title: Generalized Baum-Welch algorithm based on the similarity between sequences.
abstract: The profile hidden Markov model (PHMM) is widely used to assign the protein sequences to their respective families. A major limitation of a PHMM is the assumption that given states the observations (amino acids) are independent. To overcome this limitation, the dependency between amino acids in a multiple sequence alignment (MSA) which is the representative of a PHMM can be appended to the PHMM. Due to the fact that with a MSA, the sequences of amino acids are biologically related, the one-by-one dependency between two amino acids can be considered. In other words, based on the MSA, the dependency between an amino acid and its corresponding amino acid located above can be combined with the PHMM. For this purpose, the new emission probability matrix which considers the one-by-one dependencies between amino acids is constructed. The parameters of a PHMM are of two types; transition and emission probabilities which are usually estimated using an EM algorithm called the Baum-Welch algorithm. We have generalized the Baum-Welch algorithm using similarity emission matrix constructed by integrating the new emission probability matrix with the common emission probability matrix. Then, the performance of similarity emission is discussed by applying it to the top twenty protein families in the Pfam database. We show that using the similarity emission in the Baum-Welch algorithm significantly outperforms the common Baum-Welch algorithm in the task of assigning protein sequences to protein families.
authors.affiliation: Department of Mathematics and Statistics, Faculty of Financial Science, University of Economic Sciences, Tehran, Iran ; School of Computer Science, Institute for Research in Fundamental Science (IPM), Tehran, Iran.
authors.forename: Vahid
authors.initials: V
authors.lastname: Rezaei
authors.affiliation: School of Computer Science, Institute for Research in Fundamental Science (IPM), Tehran, Iran ; School of Mathematics, Statistics and Computer Science, University of Tehran, Iran.
authors.forename: Hamid
authors.initials: H
authors.lastname: Pezeshk
authors.affiliation: Computer Science Department, Catholic University of Murcia (UCAM), Murcia, Spain.
authors.forename: Horacio
authors.initials: H
authors.lastname: Pérez-Sa'nchez
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid