Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
RECOMB '97 Proceedings of the first annual international conference on Computational molecular biology
Multiple sequence alignment using tabu search
APBC '04 Proceedings of the second conference on Asia-Pacific bioinformatics - Volume 29
IBM Systems Journal - Deep computing for the life sciences
New techniques for extracting features from protein sequences
IBM Systems Journal - Deep computing for the life sciences
Scatter Search algorithm for Protein Structure Prediction
International Journal of Bioinformatics Research and Applications
Transmembrane segments prediction and understanding using support vector machine and decision tree
Expert Systems with Applications: An International Journal
Understanding protein structure prediction using SVM_DT
ISPA'05 Proceedings of the 2005 international conference on Parallel and Distributed Processing and Applications
Multi-level clustering support vector machine trees for improved protein local structure prediction
International Journal of Data Mining and Bioinformatics
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The importance of protein folding has been recognised for many years. Almost a half century ago, Linus Pauling discovered two quite simple, regular arrangements of amino acids the α-helix and the β-sheet that are found in almost every protein. In the early 1960s, Christian Anfinsen showed that the proteins actually "tie" themselves: If proteins become unfolded, they fold back into proper shape of their own accord; no shaper or folder is needed. The nature of the unfolded state plays a great role in understanding proteins. Alzheimer's disease, cystic fibrosis, mad cow disease, and many cancers are inherited emphysema. Recent discoveries show that all these apparently unrelated diseases result from protein folding gone wrong. Theoretical and computational studies have recently achieved noticeable success in reproducing various features of the folding mechanism of several small to medium-sized fast-folding proteins. This survey presents the state-of-the-art in protein structure prediction methods from a computer scientist perspective.