1,351 results match your criteria Briefings in bioinformatics[Journal]


Ensuring privacy and security of genomic data and functionalities.

Brief Bioinform 2019 Feb 12. Epub 2019 Feb 12.

Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia.

In recent times, the reduced cost of DNA sequencing has resulted in a plethora of genomic data that is being used to advance biomedical research and improve clinical procedures and healthcare delivery. These advances are revolutionizing areas in genome-wide association studies (GWASs), diagnostic testing, personalized medicine and drug discovery. This, however, comes with security and privacy challenges as the human genome is sensitive in nature and uniquely identifies an individual. Read More

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http://dx.doi.org/10.1093/bib/bbz013DOI Listing
February 2019

In silico drug repositioning based on drug-miRNA associations.

Brief Bioinform 2019 Feb 11. Epub 2019 Feb 11.

Department of Biomedical Engineering, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China.

Drug repositioning has become a prevailing tactic as this strategy is efficient, economical and low risk for drug discovery. Meanwhile, recent studies have confirmed that small-molecule drugs can modulate the expression of disease-related miRNAs, which indicates that miRNAs are promising therapeutic targets for complex diseases. In this study, we put forward and verified the hypothesis that drugs with similar miRNA profiles may share similar therapeutic properties. Read More

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http://dx.doi.org/10.1093/bib/bbz012DOI Listing
February 2019

Computational methods for identifying the critical nodes in biological networks.

Brief Bioinform 2019 Feb 12. Epub 2019 Feb 12.

Department of Computer Science, Xiamen University, China.

A biological network is complex. A group of critical nodes determines the quality and state of such a network. Increasing studies have shown that diseases and biological networks are closely and mutually related and that certain diseases are often caused by errors occurring in certain nodes in biological networks. Read More

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http://dx.doi.org/10.1093/bib/bbz011DOI Listing
February 2019
6 Reads

A comparison of deterministic and stochastic approaches for sensitivity analysis in computational systems biology.

Brief Bioinform 2019 Feb 7. Epub 2019 Feb 7.

The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, Rovereto (TN), Italy.

With the recent rising application of mathematical models in the field of computational systems biology, the interest in sensitivity analysis methods had increased. The stochastic approach, based on chemical master equations, and the deterministic approach, based on ordinary differential equations (ODEs), are the two main approaches for analyzing mathematical models of biochemical systems. In this work, the performance of these approaches to compute sensitivity coefficients is explored in situations where stochastic and deterministic simulation can potentially provide different results (systems with unstable steady states, oscillators with population extinction and bistable systems). Read More

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http://dx.doi.org/10.1093/bib/bbz014DOI Listing
February 2019

Performance of gene expression-based single sample predictors for assessment of clinicopathological subgroups and molecular subtypes in cancers: a case comparison study in non-small cell lung cancer.

Brief Bioinform 2019 Feb 4. Epub 2019 Feb 4.

Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Medicon Village, Lund, Sweden.

The development of multigene classifiers for cancer prognosis, treatment prediction, molecular subtypes or clinicopathological groups has been a cornerstone in transcriptomic analyses of human malignancies for nearly two decades. However, many reported classifiers are critically limited by different preprocessing needs like normalization and data centering. In response, a new breed of classifiers, single sample predictors (SSPs), has emerged. Read More

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http://dx.doi.org/10.1093/bib/bbz008DOI Listing
February 2019
2 Reads

The global dissemination of bacterial infections necessitates the study of reverse genomic epidemiology.

Brief Bioinform 2019 Feb 4. Epub 2019 Feb 4.

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Whole genome sequencing (WGS) has revolutionized the genotyping of bacterial pathogens and is expected to become the new gold standard for tracing the transmissions of bacterial infectious diseases for public health purposes. Traditional genomic epidemiology often uses WGS as a verification tool, namely, when a common source or epidemiological link is suspected, the collected isolates are sequenced for the determination of clonal relationships. However, increasingly frequent international travel and food transportation, and the associated potential for the cross-border transmission of bacterial pathogens, often lead to an absence of information on bacterial transmission routes. Read More

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http://dx.doi.org/10.1093/bib/bbz010DOI Listing
February 2019

Decoding competing endogenous RNA networks for cancer biomarker discovery.

Brief Bioinform 2019 Jan 30. Epub 2019 Jan 30.

Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, China.

