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Jonathan Cairns

Showing results (1-10 of 27) with videos related to

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Frontiers in Genetics|December 3, 2014
Quantifying the impact of inter-site heterogeneity on the distribution of ChIP-seq dataJonathan Cairns, Andy G Lynch, Simon Tavaré
Bioinformatics (Oxford, England)|June 15, 2019
Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C dataJonathan Cairns, William R Orchard, Valeriya Malysheva, et al.
SLAS Discovery : Advancing Life Sciences R & D|January 22, 2021
High-Throughput Mechanism of InhibitionGareth Davies, Hannah Semple, Megan McCandless, et al.
Bioinformatics (Oxford, England)|February 15, 2026
AutoFlow: An interactive Shiny app for supervised and unsupervised flow cytometry analysisFreya E R Woods, Emilyanne Leonard, Timothy Ebbels, et al.
Bioinformatics (Oxford, England)|January 20, 2011
BayesPeak--an R package for analysing ChIP-seq dataJonathan Cairns, Christiana Spyrou, Rory Stark, et al.
Plos One|August 20, 2024
A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experimentsChang Sik Kim, Jonathan Cairns, Valentina Quarantotti, et al.
Plos One|March 20, 2025
Correction: A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experimentsChang Sik Kim, Jonathan Cairns, Valentina Quarantotti, et al.
Disease Models & Mechanisms|September 27, 2018
Optimizing the design of population-based patient-derived tumor xenograft studies to better predict clinical responseNicolas Floc'h, Maria Luisa Guerriero, Antonio Ramos-Montoya, et al.
Frontiers in Pharmacology|April 17, 2023
Optimal experimental design for efficient toxicity testing in microphysiological systems: A bone marrow applicationJonathan Cairns, Emilyanne Leonard, Kainat Khan, et al.
Nature Protocols|August 10, 2021
Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion toolsPaula Freire-Pritchett, Helen Ray-Jones, Monica Della Rosa, et al.
Pageof 3

Showing results (1-10 of 27) with videos related to

Sort By:
Pageof 3
Frontiers in Genetics|December 3, 2014
Quantifying the impact of inter-site heterogeneity on the distribution of ChIP-seq dataJonathan Cairns, Andy G Lynch, Simon Tavaré
Bioinformatics (Oxford, England)|June 15, 2019
Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C dataJonathan Cairns, William R Orchard, Valeriya Malysheva, et al.
SLAS Discovery : Advancing Life Sciences R & D|January 22, 2021
High-Throughput Mechanism of InhibitionGareth Davies, Hannah Semple, Megan McCandless, et al.
Bioinformatics (Oxford, England)|February 15, 2026
AutoFlow: An interactive Shiny app for supervised and unsupervised flow cytometry analysisFreya E R Woods, Emilyanne Leonard, Timothy Ebbels, et al.
Bioinformatics (Oxford, England)|January 20, 2011
BayesPeak--an R package for analysing ChIP-seq dataJonathan Cairns, Christiana Spyrou, Rory Stark, et al.
Plos One|August 20, 2024
A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experimentsChang Sik Kim, Jonathan Cairns, Valentina Quarantotti, et al.
Plos One|March 20, 2025
Correction: A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experimentsChang Sik Kim, Jonathan Cairns, Valentina Quarantotti, et al.
Disease Models & Mechanisms|September 27, 2018
Optimizing the design of population-based patient-derived tumor xenograft studies to better predict clinical responseNicolas Floc'h, Maria Luisa Guerriero, Antonio Ramos-Montoya, et al.
Frontiers in Pharmacology|April 17, 2023
Optimal experimental design for efficient toxicity testing in microphysiological systems: A bone marrow applicationJonathan Cairns, Emilyanne Leonard, Kainat Khan, et al.
Nature Protocols|August 10, 2021
Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion toolsPaula Freire-Pritchett, Helen Ray-Jones, Monica Della Rosa, et al.
Pageof 3