Cargando…
Mut2Vec: distributed representation of cancerous mutations
BACKGROUND: Embedding techniques for converting high-dimensional sparse data into low-dimensional distributed representations have been gaining popularity in various fields of research. In deep learning models, embedding is commonly used and proven to be more effective than naive binary representati...
Autores principales: | Kim, Sunkyu, Lee, Heewon, Kim, Keonwoo, Kang, Jaewoo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918431/ https://www.ncbi.nlm.nih.gov/pubmed/29697361 http://dx.doi.org/10.1186/s12920-018-0349-7 |
Ejemplares similares
-
Improved survival analysis by learning shared genomic information from pan-cancer data
por: Kim, Sunkyu, et al.
Publicado: (2020) -
Gene2vec: distributed representation of genes based on co-expression
por: Du, Jingcheng, et al.
Publicado: (2019) -
G2Vec: Distributed gene representations for identification of cancer prognostic genes
por: Choi, Jonghwan, et al.
Publicado: (2018) -
In silico drug combination discovery for personalized cancer therapy
por: Jeon, Minji, et al.
Publicado: (2018) -
Generating Mesh Representations of VecGeom Solids
por: Topak, Murat
Publicado: (2019)