Analysis of phylogenetic profiles using Bayesian decomposition

G. Bidaut; K. Suhre; J. M. Claverie; M. F. Ochs

doi:10.1109/CSB.2003.1227380

Analysis of phylogenetic profiles using Bayesian decomposition

G. Bidaut, K. Suhre, J. M. Claverie, M. F. Ochs

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Antibiotic resistance together with the side effects of broad spectrum antibacterials make development of targeted antibiotics of great interest. To meet the problem of identifying potential targets specific to some genuses, a dataset comprising a series of phylogenetic profiles was built for a series of pathogenic bacteria of interest. The profiles are the highest BLAST scores for genes compared to selected genes of E. coli and M. tuberculosis. The dataset reflects the past evolution of those genes due to adaptation to specific niches, marked by lateral gene transfer, duplication and mutation of existing genes, or merging of existing genes. Genes that function together will be constrained to evolve together, to maintain viability in the organism. However, a given gene may have a role in multiple functional groups through the evolutionary process. Analysis using Bayesian decomposition helps to retrieve those relationships by retrieving fundamental patterns related to the evolutionary retained functions.

Original language	English (US)
Title of host publication	Proceedings of the 2003 IEEE Bioinformatics Conference, CSB 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	480-481
Number of pages	2
ISBN (Print)	0769520006, 9780769520001
DOIs	https://doi.org/10.1109/CSB.2003.1227380
State	Published - 2003
Externally published	Yes
Event	2nd International IEEE Computer Society Computational Systems Bioinformatics Conference, CSB 2003 - Stanford, United States Duration: Aug 11 2003 → Aug 14 2003

Other

Other	2nd International IEEE Computer Society Computational Systems Bioinformatics Conference, CSB 2003
Country/Territory	United States
City	Stanford
Period	8/11/03 → 8/14/03

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Science Applications

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10.1109/CSB.2003.1227380

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Bidaut, G, Suhre, K, Claverie, JM & Ochs, MF 2003, Analysis of phylogenetic profiles using Bayesian decomposition. in Proceedings of the 2003 IEEE Bioinformatics Conference, CSB 2003., 1227380, Institute of Electrical and Electronics Engineers Inc., pp. 480-481, 2nd International IEEE Computer Society Computational Systems Bioinformatics Conference, CSB 2003, Stanford, United States, 8/11/03. https://doi.org/10.1109/CSB.2003.1227380

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abstract = "Antibiotic resistance together with the side effects of broad spectrum antibacterials make development of targeted antibiotics of great interest. To meet the problem of identifying potential targets specific to some genuses, a dataset comprising a series of phylogenetic profiles was built for a series of pathogenic bacteria of interest. The profiles are the highest BLAST scores for genes compared to selected genes of E. coli and M. tuberculosis. The dataset reflects the past evolution of those genes due to adaptation to specific niches, marked by lateral gene transfer, duplication and mutation of existing genes, or merging of existing genes. Genes that function together will be constrained to evolve together, to maintain viability in the organism. However, a given gene may have a role in multiple functional groups through the evolutionary process. Analysis using Bayesian decomposition helps to retrieve those relationships by retrieving fundamental patterns related to the evolutionary retained functions.",

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AU - Suhre, K.

AU - Claverie, J. M.

AU - Ochs, M. F.

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N2 - Antibiotic resistance together with the side effects of broad spectrum antibacterials make development of targeted antibiotics of great interest. To meet the problem of identifying potential targets specific to some genuses, a dataset comprising a series of phylogenetic profiles was built for a series of pathogenic bacteria of interest. The profiles are the highest BLAST scores for genes compared to selected genes of E. coli and M. tuberculosis. The dataset reflects the past evolution of those genes due to adaptation to specific niches, marked by lateral gene transfer, duplication and mutation of existing genes, or merging of existing genes. Genes that function together will be constrained to evolve together, to maintain viability in the organism. However, a given gene may have a role in multiple functional groups through the evolutionary process. Analysis using Bayesian decomposition helps to retrieve those relationships by retrieving fundamental patterns related to the evolutionary retained functions.

AB - Antibiotic resistance together with the side effects of broad spectrum antibacterials make development of targeted antibiotics of great interest. To meet the problem of identifying potential targets specific to some genuses, a dataset comprising a series of phylogenetic profiles was built for a series of pathogenic bacteria of interest. The profiles are the highest BLAST scores for genes compared to selected genes of E. coli and M. tuberculosis. The dataset reflects the past evolution of those genes due to adaptation to specific niches, marked by lateral gene transfer, duplication and mutation of existing genes, or merging of existing genes. Genes that function together will be constrained to evolve together, to maintain viability in the organism. However, a given gene may have a role in multiple functional groups through the evolutionary process. Analysis using Bayesian decomposition helps to retrieve those relationships by retrieving fundamental patterns related to the evolutionary retained functions.

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Analysis of phylogenetic profiles using Bayesian decomposition

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