Crosstalk between competing endogenous RNAs (ceRNAs) is mediated by shared microRNAs (miRNAs) and plays important roles both in normal physiology and tumorigenesis; thus, it is attractive for systems-level decoding of gene regulation. As ceRNA networks link the function of miRNAs with that of transcripts sharing the same miRNA response elements (MREs), e.g. Read More

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http://dx.doi.org/10.1093/bib/bbz006DOI Listing
January 2019

Evaluation of ontology structural metrics based on public repository data.

Brief Bioinform 2019 Feb 4. Epub 2019 Feb 4.

Departamento de Informática y Sistemas, Universidad de Murcia, IMIB-Arrixaca, Murcia, Spain.

The development and application of biological ontologies have increased significantly in recent years. These ontologies can be retrieved from different repositories, which do not provide much information about quality aspects of the ontologies. In the past years, some ontology structural metrics have been proposed, but their validity as measurement instrument has not been sufficiently studied to date. Read More

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http://dx.doi.org/10.1093/bib/bbz009DOI Listing
February 2019

Computational medicine: quantitative modeling of complex diseases.

Authors:
Basant K Tiwary

Brief Bioinform 2019 Jan 30. Epub 2019 Jan 30.

Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry, India.

Biological complex systems are composed of numerous components that interact within and across different scales. The ever-increasing generation of high-throughput biomedical data has given us an opportunity to develop a quantitative model of nonlinear biological systems having implications in health and diseases. Multidimensional molecular data can be modeled using various statistical methods at different scales of biological organization, such as genome, transcriptome and proteome. Read More

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http://dx.doi.org/10.1093/bib/bbz005DOI Listing
January 2019

Disentangling the complexity of low complexity proteins.

Brief Bioinform 2019 Jan 30. Epub 2019 Jan 30.

Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, Mainz, Germany.

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. Read More

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http://dx.doi.org/10.1093/bib/bbz007DOI Listing
January 2019
2 Reads

Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis.

Brief Bioinform 2019 Jan 29. Epub 2019 Jan 29.

Department of Pathology, College of Medicine, Hanyang University, Seoul, Republic of Korea.

Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. Read More

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http://dx.doi.org/10.1093/bib/bbz003DOI Listing
January 2019
4 Reads

Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs.

Brief Bioinform 2019 Jan 23. Epub 2019 Jan 23.

Lab of Innovative Drug Research and Bioinformatics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Drugs produce their therapeutic effects by modulating specific targets, and there are 89 innovative targets of first-in-class drugs approved in 2004-17, each with information about drug clinical trial dated back to 1984. Analysis of the clinical trial timelines of these targets may reveal the trial-speed differentiating features for facilitating target assessment. Here we present a comprehensive analysis of all these 89 targets, following the earlier studies for prospective prediction of clinical success of the targets of clinical trial drugs. Read More

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http://dx.doi.org/10.1093/bib/bby130DOI Listing
January 2019
4 Reads
9.617 Impact Factor

Advanced bioinformatics methods for practical applications in proteomics.

Brief Bioinform 2019 01;20(1):347-355

National University of Singapore.

Mass spectrometry (MS)-based proteomics has undergone rapid advancements in recent years, creating challenging problems for bioinformatics. We focus on four aspects where bioinformatics plays a crucial role (and proteomics is needed for clinical application): peptide-spectra matching (PSM) based on the new data-independent acquisition (DIA) paradigm, resolving missing proteins (MPs), dealing with biological and technical heterogeneity in data and statistical feature selection (SFS). DIA is a brute-force strategy that provides greater width and depth but, because it indiscriminately captures spectra such that signal from multiple peptides is mixed, getting good PSMs is difficult. Read More

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http://dx.doi.org/10.1093/bib/bbx128DOI Listing
January 2019
4 Reads

A comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction.

Brief Bioinform 2019 01;20(1):330-346

School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, China.

Intrinsically disordered proteins and regions are widely distributed in proteins, which are associated with many biological processes and diseases. Accurate prediction of intrinsically disordered proteins and regions is critical for both basic research (such as protein structure and function prediction) and practical applications (such as drug development). During the past decades, many computational approaches have been proposed, which have greatly facilitated the development of this important field. Read More

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http://dx.doi.org/10.1093/bib/bbx126DOI Listing
January 2019
5 Reads

Principal component analysis of binary genomics data.

Brief Bioinform 2019 01;20(1):317-329

Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.

