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Briefings in Bioinformatics

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https://www.readbyqxmd.com/read/29897426/connectome-verification-inter-rater-and-connection-reliability-of-tract-tracing-based-intrinsic-hypothalamic-connectivity
#1
Oliver Schmitt, Peter Eipert, Sebastian Schwanke, Felix Lessmann, Jennifer Meinhardt, Julia Beier, Kanar Kadir, Adrian Karnitzki, Linda Sellner, Ann-Christin Klünker, Frauke Ruß, Jörg Jenssen
Motivation: Structural connectomics supports understanding aspects of neuronal dynamics and brain functions. Conducting metastudies of tract-tracing publications is one option to generate connectome databases by collating neuronal connectivity data. Meanwhile, it is a common practice that the neuronal connections and their attributes of such retrospective data collations are extracted from tract-tracing publications manually by experts. As the description of tract-tracing results is often not clear-cut and the documentation of interregional connections is not standardized, the extraction of connectivity data from tract-tracing publications could be complex...
June 11, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29893792/regulatory-variants-from-detection-to-predicting-impact
#2
Elena Rojano, Pedro Seoane, Juan A G Ranea, James R Perkins
Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression...
June 8, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29868902/microbial-genomic-island-discovery-visualization-and-analysis
#3
Claire Bertelli, Keith E Tilley, Fiona S L Brinkman
Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc)...
June 3, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29868818/a-comparison-of-mechanistic-signaling-pathway-activity-analysis-methods
#4
Alicia Amadoz, Marta R Hidalgo, Cankut Çubuk, José Carbonell-Caballero, Joaquín Dopazo
Understanding the aspects of cell functionality that account for disease mechanisms or drug modes of action is a main challenge for precision medicine. Classical gene-based approaches ignore the modular nature of most human traits, whereas conventional pathway enrichment approaches produce only illustrative results of limited practical utility. Recently, a family of new methods has emerged that change the focus from the whole pathways to the definition of elementary subpathways within them that have any mechanistic significance and to the study of their activities...
June 3, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29868882/in-silico-clinical-trials-concepts-and-early-adoptions
#5
Francesco Pappalardo, Giulia Russo, Flora Musuamba Tshinanu, Marco Viceconti
Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process...
June 2, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29860277/toward-more-accurate-prediction-of-caspase-cleavage-sites-a-comprehensive-review-of-current-methods-tools-and-features
#6
Yu Bao, Simone Marini, Takeyuki Tamura, Mayumi Kamada, Shingo Maegawa, Hiroshi Hosokawa, Jiangning Song, Tatsuya Akutsu
As one of the few irreversible protein posttranslational modifications, proteolytic cleavage is involved in nearly all aspects of cellular activities, ranging from gene regulation to cell life-cycle regulation. Among the various protease-specific types of proteolytic cleavage, cleavages by casapses/granzyme B are considered as essential in the initiation and execution of programmed cell death and inflammation processes. Although a number of substrates for both types of proteolytic cleavage have been experimentally identified, the complete repertoire of caspases and granzyme B substrates remains to be fully characterized...
May 31, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29800060/survey-of-mirna-mirna-cooperative-regulation-principles-across-cancer-types
#7
Tingting Shao, Guangjuan Wang, Hong Chen, Yunjin Xie, Xiyun Jin, Jing Bai, Juan Xu, Xia Li, Jian Huang, Yan Jin, Yongsheng Li
Cooperative regulation among multiple microRNAs (miRNAs) is a complex type of posttranscriptional regulation in human; however, the global view of the system-level regulatory principles across cancers is still unclear. Here, we investigated miRNA-miRNA cooperative regulatory landscape across 18 cancer types and summarized the regulatory principles of miRNAs. The miRNA-miRNA cooperative pan-cancer network exhibited a scale-free and modular architecture. Cancer types with similar tissue origins had high similarity in cooperative network structure and expression of cooperative miRNA pairs...
May 25, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29800232/predicting-novel-microrna-a-comprehensive-comparison-of-machine-learning-approaches
#8
Georgina Stegmayer, Leandro E Di Persia, Mariano Rubiolo, Matias Gerard, Milton Pividori, Cristian Yones, Leandro A Bugnon, Tadeo Rodriguez, Jonathan Raad, Diego H Milone
Motivation: The importance of microRNAs (miRNAs) is widely recognized in the community nowadays because these short segments of RNA can play several roles in almost all biological processes. The computational prediction of novel miRNAs involves training a classifier for identifying sequences having the highest chance of being precursors of miRNAs (pre-miRNAs). The big issue with this task is that well-known pre-miRNAs are usually few in comparison with the hundreds of thousands of candidate sequences in a genome, which results in high class imbalance...
