D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions.

Sledzieski, Samuel; Singh, Rohit; Cowen, Lenore; Berger, Bonnie

Sledzieski, Samuel; Singh, Rohit; Cowen, Lenore; Berger, Bonnie.

Afiliação

Sledzieski S; Computer Science and Artificial Intelligence Lab., Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Singh R; Computer Science and Artificial Intelligence Lab., Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Cowen L; Department of Computer Science, Tufts University, Medford, MA 02155, USA. Electronic address: cowen@cs.tufts.edu.
Berger B; Computer Science and Artificial Intelligence Lab., Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: bab@mit.edu.

Cell Syst ; 12(10): 969-982.e6, 2021 10 20.

Article em En | MEDLINE | ID: mdl-34536380

Assuntos

Fenômica; Proteínas; Animais; Bovinos; Proteínas/metabolismo

Palavras-chave

cow rumen; deep learning; embedding; function prediction; genome to phenome; interpretability; language models; metabolism; module detection; protein-protein interaction

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Fenômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Fenômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article