Motivation: Genome-wide measurements of genetic and epigenetic alterations are generating more and more high-dimensional binary data. The special mathematical characteristics of binary data make the direct use of the classical principal component analysis (PCA) model to explore low-dimensional structures less obvious. Although there are several PCA alternatives for binary data in the psychometric, data analysis and machine learning literature, they are not well known to the bioinformatics community. Read More

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https://academic.oup.com/bib/article/20/1/317/4372404
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http://dx.doi.org/10.1093/bib/bbx119DOI Listing
January 2019
5 Reads

Long non-coding RNA transcriptome of uncharacterized samples can be accurately imputed using protein-coding genes.

Brief Bioinform 2019 Jan 17. Epub 2019 Jan 17.

Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA.

Long non-coding RNAs (lncRNAs) play an important role in gene regulation and are increasingly being recognized as crucial mediators of disease pathogenesis. However, the vast majority of published transcriptome datasets lack high-quality lncRNA profiles compared to protein-coding genes (PCGs). Here we propose a framework to harnesses the correlative expression patterns between lncRNA and PCGs to impute unknown lncRNA profiles. Read More

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http://dx.doi.org/10.1093/bib/bby129DOI Listing
January 2019
1 Read

miR+Pathway: the integration and visualization of miRNA and KEGG pathways.

Brief Bioinform 2019 Jan 16. Epub 2019 Jan 16.

Ministry of Agriculture Key Lab of Agricultural Entomology, Institute of Insect Sciences, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.

miRNAs represent a type of noncoding small molecule RNA. Many studies have shown that miRNAs are widely involved in the regulation of various pathways. The key to fully understanding the regulatory function of miRNAs is the determination of the pathways in which the miRNAs participate. Read More

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http://dx.doi.org/10.1093/bib/bby128DOI Listing
January 2019
9 Reads

Corrigendum to: Dating admixture events is unsolved problem in multi-way admixed populations.

Authors:

Brief Bioinform 2019 Jan 14. Epub 2019 Jan 14.

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http://dx.doi.org/10.1093/bib/bbz001DOI Listing
January 2019
1 Read

Structure-based prediction of post-translational modification cross-talk within proteins using complementary residue- and residue pair-based features.

Brief Bioinform 2019 Jan 11. Epub 2019 Jan 11.

Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, P. R. China.

Post-translational modification (PTM)-based regulation can be mediated not only by the modification of a single residue but also by the interplay of different modifications. Accurate prediction of PTM cross-talk is a highly challenging issue and is in its infant stage. Especially, less attention has been paid to the structural preferences (except intrinsic disorder and spatial proximity) of cross-talk pairs and the characteristics of individual residues involved in cross-talk, which may restrict the improvement of the prediction accuracy. Read More

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http://dx.doi.org/10.1093/bib/bby123DOI Listing
January 2019
1 Read

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.

Brief Bioinform 2019 Jan 15. Epub 2019 Jan 15.

College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. Read More

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http://dx.doi.org/10.1093/bib/bby127DOI Listing
January 2019
4 Reads

Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools.

Brief Bioinform 2019 Jan 10. Epub 2019 Jan 10.

College of Intelligence and Computing, Tianjin University, Tianjin, China.

Cell-penetrating peptides (CPPs) facilitate the delivery of therapeutically relevant molecules, including DNA, proteins and oligonucleotides, into cells both in vitro and in vivo. This unique ability explores the possibility of CPPs as therapeutic delivery and its potential applications in clinical therapy. Over the last few decades, a number of machine learning (ML)-based prediction tools have been developed, and some of them are freely available as web portals. Read More

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http://dx.doi.org/10.1093/bib/bby124DOI Listing
January 2019
1 Read

Graph- and rule-based learning algorithms: a comprehensive review of their applications for cancer type classification and prognosis using genomic data.

Brief Bioinform 2019 Jan 11. Epub 2019 Jan 11.

Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center, Houston.

Cancer is well recognized as a complex disease with dysregulated molecular networks or modules. Graph- and rule-based analytics have been applied extensively for cancer classification as well as prognosis using large genomic and other data over the past decade. This article provides a comprehensive review of various graph- and rule-based machine learning algorithms that have been applied to numerous genomics data to determine the cancer-specific gene modules, identify gene signature-based classifiers and carry out other related objectives of potential therapeutic value. Read More

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http://dx.doi.org/10.1093/bib/bby120DOI Listing
January 2019
1 Read

Investigating the role of Simpson's paradox in the analysis of top-ranked features in high-dimensional bioinformatics datasets.

