Cargando…
OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features
Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. The reason being, effective targets have disease-relevant biological functions, and omics data unveil the protein...
Autores principales: | Thafar, Maha A., Albaradei, Somayah, Uludag, Mahmut, Alshahrani, Mona, Gojobori, Takashi, Essack, Magbubah, Gao, Xin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117673/ https://www.ncbi.nlm.nih.gov/pubmed/37091791 http://dx.doi.org/10.3389/fgene.2023.1139626 |
Ejemplares similares
-
Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models
por: Albaradei, Somayah, et al.
Publicado: (2021) -
MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data
por: Albaradei, Somayah, et al.
Publicado: (2022) -
Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning
por: Thafar, Maha A., et al.
Publicado: (2022) -
MetaCancer: A deep learning-based pan-cancer metastasis prediction model developed using multi-omics data
por: Albaradei, Somayah, et al.
Publicado: (2021) -
Machine learning and deep learning methods that use omics data for metastasis prediction
por: Albaradei, Somayah, et al.
Publicado: (2021)