Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Kristian A. Gray

dblp:124/1003 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-7035-7107ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
cancer genomics
0.112007
AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes · Bioinform. 2007
Bioinformatics and computational biology › cancer genomics › somatic mutation analysis
somatic variant detection
0.112007
AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes · Bioinform. 2007

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

mutation detection algorithm · 0.1
YearPublicationVenuePosition
2021 Updates to HCOP: the HGNC comparison of orthology predictions tool
abstract
Multiple resources currently exist that predict orthologous relationships between genes. These resources differ both in the methodologies used and in the species they make predictions for. The HGNC Comparison of Orthology Predictions (HCOP) search tool integrates and displays data from multiple ortholog prediction resources for a specified human gene or set of genes. An indication of the reliability of a prediction is provided by the number of resources that support it. HCOP was originally designed to show orthology predictions between human and mouse but has been expanded to include data from a current total of 20 selected vertebrate and model organism species. The HCOP pipeline used to fetch and integrate the information from the disparate ortholog and nomenclature data resources has recently been rewritten, both to enable the inclusion of new data and to take advantage of modern web technologies. Data from HCOP are used extensively in our work naming genes as the Vertebrate Gene Nomenclature Committee (https://vertebrate.genenames.org).
Bethan Yates, Kristian A. Gray, Tamsin E. M. Jones, Elspeth A. Bruford
Briefings Bioinform.2
2007 AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes
abstract
UNLABELLED: The undertaking of large-scale DNA sequencing screens for somatic variants in human cancers requires accurate and rapid processing of traces for variants. Due to their often aneuploid nature and admixed normal tissue, heterozygous variants found in primary cancers are often subtle and difficult to detect. To address these issues, we have developed a mutation detection algorithm, AutoCSA, specifically optimized for the high throughput screening of cancer samples. AVAILABILITY: http://www.sanger.ac.uk/genetics/CGP/Software/AutoCSA.
Ed Dicks, Jon W. Teague, Philip Stephens, Keiran Raine, Andy Yates, C. Mattocks, P. Tarpey, Adam P. Butler, Andrew Menzies, Andrew M. Jenkinson, Helen Davies, Sarah Edkins, Simon A. Forbes, Kristian A. Gray, Christopher Greenman, Rebecca Shepherd, Michael R. Stratton, P. Andrew Futreal, Richard Wooster
Bioinform.15