Protein secondary structure prediction using a small training set (compact model) combined with a Complex-valued neural network approach

• Main Authors: Rashid, Shamima, Saraswathi, Saras, Kloczkowski, Andrzej, Sundaram, Suresh, Kolinski, Andrzej
• Other Authors: School of Computer Engineering
• Format: Article
• Language: English
• Published: 2016
• Subjects: Heuristics; Secondary structure prediction
• Online Access: https://hdl.handle.net/10356/84028; http://hdl.handle.net/10220/41590
• Institution: Nanyang Technological University

Background: Protein secondary structure prediction (SSP) has been an area of intense research interest. Despite advances in recent methods conducted on large datasets, the estimated upper limit accuracy is yet to be reached. Since the predictions of SSP methods are applied as input to higher-level s...