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

Daniel Marri

Showing results (1-10 of 5) with videos related to

Pageof 1
Sort By:
Current Opinion in Toxicology|April 22, 2024
Unique challenges and best practices for single cell transcriptomic analysis in toxicologyDavid Filipovic, Omar Kana, Daniel Marri, et al.
Scientific Reports|May 12, 2023
Prediction of mammalian tissue-specific CLOCK-BMAL1 binding to E-box DNA motifsDaniel Marri, David Filipovic, Omar Kana, et al.
STAR Protocols|July 12, 2025
Protocol for predicting single- and multiple-dose-dependent gene expression using deep generative learningDerek E Bowman, Vishal Panda, Daniel Marri, et al.
Patterns (New York, N.Y.)|August 21, 2023
Generative modeling of single-cell gene expression for dose-dependent chemical perturbationsOmar Kana, Rance Nault, David Filipovic, et al.
Toxicological Sciences : an Official Journal of the Society of Toxicology|September 14, 2023
Interpretable predictive models of genome-wide aryl hydrocarbon receptor-DNA binding reveal tissue-specific binding determinantsDavid Filipovic, Wenjie Qi, Omar Kana, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Current Opinion in Toxicology|April 22, 2024
Unique challenges and best practices for single cell transcriptomic analysis in toxicologyDavid Filipovic, Omar Kana, Daniel Marri, et al.
Scientific Reports|May 12, 2023
Prediction of mammalian tissue-specific CLOCK-BMAL1 binding to E-box DNA motifsDaniel Marri, David Filipovic, Omar Kana, et al.
STAR Protocols|July 12, 2025
Protocol for predicting single- and multiple-dose-dependent gene expression using deep generative learningDerek E Bowman, Vishal Panda, Daniel Marri, et al.
Patterns (New York, N.Y.)|August 21, 2023
Generative modeling of single-cell gene expression for dose-dependent chemical perturbationsOmar Kana, Rance Nault, David Filipovic, et al.
Toxicological Sciences : an Official Journal of the Society of Toxicology|September 14, 2023
Interpretable predictive models of genome-wide aryl hydrocarbon receptor-DNA binding reveal tissue-specific binding determinantsDavid Filipovic, Wenjie Qi, Omar Kana, et al.
Pageof 1