PScL-2LSAESM: bioimage-based prediction of protein subcellular localization by integrating heterogeneous features with the two-level SAE-SM and mean ensemble method

MOTIVATION: Over the past decades, a variety of in silico methods have been developed to predict protein subcellular localization within cells. However, a common and major challenge in the design and development of such methods is how to effectively utilize the heterogeneous feature sets extracted f...

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Detalles Bibliográficos
Autores principales: Ullah, Matee, Hadi, Fazal, Song, Jiangning, Yu, Dong-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947927/
https://www.ncbi.nlm.nih.gov/pubmed/36413068
http://dx.doi.org/10.1093/bioinformatics/btac727

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947927/
https://www.ncbi.nlm.nih.gov/pubmed/36413068
http://dx.doi.org/10.1093/bioinformatics/btac727

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