Results 61 to 70 of about 7,142,455 (272)
Integration of molecular network data reconstructs Gene Ontology. [PDF]
, 2014 Motivation: Recently, a shift was made from using Gene Ontology (GO) to evaluate molecular network data to using these data to construct and evaluate GO. Dutkowski et al. provide the first evidence that a large part of GO can be reconstructed solely from
Gligorijević, V, Janjić, V, Pržulj, N
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Construction of ontology augmented networks for protein complex prediction.
PLoS ONE, 2013 Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational ...
Yijia Zhang +3 more
doaj +1 more source
Length bias correction in gene ontology enrichment analysis using logistic regression. [PDF]
PLoS ONE, 2012 When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence
Gu Mi +4 more
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GOATOOLS: A Python library for Gene Ontology analyses
Scientific Reports, 2018 The biological interpretation of gene lists with interesting shared properties, such as up- or down-regulation in a particular experiment, is typically accomplished using gene ontology enrichment analysis tools. Given a list of genes, a gene ontology (GO)
D. Klopfenstein +13 more
semanticscholar +1 more source
BMC Genomics, 2010 Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by ...
Tsatsoulis Costas, Amthauer Heather A
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InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk
BMC Genomics, 2018 Background Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human ...
Liang Cheng +6 more
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BioData Mining, 2019 The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental ...
A. Brionne +2 more
semanticscholar +1 more source
Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting [PDF]
, 2014 Copyright @ 2014 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use ...
Dumontier, M +3 more
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A Simple Protocol for Informative Visualization of Enriched Gene Ontology Terms
Bio-protocol, 2019 [Abstract] In genome-scale datasets, Gene Ontology (GO) enrichment is a common analysis to highlight functions over-represented or under-represented in a subset of differentially expressed genes to elucidate the biological significance of the results ...
Titouan Bonnot +2 more
semanticscholar +1 more source
GOnet: a tool for interactive Gene Ontology analysis
BMC Bioinformatics, 2018 Biological interpretation of gene/protein lists resulting from -omics experiments can be a complex task. A common approach consists of reviewing Gene Ontology (GO) annotations for entries in such lists and searching for enrichment patterns. Unfortunately,
M. Pomaznoy, Brendan Ha, Bjoern Peters
semanticscholar +1 more source