Authors:
Alex A Freitas

Brief Bioinform 2019 Jan 9. Epub 2019 Jan 9.

University of Kent, Kent, UK.

An important problem in bioinformatics consists of identifying the most important features (or predictors), among a large number of features in a given classification dataset. This problem is often addressed by using a machine learning-based feature ranking method to identify a small set of top-ranked predictors (i.e. Read More

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http://dx.doi.org/10.1093/bib/bby126DOI Listing
January 2019
1 Read

Computational prediction and analysis of species-specific fungi phosphorylation via feature optimization strategy.

Brief Bioinform 2018 Dec 27. Epub 2018 Dec 27.

Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, China.

Protein phosphorylation is a reversible and ubiquitous post-translational modification that primarily occurs at serine, threonine and tyrosine residues and regulates a variety of biological processes. In this paper, we first briefly summarized the current progresses in computational prediction of eukaryotic protein phosphorylation sites, which mainly focused on animals and plants, especially on human, with a less extent on fungi. Since the number of identified fungi phosphorylation sites has greatly increased in a wide variety of organisms and their roles in pathological physiology still remain largely unknown, more attention has been paid on the identification of fungi-specific phosphorylation. Read More

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http://dx.doi.org/10.1093/bib/bby122DOI Listing
December 2018
1 Read

Homeolog expression quantification methods for allopolyploids.

Brief Bioinform 2018 12 27. Epub 2018 Dec 27.

Artificial Intelligence Research Center, AIST, 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan.

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi and plants, and is especially common in crop plants. There is an increasing interest in the study of allopolyploids because of advances in polyploid genome assembly; however, the high level of sequence similarity in duplicated gene copies (homeologs) poses many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. Read More

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http://dx.doi.org/10.1093/bib/bby121DOI Listing
December 2018
4 Reads

Fuzzy Petri nets for modelling of uncertain biological systems.

Brief Bioinform 2018 Dec 27. Epub 2018 Dec 27.

Department of Computer Science, Brunel University London, Middlesex, UK.

The modelling of biological systems is accompanied with epistemic uncertainties that range from structural uncertainty to parametric uncertainty due to such limitations as insufficient understanding of the underlying mechanism and incomplete measurement data of a system. Fuzzy logic approaches such as fuzzy Petri nets (FPNs) are effective in addressing these issues. In this paper, we review FPNs that have been used for modelling uncertain biological systems, which we classify in three categories: basic fuzzy Petri nets, fuzzy quantitative Petri nets and Petri nets with fuzzy kinetic parameters. Read More

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http://dx.doi.org/10.1093/bib/bby118DOI Listing
December 2018
2 Reads

Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing.

Brief Bioinform 2018 Dec 18. Epub 2018 Dec 18.

Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.

Knowledge of the full target space of drugs (or drug-like compounds) provides important insights into the potential therapeutic use of the agents to modulate or avoid their various on- and off-targets in drug discovery and precision medicine. However, there is a lack of consolidated databases and associated data exploration tools that allow for systematic profiling of drug target-binding potencies of both approved and investigational agents using a network-centric approach. We recently initiated a community-driven platform, Drug Target Commons (DTC), which is an open-data crowdsourcing platform designed to improve the management, reproducibility and extended use of compound-target bioactivity data for drug discovery and repurposing, as well as target identification applications. Read More

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http://dx.doi.org/10.1093/bib/bby119DOI Listing
December 2018
1 Read

Network embedding in biomedical data science.

Brief Bioinform 2018 Dec 10. Epub 2018 Dec 10.

Department of Healthcare Policy and Research, Weill Cornell Medicine at Cornell University, New York, NY, USA.

Owning to the rapid development of computer technologies, an increasing number of relational data have been emerging in modern biomedical research. Many network-based learning methods have been proposed to perform analysis on such data, which provide people a deep understanding of topology and knowledge behind the biomedical networks and benefit a lot of applications for human healthcare. However, most network-based methods suffer from high computational and space cost. Read More

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http://dx.doi.org/10.1093/bib/bby117DOI Listing
December 2018
3 Reads

Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment.

Brief Bioinform 2018 Nov 29. Epub 2018 Nov 29.

