Improved performance of sequence search algorithms in remote homology detection

Improved performance of sequence search algorithms in remote homology detection

The protein sequence space is vast and diverse, spanning across different families. Biologically meaningful relationships exist between proteins at superfamily level. However, it is highly challenging to establish convincing relationships at the superfamily level by means of simple sequence searches. It is necessary to design a rigorous sequence search strategy to establish remote homology rela...

Remote Homology Detection Using Local Sequence-Structure Correlations

Remote homology detection refers to the problem of detecting protein homology in cases of low sequence similarity. Existing methods to establish homology relationships via sequence similarity do not work well for these remote homology. In this paper, we present a new method, SVM-HMMSTR, that overcomes the reliance on sequence similarity by taking into consideration the local structure similarit...

Improving Remote Homology Detection Using a Sequence Property

A Study of Remote Homology Detection

Functional annotation of newly sequenced genomes is an important challenge for computational biology systems. While much progress has been made towards scalingup experimental methods for functional assignment to putative genes, most current genomic annotation systems rely on computational solutions for homology modeling via sequence or structural similarity. We present a new method for remote h...

Remote Homology Detection of Protein Sequences

The automatic classification of protein sequences into families is of great help for the functional prediction and annotation of new proteins. In the paper we present a method called Irredundant Class that address the remote homology detection problem. The best performing methods that solve this problem are string kernels, that compute a similarity function between pairs of proteins based on th...