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

Mythreye Venkatesan

Showing results (1-10 of 14) with videos related to

Pageof 2
Sort By:
Communications Biology|December 17, 2019
Digital posters for interactive cellular media and bioengineering educationMythreye Venkatesan, Ahmet F Coskun
Biodata Mining|April 15, 2025
Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modelingXi Li, Jui-Hsuan Chang, Mythreye Venkatesan, et al.
Bioinformatics (Oxford, England)|June 3, 2024
KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language modelsNicholas Matsumoto, Jay Moran, Hyunjun Choi, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 13, 2024
Biologically Enhanced Machine Learning Model to uncover Novel Gene-Drug Targets for Alzheimer's DiseaseAlena Orlenko, Mythreye Venkatesan, Li Shen, et al.
Cell Reports. Medicine|August 2, 2021
Virtual and augmented reality for biomedical applicationsMythreye Venkatesan, Harini Mohan, Justin R Ryan, et al.
Iscience|September 12, 2022
Multiplexed protein profiling reveals spatial subcellular signaling networksShuangyi Cai, Thomas Hu, Mythreye Venkatesan, et al.
Bioinformatics (Oxford, England)|January 22, 2025
ESCARGOT: an AI agent leveraging large language models, dynamic graph of thoughts, and biomedical knowledge graphs for enhanced reasoningNicholas Matsumoto, Hyunjun Choi, Jay Moran, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 27, 2026
A random-walk-based learning framework to uncover novel gene candidates for Alzheimer's disease therapyAlena Orlenko, Binglan Li, Neda Khanjani, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 31, 2023
SynTwin: A graph-based approach for predicting clinical outcomes using digital twins derived from synthetic patientsJason H Moore, Xi Li, Jui-Hsuan Chang, et al.
The Journal of Trauma and Acute Care Surgery|March 29, 2024
Using machine learning to predict outcomes of patients with blunt traumatic aortic injuriesEileen Lu, Joseph Dubose, Mythreye Venkatesan, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Communications Biology|December 17, 2019
Digital posters for interactive cellular media and bioengineering educationMythreye Venkatesan, Ahmet F Coskun
Biodata Mining|April 15, 2025
Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modelingXi Li, Jui-Hsuan Chang, Mythreye Venkatesan, et al.
Bioinformatics (Oxford, England)|June 3, 2024
KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language modelsNicholas Matsumoto, Jay Moran, Hyunjun Choi, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 13, 2024
Biologically Enhanced Machine Learning Model to uncover Novel Gene-Drug Targets for Alzheimer's DiseaseAlena Orlenko, Mythreye Venkatesan, Li Shen, et al.
Cell Reports. Medicine|August 2, 2021
Virtual and augmented reality for biomedical applicationsMythreye Venkatesan, Harini Mohan, Justin R Ryan, et al.
Iscience|September 12, 2022
Multiplexed protein profiling reveals spatial subcellular signaling networksShuangyi Cai, Thomas Hu, Mythreye Venkatesan, et al.
Bioinformatics (Oxford, England)|January 22, 2025
ESCARGOT: an AI agent leveraging large language models, dynamic graph of thoughts, and biomedical knowledge graphs for enhanced reasoningNicholas Matsumoto, Hyunjun Choi, Jay Moran, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 27, 2026
A random-walk-based learning framework to uncover novel gene candidates for Alzheimer's disease therapyAlena Orlenko, Binglan Li, Neda Khanjani, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 31, 2023
SynTwin: A graph-based approach for predicting clinical outcomes using digital twins derived from synthetic patientsJason H Moore, Xi Li, Jui-Hsuan Chang, et al.
The Journal of Trauma and Acute Care Surgery|March 29, 2024
Using machine learning to predict outcomes of patients with blunt traumatic aortic injuriesEileen Lu, Joseph Dubose, Mythreye Venkatesan, et al.
Pageof 2