Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers

Background: The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered sev...

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Detalhes bibliográficos
Autor principal: Galpert D. (author)
Outros Autores: Fernández A. (author), Herrera F. (author), Antunes A. (author), Molina-Ruiz R. (author), Agüero-Chapin G. (author)
Formato: article
Idioma:eng
Publicado em: 2018
Assuntos:
Alignment
Classification (of information)
Decision trees
Feature extraction
Forestry
Proteins
Yeast
Amino acid compositions
Classification approach
Classification performance
Classification quality
Imbalance datum
Orthologs
Similarity measure
Supervised classification
Big data
proteome
Saccharomyces cerevisiae protein
algorithm
decision tree
metabolism
procedures
protein database
Saccharomyces cerevisiae
sequence analysis
Algorithms
Databases, Protein
Decision Trees
Proteome
Saccharomyces cerevisiae Proteins
Sequence Analysis, Protein
Texto completo:https://hdl.handle.net/10216/120462
País:Portugal
Oai:oai:repositorio-aberto.up.pt:10216/120462

Texto Completo

https://hdl.handle.net/10216/120462

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