Metabolic pathways synthesis based on ant colony optimization

A current challenge in bioinformatics is to discover how to transform particular compounds into specific products. Typically, the common approach is finding the sequence of reactions that relate the specified substrate (source) and product (target) using classical searching algorithms. However, thos...

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Detalles Bibliográficos
Autores principales: Gerard, M. F., Stegmayer Machado, Georgina S., Milone, Diego H.
Formato: Objeto de conferencia Resumen
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Informáticas
Colony-based algorithm
PhDSeeker
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/87828
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-87828
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Colony-based algorithm
PhDSeeker
spellingShingle Ciencias Informáticas
Colony-based algorithm
PhDSeeker
Gerard, M. F.
Stegmayer Machado, Georgina S.
Milone, Diego H.
Metabolic pathways synthesis based on ant colony optimization
topic_facet Ciencias Informáticas
Colony-based algorithm
PhDSeeker
description A current challenge in bioinformatics is to discover how to transform particular compounds into specific products. Typically, the common approach is finding the sequence of reactions that relate the specified substrate (source) and product (target) using classical searching algorithms. However, those methods have three main limitations: difficulty in handling large amounts of reactions and compounds; absence of a step that verifies the availability of substrates; and inability to find branched pathways. In [1], we propose a novel ant colony-based algorithm for metabolic pathways synthesis. This algorithm, named Pheromone-Directed Seeker (PhDSeeker), is able to relate several compounds simultaneously by emulating the behavior of real ants while seeking a path between their colony and a source of food. The process is designed to ensure the availability of substrates for every reaction in the solution. Thus, ants explore the set of reactions on each iteration searching for possible pathways to link the compounds. After that, they share information about solutions found by each one and then perform a new search. This process is guided by a cost function that evaluates the availability of substrates, the connection between source and target, and the pathway size.
format Objeto de conferencia
Resumen
author Gerard, M. F.
Stegmayer Machado, Georgina S.
Milone, Diego H.
author_facet Gerard, M. F.
Stegmayer Machado, Georgina S.
Milone, Diego H.
author_sort Gerard, M. F.
title Metabolic pathways synthesis based on ant colony optimization
title_short Metabolic pathways synthesis based on ant colony optimization
title_full Metabolic pathways synthesis based on ant colony optimization
title_fullStr Metabolic pathways synthesis based on ant colony optimization
title_full_unstemmed Metabolic pathways synthesis based on ant colony optimization
title_sort metabolic pathways synthesis based on ant colony optimization
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/87828
work_keys_str_mv AT gerardmf metabolicpathwayssynthesisbasedonantcolonyoptimization
AT stegmayermachadogeorginas metabolicpathwayssynthesisbasedonantcolonyoptimization
AT milonediegoh metabolicpathwayssynthesisbasedonantcolonyoptimization
bdutipo_str Repositorios
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