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Applying inspired algorithms for nature to classification of depolymerase enzyme used in biofuel production

Grant number: 15/06780-3
Support type:Scholarships in Brazil - Master
Effective date (Start): June 01, 2015
Effective date (End): February 29, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Fabricio Aparecido Breve
Grantee:Diego Henrique Negretto
Home Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
Associated research grant:11/17396-9 - Machine learning using models inspired by nature, AP.JP

Abstract

The production, exploitation and use of certain liquid fuels, such as petroleum products, has led to a depletion of non-renewable resources and may cause serious environmental problems. Thus, the search for ways to produce biofuels through abundant and renewable sources, such as the depolymerases enzymes present in microorganisms, is of great importance. Research in this field, generates massive amount of biological data, and consequently, the data analysis becomes increasingly non-trivial, thus requiring the use of computer solutions. The use of machine learning, allows classification of data from an automatic way and is useful in situations where domain experts are able to accomplish this task, but can not describe the heuristics used. Thus, it is intended with this project, apply algorithms inspired by nature for the classification of data on enzymes des polymerase related to biofuel production in their respective enzyme complexes.

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
NEGRETTO, Diego Henrique. Algoritmos de aprendizado semi-supervisionado baseados em grafos aplicados na bioinformática. 2016. 105 f. Master's Dissertation - Universidade Estadual Paulista "Júlio de Mesquita Filho" Instituto de Biociências, Letras e Ciências Exatas..

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