School of Life Science and Technology, Center for Informational Biology, Intelligent Learning Institute for Science and Application, University of Electronic Science and Technology of China, Chengdu, China.

Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computational methods can make up for the deficiencies of expensive and time-consuming experimental technologies. In this review, we have collected researches on essential gene predictions in prokaryotes and eukaryotes and summarized the five predominant types of features used in these studies. Read More

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http://dx.doi.org/10.1093/bib/bby116DOI Listing
November 2018
1 Read

Multilevel heterogeneous omics data integration with kernel fusion.

Brief Bioinform 2018 Nov 29. Epub 2018 Nov 29.

Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China.

High-throughput omics data are generated almost with no limit nowadays. It becomes increasingly important to integrate different omics data types to disentangle the molecular machinery of complex diseases with the hope for better disease prevention and treatment. Since the relationship among different omics data features are typically unknown, a supervised learning model assuming a particular distribution with a specific structure will not serve the purpose to capture the underlying complex relationship between multiple features and a disease phenotype. Read More

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http://dx.doi.org/10.1093/bib/bby115DOI Listing
November 2018
16 Reads

AIMMS suite: a web server dedicated for prediction of drug resistance on protein mutation.

Brief Bioinform 2018 Nov 29. Epub 2018 Nov 29.

Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, P.R. China.

Drug resistance is one of the most intractable issues for successful treatment in current clinical practice. Although many mutations contributing to drug resistance have been identified, the relationship between the mutations and the related pharmacological profile of drug candidates has yet to be fully elucidated, which is valuable both for the molecular dissection of drug resistance mechanisms and for suggestion of promising treatment strategies to counter resistant. Hence, effective prediction approach for estimating the sensitivity of mutations to agents is a new opportunity that counters drug resistance and creates a high interest in pharmaceutical research. Read More

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http://dx.doi.org/10.1093/bib/bby113DOI Listing
November 2018
12 Reads

Subcellular locations of potential cell wall proteins in plants: predictors, databases and cross-referencing.

Brief Bioinform 2018 11;19(6):1130-1140

HAU.

The cell wall is the most striking feature that distinguishes plant cells from animal cells. It plays an essential role in cell shape, stability, growth and protection. Despite being present in small amounts, cell wall proteins (CWPs) are crucial components of the cell wall. Read More

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http://dx.doi.org/10.1093/bib/bbx050DOI Listing
November 2018
2 Reads
9.617 Impact Factor

Cancer-specific expression quantitative loci are affected by expression dysregulation.

Brief Bioinform 2018 Nov 23. Epub 2018 Nov 23.

Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.

Expression quantitative trait loci (eQTLs) have been touted as the missing piece that can bridge the gap between genetic variants and phenotypes. Over the past decade, we have witnessed a sharp rise of effort in the identification and application of eQTLs. The successful application of eQTLs relies heavily on their reproducibility. Read More

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http://dx.doi.org/10.1093/bib/bby108DOI Listing
November 2018
10 Reads
9.620 Impact Factor

Harmonizing semantic annotations for computational models in biology.

Brief Bioinform 2018 Nov 21. Epub 2018 Nov 21.

Research Institute, Center for Global Infectious Disease Research, Seattle, USA.

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. Read More

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http://dx.doi.org/10.1093/bib/bby087DOI Listing
November 2018
2 Reads

The application of Hadoop in structural bioinformatics.

Brief Bioinform 2018 Nov 20. Epub 2018 Nov 20.

Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, United Kingdom.

The paper reviews the use of the Hadoop platform in structural bioinformatics applications. For structural bioinformatics, Hadoop provides a new framework to analyse large fractions of the Protein Data Bank that is key for high-throughput studies of, for example, protein-ligand docking, clustering of protein-ligand complexes and structural alignment. Specifically we review in the literature a number of implementations using Hadoop of high-throughput analyses and their scalability. Read More

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http://dx.doi.org/10.1093/bib/bby106DOI Listing
November 2018
2 Reads

Dating admixture events is unsolved problem in multi-way admixed populations.

Brief Bioinform 2018 Nov 19. Epub 2018 Nov 19.

Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa.

Advances in human sequencing technologies, coupled with statistical and computational tools, have fostered the development of methods for dating admixture events. These methods have merits and drawbacks in estimating admixture events in multi-way admixed populations. Here, we first provide a comprehensive review and comparison of current methods pertinent to dating admixture events. Read More

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http://dx.doi.org/10.1093/bib/bby112DOI Listing
November 2018
3 Reads

Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data.

