A flexible motif search technique based on generalized profiles.
A flexible motif search technique is presented which has two major components: (1) a generalized profile syntax serving as a motif definition language; and (2) a motif search method specifically adapted to the problem of finding multiple instances of a motif in the same sequence. The new profile structure, which is the core of the generalized profile syntax, combines the functions of a variety of motif descriptors implemented in other methods, including regular expression-like patterns, weight matrices, previously used profiles, and certain types of hidden Markov models (HMMs). The relationship between generalized profiles and other biomolecular motif descriptors is analyzed in detail, with special attention to HMMs. Generalized profiles are shown to be equivalent to a particular class of HMMs, and conversion procedures in both directions are given. The conversion procedures provide an interpretation for local alignment in the framework of stochastic models, allowing for clear, simple significance tests. A mathematical statement of the motif search problem defines the new method exactly without linking it to a specific algorithmic solution. Part of the definition includes a new definition of disjointness of alignments.
Bucher
P
P
Swiss Institute for Experimental Cancer Research, Epalinges, Switzerland.
Karplus
K
K
Moeri
N
N
Hofmann
K
K
D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D016384:Consensus Sequence / Q000235:genetics; D016678:Genome; D005914:Globins / Q000737:chemistry; D008390:Markov Chains; D008969:Molecular Sequence Data; D017475:Receptors, Nerve Growth Factor / Q000235:genetics; D018124:Receptors, Tumor Necrosis Factor / Q000235:genetics; D017421:Sequence Analysis; D012984:Software
D017475:Receptors, Nerve Growth Factor; D018124:Receptors, Tumor Necrosis Factor; D005914:Globins