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Nicholas S. Edmunds

dblp:354/2982 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein structure prediction
model quality assessment
0.812024
Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes · Bioinform. 2024
Bioinformatics and computational biology
protein structure prediction
0.812024
Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes · Bioinform. 2024

Methods — techniques the papers use, named apart from their topics

plDDT · 0.8pTM · 0.8lDDT · 0.8TM-score · 0.8
YearPublicationVenuePosition
2024 Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes
abstract
MOTIVATION: Despite an increase in protein modelling accuracy following the development of AlphaFold2, there remains an accuracy gap between predicted and observed model quality assessment (MQA) scores. In CASP15, variations in AlphaFold2 model accuracy prediction were noticed for quaternary models of very similar observed quality. In this study, we compare plDDT and pTM to their observed counterparts the local distance difference test (lDDT) and TM-score for both tertiary and quaternary models to examine whether reliability is retained across the scoring range under normal modelling conditions and in situations where AlphaFold2 functionality is customized. We also explore plDDT and pTM ranking accuracy in comparison with the published independent MQA programmes ModFOLD9 and ModFOLDdock. RESULTS: plDDT was found to be an accurate descriptor of tertiary model quality compared to observed lDDT-Cα scores (Pearson r = 0.97), and achieved a ranking agreement true positive rate (TPR) of 0.34 with observed scores, which ModFOLD9 could not improve. However, quaternary structure accuracy was reduced (plDDT r = 0.67, pTM r = 0.70) and significant overprediction was seen with both scores for some lower quality models. Additionally, ModFOLDdock was able to improve upon AF2-Multimer model ranking compared to TM-score (TPR 0.34) and oligo-lDDT score (TPR 0.43). Finally, evidence is presented for increased variability in plDDT and pTM when using custom template recycling, which is more pronounced for quaternary structures. AVAILABILITY AND IMPLEMENTATION: The ModFOLD9 and ModFOLDdock quality assessment servers are available at https://www.reading.ac.uk/bioinf/ModFOLD/ and https://www.reading.ac.uk/bioinf/ModFOLDdock/, respectively. A docker image is available at https://hub.docker.com/r/mcguffin/multifold.
Nicholas S. Edmunds, Ahmet G. Genc, Liam J. McGuffin
Bioinform.1