Evidence map›Paper›PMID 34757056›Full record

ReviewJournal of molecular biology2022

The AlphaFold Database of Protein Structures: A Biologist's Guide.

Alessia David, Suhail Islam, Evgeny Tankhilevich, Michael J E Sternberg

Abstract readReview
In one paragraph

Review in Journal of molecular biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

118 citing papers in PubMed.

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  10. Cancer-associated TRF1 mutations alter PARP1 interaction dynamics: an in silico study.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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  11. Review
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58 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alessia DavidCentre for Integrative System Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK. Electronic address: alessia.david09@imperial.ac.uk.
Suhail IslamCentre for Integrative System Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.
Evgeny TankhilevichCentre for Integrative System Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.
Michael J E SternbergCentre for Integrative System Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/M011178/1Wellcome Trust 218242/Z/19/Z
6 · The paper itself

Abstract

AlphaFold, the deep learning algorithm developed by DeepMind, recently released the three-dimensional models of the whole human proteome to the scientific community. Here we discuss the advantages, limitations and the still unsolved challenges of the AlphaFold models from the perspective of a biologist, who may not be an expert in structural biology.

Indexed as

Deep LearningProtein ConformationProtein FoldingAlgorithmsComputational BiologyDatabases, FactualHumansModels, MolecularMolecular BiologyProteomeProteomeAlphaFoldhuman proteomeinter-domain accuracythree-dimensional model

Identifiers

PMID34757056
PMCPMC8783046

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.