Title :
Hub chacterization from sequence information using statistical methods
Author :
Mahalakshmi, T. ; Sajeev, J.
Author_Institution :
Sree Narayana Inst. of Technol., Univ. of Kerala, Kollam, India
Abstract :
Maps of Protein Interaction Networks (PIN) are important as they provide clues about the functions of individual proteins as well as enable system level analyses of cellular processes. Predicting hub proteins, the highly connected proteins in PIN, is a challenging computational problem. This paper proposes two statistical methods for predicting hub proteins which applied on two different data bases - APID, HPRD - has revealed good results. In these methods, Shannon Index (a biodiversity measure) is used along with amino acid attributes Transfer Free Energy to Surface (TFES) and Hydrophobicity to distinguish hub proteins from non-hub proteins.
Keywords :
biology computing; proteins; statistical analysis; APID database; HPRD database; Shannon index; biodiversity measure; cellular process; hub characterization; hydrophobicity; protein interaction network map; sequence information; statistical methods; transfer free energy to surface; Amino acids; Bioinformatics; Humans; Indexes; Proteins; Training; APID; HPRD; Highly Connected; Hub Proteins; Hydrophobic; Protein Interaction Network (PIN); Shannon Index; Transfer Free Energy to Surface (TFES);
Conference_Titel :
Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE
Conference_Location :
Trivandrum
Print_ISBN :
978-1-4244-9478-1
DOI :
10.1109/RAICS.2011.6069299
