D
Derrick W. Crook
Researcher at University of Oxford
Publications - 510
Citations - 38699
Derrick W. Crook is an academic researcher from University of Oxford. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 92, co-authored 474 publications receiving 29885 citations. Previous affiliations of Derrick W. Crook include Oxford Brookes University & The Chinese University of Hong Kong.
Papers
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Journal ArticleDOI
Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys.
Koen B. Pouwels,Laurence Roope,James M. Buchanan,Liz Morrell,Sarah Tonkin-Crine,Michele Peters,Leah Jones,Enrique Castro-Sánchez,Derrick W. Crook,Tim E. A. Peto,Christopher C Butler,Julie V. Robotham,A. Sarah Walker,Sarah Wordsworth +13 more
TL;DR: In this paper, three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibiotics for influenza-like illnesses (ILI) (May/June 2015, Oct/Nov 2016 and Mar 2017).
Posted ContentDOI
Hash-based core genome multi-locus sequencing typing for Clostridium difficile
David W Eyre,David W Eyre,Tim E. A. Peto,Tim E. A. Peto,Tim E. A. Peto,Derrick W. Crook,Derrick W. Crook,Derrick W. Crook,A. Sarah Walker,A. Sarah Walker,A. Sarah Walker,Mark H. Wilcox +11 more
TL;DR: A refinement to core-genome multi-locus sequence typing (cgMLST) where alleles at each gene are reproducibly converted to a unique hash, or short string of letters (hash-cg MLST), which avoids the resource-intensive need for a single centralised database of sequentially-numbered alleles.
Journal ArticleDOI
Construction of a novel shuttle vector for use in Haemophilus influenzae and H. parainfluenzae
TL;DR: A shuttle vector, pEJ6, which transfers genes between Escherichia coli and H. influenzae and is functional for allelic replacement and mutant complementation and will be useful for investigating gene function in Haemophilus spp.
Journal ArticleDOI
Prediction of Pyrazinamide Resistance in Mycobacterium Tuberculosis Using Structure-Based Machine Learning Approaches
Joshua Carter,Timothy M Walker,A. Sarah Walker,Michael G. Whitfield,Glenn P. Morlock,Tim E. A. Peto,James E. Posey,Derrick W. Crook,Derrick W. Crook,Philip W. Fowler +9 more
TL;DR: In this article, a machine learning model was used to predict pyrazinamide resistance in clinical isolates based on sequence and structure-based features of missense pncA mutations.
Journal ArticleDOI
An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
Yang Yang,Timothy M. Walker,Samaneh Kouchaki,Chenyang Wang,Tim E. A. Peto,Derrick W. Crook,David A. Clifton +6 more
TL;DR: In this article, a deep graph learning method based on heterogeneous graph attention network (HGAT-AMR) was proposed to predict anti-tuberculosis (TB) drug resistance, which is able to accommodate incomplete phenotypic profiles, as well as provide 'attention scores' of genes and single nucleotide polymorphisms both at a population level and for individual samples.