Brief Bioinform 2018 Nov 20. Epub 2018 Nov 20.

Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea.

Motivation: : Biological pathways are extensively used for the analysis of transcriptome data to characterize biological mechanisms underlying various phenotypes. There are a number of computational tools that summarize transcriptome data at the pathway level. However, there is no comparative study on how well these tools produce useful information at the cohort level, enabling comparison of many samples or patients. Read More

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http://dx.doi.org/10.1093/bib/bby097DOI Listing
November 2018
2 Reads

A comprehensive review of computational prediction of genome-wide features.

Brief Bioinform 2018 Nov 16. Epub 2018 Nov 16.

Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

There are significant correlations among different types of genetic, genomic and epigenomic features within the genome. These correlations make the in silico feature prediction possible through statistical or machine learning models. With the accumulation of a vast amount of high-throughput data, feature prediction has gained significant interest lately, and a plethora of papers have been published in the past few years. Read More

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http://dx.doi.org/10.1093/bib/bby110DOI Listing
November 2018
14 Reads

Bioinformatics methodologies for coeliac disease and its comorbidities.

Brief Bioinform 2018 Nov 16. Epub 2018 Nov 16.

Computer Laboratory, University of Cambridge, JJ Thomson Ave., Cambridge, UK.

Coeliac disease (CD) is a complex, multifactorial pathology caused by different factors, such as nutrition, immunological response and genetic factors. Many autoimmune diseases are comorbidities for CD, and a comprehensive and integrated analysis with bioinformatics approaches can help in evaluating the interconnections among all the selected pathologies. We first performed a detailed survey of gene expression data available in public repositories on CD and less commonly considered comorbidities. Read More

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http://dx.doi.org/10.1093/bib/bby109DOI Listing
November 2018
2 Reads

The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes.

Brief Bioinform 2018 Nov 16. Epub 2018 Nov 16.

College of Chemistry, Sichuan University, Chengdu, Sichuan, P.R. China.

We know that different types of cancers usually have different responses to the same treatment. Therefore, it is important to understand the similarities and differences across subtypes of cancers, so as to provide a basis for the individualized treatments. Until now, no comprehensive investigation on competing endogenous RNAs (ceRNAs) has been reported for the three main subtypes of renal cell carcinoma (RCC), so the regulation characteristics of ceRNAs in three subtypes are not well revealed. Read More

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http://dx.doi.org/10.1093/bib/bby101DOI Listing
November 2018
8 Reads

Characteristics of plant circular RNAs.

Brief Bioinform 2018 Nov 15. Epub 2018 Nov 15.

Institute of Crop Science, Zhejiang University, Hangzhou, China.

Circular RNA (circRNA) is a kind of covalently closed single-stranded RNA molecules that have been proved to play important roles in transcriptional regulation of genes in diverse species. With the rapid development of bioinformatics tools, a huge number (95143) of circRNAs have been identified from different plant species, providing an opportunity for uncovering the overall characteristics of plant circRNAs. Here, based on publicly available circRNAs, we comprehensively analyzed characteristics of plant circRNAs with the help of various bioinformatics tools as well as in-house scripts and workflows, including the percentage of coding genes generating circRNAs, the frequency of alternative splicing events of circRNAs, the non-canonical splicing signals of circRNAs and the networks involving circRNAs, miRNAs and mRNAs. Read More

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http://dx.doi.org/10.1093/bib/bby111DOI Listing
November 2018
1 Read

gmRAD: an integrated SNP calling pipeline for genetic mapping with RADseq across a hybrid population.

Brief Bioinform 2018 Nov 14. Epub 2018 Nov 14.

Southern Modern Forestry Collaborative Innovation Center, College of Forestry, Nanjing Forestry University, Nanjing, China.

Restriction site-associated DNA sequencing (RADseq) is a powerful technology that has been extensively applied in population genetics, phylogenetics and genetic mapping. Although many software packages are available for ecological and evolutionary studies, a few effective tools are available for extracting genotype data with RADseq for genetic mapping, a prerequisite for quantitative trait locus mapping, comparative genomics and genome scaffold assembly. Here, we present an integrated pipeline called gmRAD for generating single nucleotide polymorphism (SNP) genotypes from RADseq data, de novo, across a genetic mapping population derived by crossing two parents. Read More

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http://dx.doi.org/10.1093/bib/bby114DOI Listing
November 2018
2 Reads

HITS-PR-HHblits: protein remote homology detection by combining PageRank and Hyperlink-Induced Topic Search.

