title: Efficacy of different protein descriptors in predicting protein functional families.
abstract: BACKGROUND
  Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a need to comparatively evaluate the effectiveness of these descriptor-sets by using the same method and parameter optimization algorithm, and to examine whether the combined use of these descriptor-sets help to improve predictive performance. Six individual descriptor-sets and four combination-sets were evaluated in support vector machines (SVM) prediction of six protein functional families.
  
  
  RESULTS
  The performance of these descriptor-sets were ranked by Matthews correlation coefficient (MCC), and categorized into two groups based on their performance. While there is no overwhelmingly favourable choice of descriptor-sets, certain trends were found. The combination-sets tend to give slightly but consistently higher MCC values and thus overall best performance such that three out of four combination-sets show slightly better performance compared to one out of six individual descriptor-sets.
  
  
  CONCLUSIONS
  Our study suggests that currently used descriptor-sets are generally useful for classifying proteins and the prediction performance may be enhanced by exploring combinations of descriptors.
authors: Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 08-14, 3 Science Drive 2, Singapore 117543, Singapore. renese7@gmail.com
authors: Serene A K
authors: SA
authors: Ong
authors: Hong Huang
authors: HH
authors: Lin
authors: Yu Zong
authors: YZ
authors: Chen
authors: Ze Rong
authors: ZR
authors: Li
authors: Zhiwei
authors: Z
authors: Cao
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000145:classification* / Q000378:metabolism; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins
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