Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Alexis Battle

Showing results (1-10 of 101) with videos related to

Pageof 11
Sort By:
F1000Research|April 24, 2019
False positives in trans-eQTL and co-expression analyses arising from RNA-sequencing alignment errorsAshis Saha, Alexis Battle
Trends in Genetics : TIG|March 13, 2026
Beyond the baseline: mapping the context-specific regulatory landscape of diseaseYoav Gilad, Alexis Battle
Trends in Genetics : TIG|August 10, 2024
Computational methods for allele-specific expression in single cellsGuanghao Qi, Alexis Battle
F1000Research|March 18, 2024
Bayesian Multi-View Clustering given complex inter-view structureBenjamin D Shapiro, Alexis Battle
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 6, 2005
Probabilistic discovery of overlapping cellular processes and their regulationAlexis Battle, Eran Segal, Daphne Koller
Trends in Genetics : TIG|September 11, 2020
Where Are the Disease-Associated eQTLs?Benjamin D Umans, Alexis Battle, Yoav Gilad
Cell Systems|August 22, 2024
Transcriptome data are insufficient to control false discoveries in regulatory network inferenceEric Kernfeld, Rebecca Keener, Patrick Cahan, et al.
American Journal of Human Genetics|January 27, 2022
Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneityMarios Arvanitis, Karl Tayeb, Benjamin J Strober, et al.
Biorxiv : the Preprint Server for Biology|August 14, 2023
A systematic comparison of computational methods for expression forecastingEric Kernfeld, Yunxiao Yang, Joshua Weinstock, et al.
Biorxiv : the Preprint Server for Biology|October 3, 2025
Fine-tuning sequence to function deep learning models on large-scale proteomic data improves the accuracy of variant effect predictionEduarda Vaz, Lena Wang, Jake Galvin, et al.
Pageof 11

Showing results (1-10 of 101) with videos related to

Sort By:
Pageof 11
F1000Research|April 24, 2019
False positives in trans-eQTL and co-expression analyses arising from RNA-sequencing alignment errorsAshis Saha, Alexis Battle
Trends in Genetics : TIG|March 13, 2026
Beyond the baseline: mapping the context-specific regulatory landscape of diseaseYoav Gilad, Alexis Battle
Trends in Genetics : TIG|August 10, 2024
Computational methods for allele-specific expression in single cellsGuanghao Qi, Alexis Battle
F1000Research|March 18, 2024
Bayesian Multi-View Clustering given complex inter-view structureBenjamin D Shapiro, Alexis Battle
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 6, 2005
Probabilistic discovery of overlapping cellular processes and their regulationAlexis Battle, Eran Segal, Daphne Koller
Trends in Genetics : TIG|September 11, 2020
Where Are the Disease-Associated eQTLs?Benjamin D Umans, Alexis Battle, Yoav Gilad
Cell Systems|August 22, 2024
Transcriptome data are insufficient to control false discoveries in regulatory network inferenceEric Kernfeld, Rebecca Keener, Patrick Cahan, et al.
American Journal of Human Genetics|January 27, 2022
Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneityMarios Arvanitis, Karl Tayeb, Benjamin J Strober, et al.
Biorxiv : the Preprint Server for Biology|August 14, 2023
A systematic comparison of computational methods for expression forecastingEric Kernfeld, Yunxiao Yang, Joshua Weinstock, et al.
Biorxiv : the Preprint Server for Biology|October 3, 2025
Fine-tuning sequence to function deep learning models on large-scale proteomic data improves the accuracy of variant effect predictionEduarda Vaz, Lena Wang, Jake Galvin, et al.
Pageof 11