Chemical reaction networks and opportunities for machine learning.
Nat Comput Sci
; 3(1): 12-24, 2023 Jan.
Article
en En
| MEDLINE
| ID: mdl-38177958
ABSTRACT
Chemical reaction networks (CRNs), defined by sets of species and possible reactions between them, are widely used to interrogate chemical systems. To capture increasingly complex phenomena, CRNs can be leveraged alongside data-driven methods and machine learning (ML). In this Perspective, we assess the diverse strategies available for CRN construction and analysis in pursuit of a wide range of scientific goals, discuss ML techniques currently being applied to CRNs and outline future CRN-ML approaches, presenting scientific and technical challenges to overcome.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Nat Comput Sci
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos