標題: Applying Stacked and Cascade Generalizations to B-cell Epitope Prediction
作者: Hu, Yuh-Jyh
Lin, Shun-Chien
Lin, Yu-Lung
分子醫學與生物工程研究所
Institute of Molecular Medicine and Bioengineering
關鍵字: epitope prediction;linear;conformational;meta learning
公開日期: 1-Jan-2014
摘要: One of the major challenges in the field of vaccine design is to identify the B-cell epitopes in ever-evolving viruses. Various prediction servers have been developed to predict linear or conformational epitopes, each relying on different physicochemical properties and adopting distinct search strategies. We propose meta learning approaches to epitope prediction based on stacked generalization and cascade generalization. By combining the base prediction servers in a hierarchical architecture, we demonstrated that a meta learner outperformed the best single server in predicting the epitopes of an independent dataset of pathogen proteins.
URI: http://hdl.handle.net/11536/124924
ISBN: 978-84-15814-84-9
ISSN: 
期刊: PROCEEDINGS IWBBIO 2014: INTERNATIONAL WORK-CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1 AND 2
起始頁: 1154
結束頁: 1163
Appears in Collections:Conferences Paper