Co-evolution based machine-learning for predicting functional interactions between human genes
With the rise in number of eukaryotic species being fully sequenced, large scale phylogenetic profiling can give insights on gene function, Here, the authors describe a machine-learning approach that integrates co-evolution across eukaryotic clades to predict gene function and functional interaction...
Guardado en:
Autores principales: | Doron Stupp, Elad Sharon, Idit Bloch, Marinka Zitnik, Or Zuk, Yuval Tabach |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/59ff6a7933cf40ff80afbe2c5b1265df |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Robust seed germination prediction using deep learning and RGB image data
por: Yuval Nehoshtan, et al.
Publicado: (2021) -
A machine learning framework for predicting drug–drug interactions
por: Suyu Mei, et al.
Publicado: (2021) -
Prioritizing network communities
por: Marinka Zitnik, et al.
Publicado: (2018) -
Identification of disease treatment mechanisms through the multiscale interactome
por: Camilo Ruiz, et al.
Publicado: (2021) -
Publisher Correction: A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes
por: Frédéric Cadet, et al.
Publicado: (2021)