A Novel Approach to Remote Homology Detection: Jumping Alignments

We describe a new algorithm for protein classi cation and the detection of remote homologs. The rationale is to exploit both vertical and horizontal information of a multiple alignment in a well-balanced manner. This is in contrast to established methods such as proles and pro le hidden Markov models which focus on vertical information as they model the columns of the alignment independently and to family pairwise search which focuses on horizontal information as it treats given sequences separately. In our setting, we want to select from a given database of "candidate sequences" those proteins that belong to a given superfamily. In order to do so, each candidate sequence is separately tested against a multiple alignment of the known members of the superfamily by means of a new jumping alignment algorithm. This algorithm is an extension of the Smith-Waterman algorithm and computes a local alignment of a single sequence and a multiple alignment. In contrast to traditional met...

• Type: Journal
• Year: 2002
• Where: JCB
• Authors: Rainer Spang, Marc Rehmsmeier, Jens Stoye
• Keywords: Candidate Sequence, JCB 2002, Multiple Alignment, Protein Classi Cation