May 23, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29788276/proteomic-analysis-and-prediction-of-amino-acid-variations-that-influence-protein-posttranslational-modifications
#9
Shaoping Shi, Lina Wang, Man Cao, Guodong Chen, Jialin Yu
Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis...
May 17, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29726961/application-of-atlas-of-cancer-signalling-network-in-preclinical-studies
#10
L Cristobal Monraz Gomez, Maria Kondratova, Jean-Marie Ravel, Emmanuel Barillot, Andrei Zinovyev, Inna Kuperstein
Cancer initiation and progression are associated with multiple molecular mechanisms. The knowledge of these mechanisms is expanding and should be converted into guidelines for tackling the disease. Here, we discuss the formalization of biological knowledge into a comprehensive resource: the Atlas of Cancer Signalling Network (ACSN) and the Google Maps-based tool NaviCell, which supports map navigation. The application of ACSN for omics data visualization, in the context of signalling maps, is possible via the NaviCell Web Service module and through the NaviCom tool...
May 3, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29726962/integrated-use-of-bioinformatic-resources-reveals-that-co-targeting-of-histone-deacetylases-ikbk-and-src-inhibits-epithelial-mesenchymal-transition-in-cancer
#11
Farnaz Barneh, Mehdi Mirzaie, Payman Nickchi, Tuan Zea Tan, Jean Paul Thiery, Mehran Piran, Mona Salimi, Fatemeh Goshadrou, Amir R Aref, Mohieddin Jafari
With the advent of high-throughput technologies leading to big data generation, increasing number of gene signatures are being published to predict various features of diseases such as prognosis and patient survival. However, to use these signatures for identifying therapeutic targets, use of additional bioinformatic tools is indispensible part of research. Here, we have generated a pipeline comprised of nearly 15 bioinformatic tools and enrichment statistical methods to propose and validate a drug combination strategy from already approved drugs and present our approach using published pan-cancer epithelial-mesenchymal transition (EMT) signatures as a case study...
May 2, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29701762/post-genome-wide-association-analysis-dissecting-computational-pathway-network-based-approaches
#12
Emile R Chimusa, Shareefa Dalvie, Collet Dandara, Ambroise Wonkam, Gaston K Mazandu
Over thousands of genetic associations to diseases have been identified by genome-wide association studies (GWASs), which conceptually is a single-marker-based approach. There are potentially many uses of these identified variants, including a better understanding of the pathogenesis of diseases, new leads for studying underlying risk prediction and clinical prediction of treatment. However, because of inadequate power, GWAS might miss disease genes and/or pathways with weak genetic or strong epistatic effects...
April 26, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29697742/prediction-of-lncrnas-and-their-interactions-with-nucleic-acids-benchmarking-bioinformatics-tools
#13
Ivan V Antonov, Evgeny Mazurov, Mark Borodovsky, Yulia A Medvedeva
The genomes of mammalian species are pervasively transcribed producing as many noncoding as protein-coding RNAs. There is a growing body of evidence supporting their functional role. Long noncoding RNA (lncRNA) can bind both nucleic acids and proteins through several mechanisms. A reliable computational prediction of the most probable mechanism of lncRNA interaction can facilitate experimental validation of its function. In this study, we benchmarked computational tools capable to discriminate lncRNA from mRNA and predict lncRNA interactions with other nucleic acids...
April 24, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29697740/pattern-recognition-analysis-on-long-noncoding-rnas-a-tool-for-prediction-in-plants
#14
Tatianne da Costa Negri, Wonder Alexandre Luz Alves, Pedro Henrique Bugatti, Priscila Tiemi Maeda Saito, Douglas Silva Domingues, Alexandre Rossi Paschoal
Motivation: Long noncoding RNAs (lncRNAs) correspond to a eukaryotic noncoding RNA class that gained great attention in the past years as a higher layer of regulation for gene expression in cells. There is, however, a lack of specific computational approaches to reliably predict lncRNA in plants, which contrast the variety of prediction tools available for mammalian lncRNAs. This distinction is not that obvious, given that biological features and mechanisms generating lncRNAs in the cell are likely different between animals and plants...
