AMBIENTUM BIOETHICA BIOLOGIA CHEMIA DIGITALIA DRAMATICA EDUCATIO ARTIS GYMNAST. ENGINEERING EPHEMERIDES EUROPAEA GEOGRAPHIA GEOLOGIA HISTORIA HISTORIA ARTIUM INFORMATICA IURISPRUDENTIA MATHEMATICA MUSICA NEGOTIA OECONOMICA PHILOLOGIA PHILOSOPHIA PHYSICA POLITICA PSYCHOLOGIA-PAEDAGOGIA SOCIOLOGIA THEOLOGIA CATHOLICA THEOLOGIA CATHOLICA LATIN THEOLOGIA GR.-CATH. VARAD THEOLOGIA ORTHODOXA THEOLOGIA REF. TRANSYLVAN
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STUDIA INFORMATICA - Ediţia nr.2 din 2014 | |||||||
Articol: |
ON REINFORCEMENT LEARNING BASED MULTIPLE SEQUENCE ALIGNMENT. Autori: . |
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Rezumat:
Multiple alignment of biological sequences may reveal important functional, structural or evolutionary relationships between the sequences. Although very important from a biological perspective, the problem of multiple sequence alignment is quite challenging from a computational point of view, as it is NP-complete. Reinforcement learning is an approach to machine intelligence in which an adaptive system can learn to behave in a certain way by receiving punishments or rewards for its chosen actions. In this paper we investigate a reinforcement learning based model for the multiple sequence alignment problem, which combines a Q-learning algorithm with two variations of a sequence alignment algorithm and three different action selection policies. The model is experimentally evaluated on two data sets containing mitochondrial human DNA sequences from remains collected during several archeological excavations. The obtained results for each algorithmic combination are analysed and we provide comparisons of these results. 2010 Mathematics Subject Classification. 68P15, 68T05.1998 CR Categories and Descriptors. I.2.6[Computing Methodologies]: Articial Intelligence - Learning; I.2.8[Computing Methodologies]: Problem Solving, Control Methods, and Search - Heuristic methods. Key words and phrases. Bioinformatics, Multiple sequence alignment, Reinforcement learning.
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