title: Entropic Biological Score: a cell cycle investigation for GRNs inference.
abstract: Inference of gene regulatory networks (GRNs) is one of the most challenging research problems of Systems Biology. In this investigation, a new GRNs inference methodology, called Entropic Biological Score (EBS), which linearly combines the mean conditional entropy (MCE) from expression levels and a Biological Score (BS), obtained by integrating different biological data sources, is proposed. The EBS is validated with the Cell Cycle related functional annotation information, available from Munich Information Center for Protein Sequences (MIPS), and compared with some existing methods like MRNET, ARACNE, CLR and MCE for GRNs inference. For real networks, the performance of EBS, which uses the concept of integrating different data sources, is found to be superior to the aforementioned inference methods. The best results for EBS are obtained by considering the weights w1=0.2 and w2=0.8 for MCE and BS values, respectively, where approximately 40% of the inferred connections are found to be correct and significantly better than related methods. The results also indicate that expression profile is able to recover some true connections, that are not present in biological annotations, thus leading to the possibility of discovering new relations between its genes.
authors.affiliation: Federal University of Technology, Paraná, Brazil. Electronic address: fabricio@utfpr.edu.br.
authors.forename: Fabrício M
authors.initials: FM
authors.lastname: Lopes
authors.affiliation: Center for Soft Computing Research and Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700108, India. Electronic address: shubhra@isical.ac.in.
authors.forename: Shubhra Sankar
authors.initials: SS
authors.lastname: Ray
authors.affiliation: Institute of Mathematics and Statistics, University of São Paulo, Brazil. Electronic address: ronaldo@ime.usp.br.
authors.forename: Ronaldo F
authors.initials: RF
authors.lastname: Hashimoto
authors.affiliation: Institute of Mathematics and Statistics, University of São Paulo, Brazil; Brazilian Bioethanol Science and Technology Laboratory (CTBE), Brazil. Electronic address: cesar@ime.usp.br.
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Cesar
mesh_terms: D002453:Cell Cycle / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D019277:Entropy; D015870:Gene Expression; D053263:Gene Regulatory Networks; D008962:Models, Theoretical; D010641:Phenotype; D025941:Protein Interaction Mapping
keywords: Biological Score; Cell Cycle network; Entropic Biological Score; GRNs inference; Gene regulatory networks