In this paper, a novel method to predict protein secondary structure (e.g., helix, beta-sheet and coil) is described. Our method predicts the secondary structure for a query sequence using a segment-wise similarity search, which finds the most probable secondary structure based on similarities between a set of sequence segments of a query sequence and our segment databases: the segment sequence...

MOTIVATION Protein secondary structure prediction is an important step towards understanding how proteins fold in three dimensions. Recent analysis by information theory indicates that the correlation between neighboring secondary structures are much stronger than that of neighboring amino acids. In this article, we focus on the combination problem for sequences, i.e. combining the scores or as...

MOTIVATION Secondary-Structure Guided Superposition tool (SSGS) is a permissive secondary structure-based algorithm for matching of protein structures and in particular their fragments. The algorithm was developed towards protein structure prediction via fragment assembly. RESULTS In a fragment-based structural prediction scheme, a protein sequence is cut into building blocks (BBs). The BBs a...

Large-scale sequencing projects produce an exploding number of known protein sequences. The current number is about 36,000 [Bairoch & Boeckmann, 92] sequences, but before the end of the century many more than 100,000 will have to be dealt with. This is in contrast to the far slower increase in the number of known protein structures, currently about 2,000 [Berstein et al., 77]. The rate of incre...

MOTIVATION The Monte Carlo fragment insertion method for protein tertiary structure prediction (ROSETTA) of Baker and others, has been merged with the I-SITES library of sequence structure motifs and the HMMSTR model for local structure in proteins, to form a new public server for the ab initio prediction of protein structure. The server performs several tasks in addition to tertiary structure ...

In this unit, protocols are provided for predicting RNA secondary structure with the user-friendly RNAstructure desktop computer program and the RNAstructure Web server. The minimum free energy structure and a set of suboptimal structures with similar free energies are predicted. Prediction of high-affinity oligonucleotide binding sites to a structured RNA target is also presented. © 2016 by Jo...

Protein secondary structure prediction has been satisfactorily performed by machine learning techniques such as support vector machines (SVM’s). We discuss a special technique to include hyrophobicity information to further improve the classification results. Hydrophobicity or hydrophobic moment measure of each amino acid is included within a given window length in the protein secondary structu...

The structure and function of proteins are closely related, and protein structure decides its function, therefore protein structure prediction is quite important. β-turns are important components of protein secondary structure. So development of an accurate prediction method of β-turn types is very necessary. In this paper, we used the composite vector with position conservation scoring functio...