Cargando…
Using Multi-Instance Hierarchical Clustering Learning System to Predict Yeast Gene Function
Time-course gene expression datasets, which record continuous biological processes of genes, have recently been used to predict gene function. However, only few positive genes can be obtained from annotation databases, such as gene ontology (GO). To obtain more useful information and effectively pre...
Autores principales: | Liao, Bo, Li, Yun, Jiang, Yan, Cai, Lijun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951281/ https://www.ncbi.nlm.nih.gov/pubmed/24621610 http://dx.doi.org/10.1371/journal.pone.0090962 |
Ejemplares similares
-
Gene function prediction based on combining gene ontology hierarchy with multi-instance multi-label learning
por: Li, Zejun, et al.
Publicado: (2018) -
Multi-Instance Multilabel Learning with Weak-Label for Predicting Protein Function in Electricigens
por: Wu, Jian-Sheng, et al.
Publicado: (2015) -
Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction
por: Xu, Yonghui, et al.
Publicado: (2017) -
Enhancing unsupervised medical entity linking with multi-instance learning
por: Yan, Cheng, et al.
Publicado: (2021) -
Multi-instance learning of graph neural networks for aqueous pK(a) prediction
por: Xiong, Jiacheng, et al.
Publicado: (2021)