Improving domain-based protein interaction prediction using biologically-significant negative dataset

International Journal of Data Mining and Bioinformatics

Volumn 1, Issue 2, 2006, Pages 138-149

  Li, Xiao Li ^a   Tan, Soon Heng ^a   Ng, See Kiong ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

biologically significant negative set; classification; domain domain interaction; F measure; protein protein interaction prediction; randomly selected negative set

Indexed keywords

ANIMAL; ARTICLE; COMPUTER PROGRAM; METHODOLOGY; PROTEIN ANALYSIS; PROTEIN BINDING; PROTEIN DATABASE; PROTEIN TERTIARY STRUCTURE; SPECIES DIFFERENCE; STATISTICAL MODEL;

ANIMALS; DATABASES, PROTEIN; MODELS, STATISTICAL; PROTEIN BINDING; PROTEIN INTERACTION MAPPING; PROTEIN STRUCTURE, TERTIARY; SOFTWARE; SPECIES SPECIFICITY;

EID: 43549094730     PISSN: 17485673     EISSN: 17485681     Source Type: Journal    
DOI: 10.1504/IJDMB.2006.010852     Document Type: Article

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18. This manuscript is based on our recent conference paper (Li et al., 2005), with additional materials on the use of GO annotations for defining biologically-significant negative datasets, and a more comprehensive evaluation of our proposed approach with results based on interaction data from multiple species.
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