April 24, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29688321/comparison-and-evaluation-of-integrative-methods-for-the-analysis-of-multilevel-omics-data-a-study-based-on-simulated-and-experimental-cancer-data
#15
Bettina M Pucher, Oana A Zeleznik, Gerhard G Thallinger
Integrative analysis aims to identify the driving factors of a biological process by the joint exploration of data from multiple cellular levels. The volume of omics data produced is constantly increasing, and so too does the collection of tools for its analysis. Comparative studies assessing performance and the biological value of results, however, are rare but in great demand. We present a comprehensive comparison of three integrative analysis approaches, sparse canonical correlation analysis (sCCA), non-negative matrix factorization (NMF) and logic data mining MicroArray Logic Analyzer (MALA), by applying them to simulated and experimental omics data...
April 23, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29688273/community-driven-roadmap-for-integrated-disease-maps
#16
Marek Ostaszewski, Stephan Gebel, Inna Kuperstein, Alexander Mazein, Andrei Zinovyev, Ugur Dogrusoz, Jan Hasenauer, Ronan M T Fleming, Nicolas Le Novère, Piotr Gawron, Thomas Ligon, Anna Niarakis, David Nickerson, Daniel Weindl, Rudi Balling, Emmanuel Barillot, Charles Auffray, Reinhard Schneider
The Disease Maps Project builds on a network of scientific and clinical groups that exchange best practices, share information and develop systems biomedicine tools. The project aims for an integrated, highly curated and user-friendly platform for disease-related knowledge. The primary focus of disease maps is on interconnected signaling, metabolic and gene regulatory network pathways represented in standard formats. The involvement of domain experts ensures that the key disease hallmarks are covered and relevant, up-to-date knowledge is adequately represented...
April 23, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29897421/robust-genetic-interaction-analysis
#17
Mengyun Wu, Shuangge Ma
For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that genetic interactions (including gene-gene and gene-environment interactions) play important roles beyond the main genetic and environmental effects. In practical genetic interaction analyses, model mis-specification and outliers/contaminations in response variables and covariates are not uncommon, and demand robust analysis methods. Compared with their nonrobust counterparts, robust genetic interaction analysis methods are significantly less popular but are gaining attention fast...
April 19, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29897410/iprot-sub-a-comprehensive-package-for-accurately-mapping-and-predicting-protease-specific-substrates-and-cleavage-sites
#18
Jiangning Song, Yanan Wang, Fuyi Li, Tatsuya Akutsu, Neil D Rawlings, Geoffrey I Webb, Kuo-Chen Chou
Regulation of proteolysis plays a critical role in a myriad of important cellular processes. The key to better understanding the mechanisms that control this process is to identify the specific substrates that each protease targets. To address this, we have developed iProt-Sub, a powerful bioinformatics tool for the accurate prediction of protease-specific substrates and their cleavage sites. Importantly, iProt-Sub represents a significantly advanced version of its successful predecessor, PROSPER. It provides optimized cleavage site prediction models with better prediction performance and coverage for more species-specific proteases (4 major protease families and 38 different proteases)...
April 19, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29684165/navigating-the-disease-landscape-knowledge-representations-for-contextualizing-molecular-signatures
#19
Mansoor Saqi, Artem Lysenko, Yi-Ke Guo, Tatsuhiko Tsunoda, Charles Auffray
Large amounts of data emerging from experiments in molecular medicine are leading to the identification of molecular signatures associated with disease subtypes. The contextualization of these patterns is important for obtaining mechanistic insight into the aberrant processes associated with a disease, and this typically involves the integration of multiple heterogeneous types of data. In this review, we discuss knowledge representations that can be useful to explore the biological context of molecular signatures, in particular three main approaches, namely, pathway mapping approaches, molecular network centric approaches and approaches that represent biological statements as knowledge graphs...
April 19, 2018: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29672663/analysis-of-long-noncoding-rnas-highlights-region-specific-altered-expression-patterns-and-diagnostic-roles-in-alzheimer-s-disease
#20
Meng Zhou, Hengqiang Zhao, Xinyu Wang, Jie Sun, Jianzhong Su
Increasing evidence has revealed the multiple roles of long noncoding RNAs (lncRNAs) in neurodevelopment, brain function and aging, and their dysregulation was implicated in many types of neurological diseases. However, expression pattern and diagnostic role of lncRNAs in Alzheimer's disease (AD) remain largely unknown and has gained significant attention. In this study, we performed a comparative analysis for lncRNA expression profiles in four brain regions in brain aging and AD. Our analysis revealed age- and disease-dependent region-specific lncRNA expression patterns in aging and AD...
April 17, 2018: Briefings in Bioinformatics
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