Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 55, Issue 5, Pages 1077-1086Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ci500760m
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Funding
- FEDER funds through Operational Programme for Competitiveness Factors (COMPETE)
- National Funds through FCT (Foundation for Science and Technology) [PEST-C/EQB/LA0006/2013, COMPETE FCOMP-01-0124-FEDER-37285]
- Collaborative Project on Medical Informatics (CIMED) - Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation [PI13/00280]
- European Regional Development Funds (FEDER)
- Galician Network of Drugs R+D REGID (Xunta de Galicia) [R2014/025]
- FCT Ciencia
- FCT - European Social Fund [IF/00578/2014]
- FCT - Programa Operacional Potencial Humano [IF/00578/2014]
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Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems) The best models for these interactions have been implemented in two free Web tools.
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