Infrared: a declarative tree decomposition-powered framework for bioinformatics

Motivation Many bioinformatics problems can be approached as optimization or controlled sampling tasks, and solved exactly and efficiently using Dynamic Programming (DP). However, such exact methods are typically tailored towards specific settings, complex to develop, and hard to implement and adapt...

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Veröffentlicht in:	Algorithms for molecular biology Jg. 19; H. 1; S. 13 - 29
Hauptverfasser:	Yao, Hua-Ting, Marchand, Bertrand, Berkemer, Sarah J., Ponty, Yann, Will, Sebastian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 16.03.2024 Springer Nature B.V BMC
Schlagworte:	Algorithms Availability Bioinformatics Biomedical and Life Sciences Boltzmann sampling Cellular and Medical Topics Cognitive science Computational Biology/Bioinformatics Computer Science Constraint modelling Decomposition Dynamic programming Expected values Fixed-parameter tractable algorithms Graph coloring Heuristic Life Sciences Linear programming Network phylogeny Networks Nucleotide sequence Optimization Phylogeny Physiological RNA sequence design Sampling Tree decomposition Variables RNA sequence design Pseudoknots Network phylogeny Fixed-parameter tractable algorithms Boltzmann sampling Tree decomposition Bioinformatics RNA alignment Bioinformatics Fixed-parameter tractable algorithms Tree decomposition Boltzmann sampling Network phylogeny RNA sequence design RNA alignment Pseudoknots
ISSN:	1748-7188, 1748-7188
Online-Zugang:	Volltext
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