AlphaFold and the future of structural biology.

Read, Randy J; Baker, Edward N; Bond, Charles S; Garman, Elspeth F; van Raaij, Mark J

Read, Randy J; Baker, Edward N; Bond, Charles S; Garman, Elspeth F; van Raaij, Mark J.

Afiliación

Read RJ; Cambridge Institute for Medical Research, University of Cambridge, The Keith Peters Building, Hills Road, Cambridge CB2 0XY, United Kingdom.
Baker EN; School of Biological Sciences, University of Auckland, Auckland, New Zealand.
Bond CS; School of Molecular Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.
Garman EF; Department of Biochemistry, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, United Kingdom.
van Raaij MJ; Departamento de Estructura de Macromoleculas, Centro Nacional de Biotecnologia, Consejo Superior de Investigaciones Cientificas, 28049 Madrid, Spain.

IUCrJ ; 10(Pt 4): 377-379, 2023 Jul 01.

Article en En | MEDLINE | ID: mdl-37358477

ABSTRACT

ABSTRACT

This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.

Asunto(s)

Biología; Aprendizaje Automático; Microscopía por Crioelectrón; Cristalografía por Rayos X

Palabras clave

AlphaFold; cryo-EM; crystallography; protein structure prediction

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología / Aprendizaje Automático Idioma: En Revista: IUCrJ Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google