Protein aggregation, structural disorder and RNA-binding ability: a new approach for physico-chemical and gene ontology classification of multiple datasets

BMC Genomics

Software

Carmen Maria Livi¹  Petr Klus¹  Riccardo Delli Ponti¹  Gian Gaetano Tartaglia² 

[1] Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain;Universitat Pompeu Fabra (UPF), 08003, Barcelona, Spain;Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain;Universitat Pompeu Fabra (UPF), 08003, Barcelona, Spain;Institució Catalana de Recerca i Estudis Avançats (ICREA), 23 Passeig Lluís Companys, 08010, Barcelona, Spain;

关键词: Protein classification;    Physico-chemical properties;    Gene ontology;    Solubility;    RNA-binding ability;   

DOI  :  10.1186/s12864-015-2280-z

 received in 2015-05-28, accepted in 2015-12-08,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundComparison between multiple protein datasets requires the choice of an appropriate reference system and a number of variables to describe their differences. Here we introduce an innovative approach to discriminate multiple protein datasets (multiCM) and to measure enrichments in gene ontology terms (cleverGO) using semantic similarities.ResultsWe illustrate the powerfulness of our approach by investigating the links between RNA-binding ability and other protein features, such as structural disorder and aggregation, in S. cerevisiae, C. elegans, M. musculus and H. sapiens. Our results are in striking agreement with available experimental evidence and unravel features that are key to understand the mechanisms regulating cellular homeostasis. ConclusionsIn an intuitive way, multiCM and cleverGO provide accurate classifications of physico-chemical features and annotations of biological processes, molecular functions and cellular components, which is extremely useful for the discovery and characterization of new trends in protein datasets. The multiCM and cleverGO can be freely accessed on the Web at http://www.tartaglialab.com/cs_multi/submission and http://www.tartaglialab.com/GO_analyser/universal. Each of the pages contains links to the corresponding documentation and tutorial.

【 授权许可】

CC BY   
© Klus et al. 2015