GOGrapher: A Python library for GO graph representation and analysis
作者： Brian Muller , Adam J Richards , Bo Jin , Xinghua Lu
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摘要: Background The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in ontology are organized as a directed acyclic graph, which node corresponds to biological concept and edge denotes parent-child semantic relationship between pair of terms. A large number protein annotations further create links proteins their functional annotations, reflecting contemporary knowledge about relationships. This leads complex graph consisting interleaved associated What needed simple, open source library that provides tools not only view but analyze manipulate it well. Here we describe development use GOGrapher, Python can be creation, analysis, manipulation, visualization related graphs.
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sci-hub.se 参考文章(5)
A. Alexa, J. Rahnenfuhrer, T. Lengauer, Improved scoring of functional groups from gene expression data by decorrelating GO graph structure Bioinformatics. ,vol. 22, pp. 1600- 1607 ,(2006) , 10.1093/BIOINFORMATICS/BTL140
Jelle J. Goeman, Ulrich Mansmann, Multiple testing on the directed acyclic graph of gene ontology Bioinformatics. ,vol. 24, pp. 537- 544 ,(2008) , 10.1093/BIOINFORMATICS/BTM628
Aric A. Hagberg, Daniel A. Schult, Pieter J. Swart, Exploring Network Structure, Dynamics, and Function using NetworkX ,(2008)
P. Khatri, S. Draghici, Ontological analysis of gene expression data: current tools, limitations, and open problems Bioinformatics. ,vol. 21, pp. 3587- 3595 ,(2005) , 10.1093/BIOINFORMATICS/BTI565
S. Grossmann, S. Bauer, P. N. Robinson, M. Vingron, Improved detection of overrepresentation of Gene-Ontology annotations with parent–child analysis Bioinformatics. ,vol. 23, pp. 3024- 3031 ,(2007) , 10.1093/BIOINFORMATICS/BTM440