MOTIVATION As more genomes are sequenced, the demand for fast gene classification techniques is increasing. To analyze a newly sequenced genome, first the genes are identified and translated into amino acid sequences which are then classified into structural or functional classes. The best-performing protein classification methods are based on protein homology detection using sequence alignment...

This paper describes an approach to data-driven discovery of decision trees or rules for assigning protein sequences to functional families using sequence motifs. This method is able to capture regularities that can be described in terms of presence or absence of arbitrary combinations of motifs. A training set of peptidase sequences labeled with the corresponding MEROPS functional families or ...

MOTIVATION Biologists frequently align multiple biological sequences to determine consensus sequences and/or search for predominant residues and conserved regions. Particularly, determining conserved regions in an alignment is one of the most important activities. Since protein sequences are often several-hundred residues or longer, it is difficult to distinguish biologically important conserve...

Large-scale automatic annotation of protein sequences remains challenging in postgenomics era. E1DS is designed for annotating enzyme sequences based on a repository of 1D signatures. The employed sequence signatures are derived using a novel pattern mining approach that discovers long motifs consisted of several sequential blocks (conserved segments). Each of the sequential blocks is considera...

In this thesis we have developed novel methods for analyzing biological data, the primary sequences of the DNA and proteins, the microarray based gene expression data, and other functional genomics data. The main contribution is the development of the pattern discovery algorithm SPEXS, accompanied by several practical applications for analyzing real biological problems. For performing these bio...

Regular expression pattern matching is widely used in computational biology. Searching through a database of sequences for a motif (a simple regular expression), or its variations is an important interactive process which requires fast motif-matching algorithms. In this paper, we explore and evaluate various representations of the database of sequences using suffix trees for two types of query ...

UNLABELLED We present the development of a Comprehensive database of 12 076 invariant Peptide Signatures (CoPS) derived from 52 bacterial genomes with a minimum occurrence in at least seven organisms. These peptides were observed in functionally similar proteins and are distributed over nearly 1250 different functional proteins. The database provides function, structure and occurrence in bioche...

We have examined conserved protein motifs in the non-coding, intergenic regions ("pseudomotif patterns") and surveyed their occurrence in the fly, worm, yeast and human genomes (chromosomes 21 and 22 only). To identify these patterns, we masked out annotated genes, pseudogenes and repeat regions from the raw genomic sequence and then compared the remaining sequence, in six-frame translation, ag...

The aim of this work is to use a supervised learning approach to identify sets of motif-based sequence characteristics, combinations of which can give the most accurate annotation of new proteins. We assess several of InterPro Consortium member databases for their informativeness for the annotation of full-length protein sequences. Thus, our study addresses the problem of integrating biological...