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

Kevin L Yang

Showing results (1-10 of 9) with videos related to

Pageof 1
Sort By:
Nature Communications|January 2, 2025
diaTracer enables spectrum-centric analysis of diaPASEF proteomics dataKai Li, Guo Ci Teo, Kevin L Yang, et al.
Biorxiv : the Preprint Server for Biology|June 10, 2024
diaTracer enables spectrum-centric analysis of diaPASEF proteomics dataKai Li, Guo Ci Teo, Kevin L Yang, et al.
Nature Communications|July 27, 2023
MSBooster: improving peptide identification rates using deep learning-based featuresKevin L Yang, Fengchao Yu, Guo Ci Teo, et al.
Biorxiv : the Preprint Server for Biology|June 12, 2025
Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome CoverageNikita Levin, Cemil Can Saylan, Joel Lapin, et al.
Nature Methods|March 24, 2026
Integration of alternative fragmentation techniques into standard LC-MS workflows using a single deep learning model enhances proteome coverageNikita Levin, Cemil Can Saylan, Joel Lapin, et al.
Molecular & Cellular Proteomics : MCP|May 2, 2025
Benchmarking SILAC Proteomics Workflows and Data Analysis PlatformsAshley M Frankenfield, Kevin L Yang, Wan Nur Atiqah Binti Mazli, et al.
Biorxiv : the Preprint Server for Biology|June 19, 2024
Koina: Democratizing machine learning for proteomics researchLudwig Lautenbacher, Kevin L Yang, Tobias Kockmann, et al.
Metallomics : Integrated Biometal Science|May 19, 2020
Huntington's disease genotype suppresses global manganese-responsive processes in pre-manifest and manifest YAC128 miceAnna C Pfalzer, Jordyn M Wilcox, Simona G Codreanu, et al.
Nature Communications|November 11, 2025
Koina: Democratizing machine learning for proteomics researchLudwig Lautenbacher, Kevin L Yang, Tobias Kockmann, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Nature Communications|January 2, 2025
diaTracer enables spectrum-centric analysis of diaPASEF proteomics dataKai Li, Guo Ci Teo, Kevin L Yang, et al.
Biorxiv : the Preprint Server for Biology|June 10, 2024
diaTracer enables spectrum-centric analysis of diaPASEF proteomics dataKai Li, Guo Ci Teo, Kevin L Yang, et al.
Nature Communications|July 27, 2023
MSBooster: improving peptide identification rates using deep learning-based featuresKevin L Yang, Fengchao Yu, Guo Ci Teo, et al.
Biorxiv : the Preprint Server for Biology|June 12, 2025
Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome CoverageNikita Levin, Cemil Can Saylan, Joel Lapin, et al.
Nature Methods|March 24, 2026
Integration of alternative fragmentation techniques into standard LC-MS workflows using a single deep learning model enhances proteome coverageNikita Levin, Cemil Can Saylan, Joel Lapin, et al.
Molecular & Cellular Proteomics : MCP|May 2, 2025
Benchmarking SILAC Proteomics Workflows and Data Analysis PlatformsAshley M Frankenfield, Kevin L Yang, Wan Nur Atiqah Binti Mazli, et al.
Biorxiv : the Preprint Server for Biology|June 19, 2024
Koina: Democratizing machine learning for proteomics researchLudwig Lautenbacher, Kevin L Yang, Tobias Kockmann, et al.
Metallomics : Integrated Biometal Science|May 19, 2020
Huntington's disease genotype suppresses global manganese-responsive processes in pre-manifest and manifest YAC128 miceAnna C Pfalzer, Jordyn M Wilcox, Simona G Codreanu, et al.
Nature Communications|November 11, 2025
Koina: Democratizing machine learning for proteomics researchLudwig Lautenbacher, Kevin L Yang, Tobias Kockmann, et al.
Pageof 1