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Gearoid Fox

dblp:141/5370 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

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

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › multiple sequence alignment › alignment quality assessment
alignment benchmark
0.212016
Using de novo protein structure predictions to measure the quality of very large multiple sequence alignments · Bioinform. 2016
Bioinformatics and computational biology
multiple sequence alignment
0.212016
Using de novo protein structure predictions to measure the quality of very large multiple sequence alignments · Bioinform. 2016
Bioinformatics and computational biology
protein structure prediction
0.212016
Using de novo protein structure predictions to measure the quality of very large multiple sequence alignments · Bioinform. 2016

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

de novo protein structure prediction · 0.2chained guide trees · 0.2
YearPublicationVenuePosition
2016 Using de novo protein structure predictions to measure the quality of very large multiple sequence alignments
abstract
MOTIVATION: Multiple sequence alignments (MSAs) with large numbers of sequences are now commonplace. However, current multiple alignment benchmarks are ill-suited for testing these types of alignments, as test cases either contain a very small number of sequences or are based purely on simulation rather than empirical data. RESULTS: We take advantage of recent developments in protein structure prediction methods to create a benchmark (ContTest) for protein MSAs containing many thousands of sequences in each test case and which is based on empirical biological data. We rank popular MSA methods using this benchmark and verify a recent result showing that chained guide trees increase the accuracy of progressive alignment packages on datasets with thousands of proteins. AVAILABILITY AND IMPLEMENTATION: Benchmark data and scripts are available for download at http://www.bioinf.ucd.ie/download/ContTest.tar.gz CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Gearoid Fox, Fabian Sievers, Desmond G. Higgins
Bioinform.1