Cargando…
An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species
Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles) are combined in a supervised pairwise ortholog detection app...
Autores principales: | Galpert, Deborah, del Río, Sara, Herrera, Francisco, Ancede-Gallardo, Evys, Antunes, Agostinho, Agüero-Chapin, Guillermin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4641943/ https://www.ncbi.nlm.nih.gov/pubmed/26605337 http://dx.doi.org/10.1155/2015/748681 |
Ejemplares similares
-
Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers
por: Galpert, Deborah, et al.
Publicado: (2018) -
Graph Theory-Based Sequence Descriptors as Remote Homology Predictors
por: Agüero-Chapin, Guillermin, et al.
Publicado: (2019) -
Emerging Computational Approaches for Antimicrobial Peptide Discovery
por: Agüero-Chapin, Guillermin, et al.
Publicado: (2022) -
A 2022 Update on Computational Approaches to the Discovery and Design of Antimicrobial Peptides
por: Agüero-Chapin, Guillermin, et al.
Publicado: (2023) -
An Impartial Semi-Supervised Learning Strategy for Imbalanced Classification on VHR Images
por: Sun, Fei, et al.
Publicado: (2020)