| Texto completo | |
| Autor(es): |
Alcantara, Leonardo U.
;
Triguero, Isaac
;
Cerri, Ricardo
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | INTELLIGENT SYSTEMS, BRACIS 2024, PT II; v. 15413, p. 16-pg., 2025-01-01. |
| Resumo | |
Protein subcellular localization is an important classification task because the location of proteins in a cell is directly linked to their functions. Since a protein can act at two or more locations simultaneously, multi-label classification algorithms are necessary. The currently used algorithms are usually based on supervised learning, which presents some disadvantages such as (i) a need for a large amount of labeled instances for training; (ii) a waste of valuable information that labeled instances can provide; and (iii) a high cost involved in obtaining labeled instances for training. To overcome these disadvantages, semi-supervised learning can be applied, where classifiers exploit both labeled and unlabeled data. Thus, in this paper, we propose a new semi-supervised algorithm for multi-label protein subcellular localization. Our proposal is based on decision tree classifiers induced using predictive clustering trees. We investigate many semi-supervised protein subcellular localization scenarios to test whether unlabeled instances can improve the multi-label classification process. Our results show that the proposal can achieve competitive or better results when compared to the pure supervised version of the predictive clustering trees. (AU) | |
| Processo FAPESP: | 16/25220-1 - Aprendizado de Maquina Multirrótulo para Localização Subcelular de Proteínas |
| Beneficiário: | Leonardo Utida Alcântara |
| Modalidade de apoio: | Bolsas no Brasil - Iniciação Científica |
| Processo FAPESP: | 22/02981-8 - Detecção de novidade em fluxos contínuos de dados multirrótulo |
| Beneficiário: | Ricardo Cerri |
| Modalidade de apoio: | Auxílio à Pesquisa - Projeto Inicial |
| Processo FAPESP: | 17/24807-1 - Aprendizado ativo para localização subcelular de proteínas |
| Beneficiário: | Leonardo Utida Alcântara |
| Modalidade de apoio: | Bolsas no Exterior - Estágio de Pesquisa - Iniciação Científica |