Brief Bioinform 2018 Nov 7. Epub 2018 Nov 7.

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.

As one of the most important fundamental problems in protein sequence analysis, protein remote homology detection is critical for both theoretical research (protein structure and function studies) and real world applications (drug design). Although several computational predictors have been proposed, their detection performance is still limited. In this study, we treat protein remote homology detection as a document retrieval task, where the proteins are considered as documents and its aim is to find the highly related documents with the query documents in a database. Read More

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http://dx.doi.org/10.1093/bib/bby104DOI Listing
November 2018
4 Reads

Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms.

Brief Bioinform 2018 Oct 31. Epub 2018 Oct 31.

School of Computer Science and Technology, Tianjin University, Tianjin, China.

Quorum-sensing peptides (QSPs) are the signal molecules that are closely associated with diverse cellular processes, such as cell-cell communication, and gene expression regulation in Gram-positive bacteria. It is therefore of great importance to identify QSPs for better understanding and in-depth revealing of their functional mechanisms in physiological processes. Machine learning algorithms have been developed for this purpose, showing the great potential for the reliable prediction of QSPs. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/bib/bby107DOI Listing
October 2018
2 Reads

CytoPred: 7-gene pair metric for AML cytogenetic risk prediction.

Brief Bioinform 2018 Oct 30. Epub 2018 Oct 30.

Shilpee Dutt laboratory, Tata Memorial Centre, Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai, India.

Cytogenetic-based subjective prognostication of acute myeloid leukemia (AML) patients is a cumbersome process. Top scoring pair (TSP)-based decision tree using a robust analytical algorithm with statistical rigor offers a promising alternative. We describe CytoPred as a 7-gene pair signature based on the analysis of 2547 AML patient sample gene expression data using a modified TSP algorithm to estimate cytogenetic risk. Read More

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https://academic.oup.com/bib/advance-article/doi/10.1093/bib
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http://dx.doi.org/10.1093/bib/bby100DOI Listing
October 2018
3 Reads
9.620 Impact Factor

dbCPM: a manually curated database for exploring the cancer passenger mutations.

Brief Bioinform 2018 Oct 30. Epub 2018 Oct 30.

Institute of Physical Science and Information Technology, School of Computer Science and Technology, Anhui University, Hefei, Anhui, China.

While recently emergent driver mutation data sets are available for developing computational methods to predict cancer mutation effects, benchmark sets focusing on passenger mutations are largely missing. Here, we developed a comprehensive literature-based database of Cancer Passenger Mutations (dbCPM), which contains 941 experimentally supported and 978 putative passenger mutations derived from a manual curation of the literature. Using the missense mutation data, the largest group in the dbCPM, we explored patterns of missense passenger mutations by comparing them with the missense driver mutations and assessed the performance of four cancer-focused mutation effect predictors. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/bib/bby105DOI Listing
October 2018
3 Reads

Landscape of SNPs-mediated lncRNA structural variations and their implication in human complex diseases.

Brief Bioinform 2018 Oct 30. Epub 2018 Oct 30.

Wenzhou Medical University.

An increasing number of functional studies shows that long noncoding RNAs (lncRNAs) are involved in many aspects of cellular physiology and fulfills a wide variety of regulatory roles at almost every stage of gene expression. A major feature of lncRNAs is the highly folded modular domains in transcripts. With improved modeling and definition, it is now feasible to explore and gain novel insights into the structural-functional relationship of lncRNAs and their association with complex human diseases. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/bib/bby102DOI Listing
October 2018
17 Reads

Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power.

Brief Bioinform 2018 Oct 31. Epub 2018 Oct 31.

College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, P. R. China.

Protein kinases have been regarded as important therapeutic targets for many diseases. Currently, a total of 41 kinase inhibitors have been approved by the Food and Drug Administration, along with a large number of kinase inhibitors being evaluated in clinical and preclinical trials. Among all, allosteric inhibitors, such as type II kinase inhibitors, have attracted extensive attention owing to their potential high selectivity. Read More

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http://dx.doi.org/10.1093/bib/bby103DOI Listing
October 2018
4 Reads