Hidden Markov models and the Viterbi algorithm applied to integrated bioinformatics analyses of putative flagellar actin-interacting proteins in Leishmania spp.
by Ana Carolina L. Pacheco, Fabiana F. Araujo, Michel T. Kamimura, Samara C. Silva, Michely C. Diniz, Fatima De Cassia E. Oliveira, Raimundo Araujo Filho, Marcilia P. Costa, Diana M. Oliveira
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 1, No. 4, 2009

Abstract: For performing vital cellular processes, such as motility, eukaryotic cells rely on the actin cytoskeleton, whose structure and dynamics are tightly controlled by a large number of actin-interacting proteins (AIPs). Actin can determine cell stiffness and transmit force during mechanotransduction, cytokinesis, cell motility and other cellular shape changes, while the identification and analyses of AIPs can help to improve understanding of their mechanical properties on physiological/pathological architectures. In this work we employ bioinformatics tools in some refined pattern recognition techniques (such as hidden Markov models (HMMs) through the Viterbi algorithm/path) in order to improve the recognition of actin-binding/interacting activity through identification of AIPs in genomes, transcriptomes and proteomes of the flagellated protozoan Leishmania. We report our in silico analyses on cofilin and twinfilin, here predicted as flagellar proteins, a direct bioinformatics contribution in the secondary annotation of Leishmania genomes.

Online publication date: Fri, 18-Sep-2009

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