Publications
Detailed Information
Novel machine learning approaches revolutionize protein knowledge
Cited 15 time in
Web of Science
Cited 18 time in Scopus
- Authors
- Issue Date
- 2023-04
- Publisher
- Elsevier BV
- Citation
- Trends in Biochemical Sciences, Vol.48 No.4, pp.345-359
- Abstract
- Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models of proteins and annotating their functions on a large scale is no longer limited by time and resources. The most recent method to be top ranked by the Critical Assessment of Structure Prediction (CASP) assessment, AlphaFold 2 (AF2), is capable of building structural models with an accuracy comparable to that of experimental structures. Annotations of 3D models are keeping pace with the deposition of the structures due to advance-ments in protein language models (pLMs) and structural aligners that help vali-date these transferred annotations. In this review we describe how recent developments in ML for protein science are making large-scale structural bioin-formatics available to the general scientific community.
- ISSN
- 0968-0004
- Files in This Item:
- There are no files associated with this item.
- Appears in Collections:
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.