, further demands for new bioinformatics approaches and expertise will arise. This article reviews key strategies, resources and techniques for the prediction of drug sensitivity in cell lines and patient-derived samples. It discusses major advances and challenges associated with the different model development steps. This review highlights major trends in this area, and will assist researchers in the assessment of recent progress and in the selection of approaches to emerging applications in oncology.
      PubDate: 2016-07-21
      DOI: 10.1093/bib/bbw065
  • TBC2health: a database of experimentally validated health-beneficial
           effects of tea bioactive compounds
    • Authors: Zhang S; Xuan H, Zhang L, et al.
      First page: 830
      Abstract: AbstractTea is one of the most consumed beverages in the world. Considerable studies show the exceptional health benefits (e.g. antioxidation, cancer prevention) of tea owing to its various bioactive components. However, data from these extensively published papers had not been made available in a central database. To lay a foundation in improving the understanding of healthy tea functions, we established a TBC2health database that currently documents 1338 relationships between 497 tea bioactive compounds and 206 diseases (or phenotypes) manually culled from over 300 published articles. Each entry in TBC2health contains comprehensive information about a bioactive relationship that can be accessed in three aspects: (i) compound information, (ii) disease (or phenotype) information and (iii) evidence and reference. Using the curated bioactive relationships, a bipartite network was reconstructed and the corresponding network (or sub-network) visualization and topological analyses are provided for users. This database has a user-friendly interface for entry browse, search and download. In addition, TBC2health provides a submission page and several useful tools (e.g. BLAST, molecular docking) to facilitate use of the database. Consequently, TBC2health can serve as a valuable bioinformatics platform for the exploration of beneficial effects of tea on human health. TBC2health is freely available at
      PubDate: 2016-07-05
      DOI: 10.1093/bib/bbw055
  • Comparative assessment of differential network analysis methods
    • Authors: Lichtblau Y; Zimmermann K, Haldemann B, et al.
      First page: 837
      Abstract: AbstractDifferential network analysis (DiNA) denotes a recent class of network-based Bioinformatics algorithms which focus on the differences in network topologies between two states of a cell, such as healthy and disease, to identify key players in the discriminating biological processes. In contrast to conventional differential analysis, DiNA identifies changes in the interplay between molecules, rather than changes in single molecules. This ability is especially important in cases where effectors are changed, e.g. mutated, but their expression is not. A number of different DiNA approaches have been proposed, yet a comparative assessment of their performance in different settings is still lacking. In this paper, we evaluate 10 different DiNA algorithms regarding their ability to recover genetic key players from transcriptome data. We construct high-quality regulatory networks and enrich them with co-expression data from four different types of cancer. Next, we assess the results of applying DiNA algorithms on these data sets using a gold standard list (GSL). We find that local DiNA algorithms are generally superior to global algorithms, and that all DiNA algorithms outperform conventional differential expression analysis. We also assess the ability of DiNA methods to exploit additional knowledge in the underlying cellular networks. To this end, we enrich the cancer-type specific networks with known regulatory miRNAs and compare the algorithms performance in networks with and without miRNA. We find that including miRNAs consistently and considerably improves the performance of almost all tested algorithms. Our results underline the advantages of comprehensive cell models for the analysis of -omics data.
      PubDate: 2016-07-25
      DOI: 10.1093/bib/bbw061
  • Deep learning in bioinformatics
    • Authors: Min S; Lee B, Yoon S.
      First page: 851
      Abstract: AbstractIn the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies.
      PubDate: 2016-07-25
      DOI: 10.1093/bib/bbw068
  • Graphics processing units in bioinformatics, computational biology and
           systems biology
    • Authors: Nobile MS; Cazzaniga P, Tangherloni A, et al.
      First page: 870
      Abstract: AbstractSeveral studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at
      PubDate: 2016-07-07
      DOI: 10.1093/bib/bbw058
  • Gene Ontology semantic similarity tools: survey on features and challenges
           for biological knowledge discovery
    • Authors: Mazandu GK; Chimusa ER, Mulder NJ.
      First page: 886
      Abstract: AbstractGene Ontology (GO) semantic similarity tools enable retrieval of semantic similarity scores, which incorporate biological knowledge embedded in the GO structure for comparing or classifying different proteins or list of proteins based on their GO annotations. This facilitates a better understanding of biological phenomena underlying the corresponding experiment and enables the identification of processes pertinent to different biological conditions. Currently, about 14 tools are available, which may play an important role in improving protein analyses at the functional level using different GO semantic similarity measures. Here we survey these tools to provide a comprehensive view of the challenges and advances made in this area to avoid redundant effort in developing features that already exist, or implementing ideas already proven to be obsolete in the context of GO. This helps researchers, tool developers, as well as end users, understand the underlying semantic similarity measures implemented through knowledge of pertinent features of, and issues related to, a particular tool. This should empower users to make appropriate choices for their biological applications and ensure effective knowledge discovery based on GO annotations.
      PubDate: 2016-07-26
      DOI: 10.1093/bib/bbw067
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