dorsal/arxiv
View SchemaProbabilistic sequence alignments: realistic models with efficient algorithms
| Authors | E. Yeramian, E. Debonneuil |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0606010 |
| URL | https://arxiv.org/abs/q-bio/0606010 |
| DOI | 10.1103/PhysRevLett.98.078101 |
Abstract
Alignment algorithms usually rely on simplified models of gaps for computational efficiency. Based on an isomorphism between alignments and physical helix-coil models, we show in statistical mechanics that alignments with realistic laws for gaps can be computed with fast algorithms. Improved performances of probabilistic alignments with realistic models of gaps are illustrated. Probabilistic and optimization formulations are compared, with potential implications in many fields and perspectives for computationally efficient extensions to Markov models with realistic long-range interactions.
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"abstract": "Alignment algorithms usually rely on simplified models of gaps for\ncomputational efficiency. Based on an isomorphism between alignments and\nphysical helix-coil models, we show in statistical mechanics that alignments\nwith realistic laws for gaps can be computed with fast algorithms. Improved\nperformances of probabilistic alignments with realistic models of gaps are\nillustrated. Probabilistic and optimization formulations are compared, with\npotential implications in many fields and perspectives for computationally\nefficient extensions to Markov models with realistic long-range interactions.",
"arxiv_id": "q-bio/0606010",
"authors": [
"E. Yeramian",
"E. Debonneuil"
],
"categories": [
"q-bio.GN",
"cond-mat.dis-nn",
"cond-mat.stat-mech",
"physics.bio-ph",
"physics.comp-ph"
],
"doi": "10.1103/PhysRevLett.98.078101",
"title": "Probabilistic sequence alignments: realistic models with efficient algorithms",
"url": "https://arxiv.org/abs/q-bio/0606010"
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