title: Accurate prediction of protein relative solvent accessibility using a balanced model.
abstract: BACKGROUND
  Protein relative solvent accessibility provides insight into understanding protein structure and function. Prediction of protein relative solvent accessibility is often the first stage of predicting other protein properties. Recent predictors of relative solvent accessibility discriminate against exposed regions as compared with buried regions, resulting in higher prediction accuracy associated with buried regions relative to exposed regions.
  
  
  METHODS
  Here, we propose a more accurate and balanced predictor of protein relative solvent accessibility. First, we collected known proteins in three subsets according to sequence length and constructed a balanced dataset after reducing redundancy within each subset. Next, we measured the performance associated with different variables and variable combinations to determine the best variable combination. Finally, a predictor called BMRSA was constructed for modelling and prediction, which used the balanced set as the training set, the position- specific scoring matrix, predicted secondary structure, buried-exposed profile, and length of a query sequence as variables, and the conditional random field as the machine-learning method.
  
  
  RESULTS
  BMRSA performance on test sets confirmed that our approach improved prediction accuracy relative to state-of-the-art approaches and was balanced in its comparison of buried and exposed regions. Our method is valuable when higher levels of accuracy in predicting exposed-residue states are required. The BMRSA is available at: http://cheminfo.tongji.edu.cn:8080/BMRSA/.
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wu
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Zhiheng
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Peisheng
authors.initials: P
authors.lastname: Cong
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Tonghua
authors.initials: T
authors.lastname: Li
keywords: Balanceable model; Prediction; Profile; Relative solvent accessibility