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F1000Research|February 1, 2018
The rise and fall of machine learning methods in biomedical researchHashem KoohyF1000Research|May 15, 2020
<i>In silico</i> identification of vaccine targets for 2019-nCoVChloe H Lee, Hashem KoohyImmunoinformatics (Amsterdam, Netherlands)|March 25, 2024
A comparison of clustering models for inference of T cell receptor antigen specificityDan Hudson, Alex Lubbock, Mark Basham, et al.Plos One|August 8, 2013
Chromatin accessibility data sets show bias due to sequence specificity of the DNase I enzymeHashem Koohy, Thomas A Down, Tim J HubbardPlos One|May 10, 2014
A comparison of peak callers used for DNase-Seq dataHashem Koohy, Thomas A Down, Mikhail Spivakov, et al.Nature Reviews. Immunology|February 9, 2023
Can we predict T cell specificity with digital biology and machine learning?Dan Hudson, Ricardo A Fernandes, Mark Basham, et al.Nature Methods|April 23, 2024
Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Benjamin McMaster, Christopher Thorpe, Graham Ogg, et al.Frontiers in Immunology|December 17, 2024
Quantifying conformational changes in the TCR:pMHC-I binding interfaceBenjamin McMaster, Christopher J Thorpe, Jamie Rossjohn, et al.Bioinformatics (Oxford, England)|August 11, 2010
An alignment-free model for comparison of regulatory sequencesHashem Koohy, Nigel P Dyer, John E Reid, et al.Immunotherapy Advances|April 21, 2023
A systems approach evaluating the impact of SARS-CoV-2 variant of concern mutations on CD8+ T cell responsesPaul R Buckley, Chloe H Lee, Agne Antanaviciute, et al.Pageof 4