Details

Autor(en) / Beteiligte

• Ishida, Takashi
• Kinoshita, Kengo

Titel

Prediction of disordered regions in proteins based on the meta approach

Ist Teil von

• Bioinformatics, 2008-06, Vol.24 (11), p.1344-1348

Ort / Verlag

Oxford: Oxford University Press

Erscheinungsjahr

2008

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Motivation: Intrinsically disordered regions in proteins have no unique stable structures without their partner molecules, thus these regions sometimes prevent high-quality structure determination. Furthermore, proteins with disordered regions are often involved in important biological processes, and the disordered regions are considered to play important roles in molecular interactions. Therefore, identifying disordered regions is important to obtain high-resolution structural information and to understand the functional aspects of these proteins. Results: We developed a new prediction method for disordered regions in proteins based on the meta approach and implemented a web-server for this prediction method named ‘metaPrDOS’. The method predicts the disorder tendency of each residue using support vector machines from the prediction results of the seven independent predictors. Evaluation of the meta approach was performed using the CASP7 prediction targets to avoid an overestimation due to the inclusion of proteins used in the training set of some component predictors. As a result, the meta approach achieved higher prediction accuracy than all methods participating in CASP7. Availability: http://prdos.hgc.jp/meta/ Contact: t-ishida@hgc.jp