Search research articles
Contact Us
Filters
Showing results (1-10 of 16) with videos related to
Page
of 2
Sort By:
Methods in Molecular Biology (Clifton, N.J.)
|
November 3, 2021
Ultrahigh Throughput Protein-Ligand Docking with Deep Learning
Austin Clyde
Patterns (New York, N.Y.)
|
February 24, 2022
AI for science and global citizens
Austin Clyde
Frontiers in Medicine
|
March 6, 2023
Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
Alexander Partin, Thomas S Brettin, Yitan Zhu, et al.
Cancers
|
January 11, 2024
Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models
Oleksandr Narykov, Yitan Zhu, Thomas Brettin, et al.
BMC Bioinformatics
|
May 18, 2021
Learning curves for drug response prediction in cancer cell lines
Alexander Partin, Thomas Brettin, Yvonne A Evrard, et al.
Scientific Reports
|
February 6, 2023
AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
Austin Clyde, Xuefeng Liu, Thomas Brettin, et al.
Journal of Medicinal Chemistry
|
October 27, 2021
Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease
Daniel W Kneller, Hui Li, Stephanie Galanie, et al.
Briefings in Bioinformatics
|
September 15, 2021
A cross-study analysis of drug response prediction in cancer cell lines
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash, et al.
Journal of Chemical Information and Modeling
|
February 22, 2023
AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2
Rajendra P Joshi, Katherine J Schultz, Jesse William Wilson, et al.
Journal of Chemical Information and Modeling
|
November 18, 2021
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor
Austin Clyde, Stephanie Galanie, Daniel W Kneller, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 16) with videos related to
Sort By:
Page
of 2
Methods in Molecular Biology (Clifton, N.J.)
|
November 3, 2021
Ultrahigh Throughput Protein-Ligand Docking with Deep Learning
Austin Clyde
Patterns (New York, N.Y.)
|
February 24, 2022
AI for science and global citizens
Austin Clyde
Frontiers in Medicine
|
March 6, 2023
Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
Alexander Partin, Thomas S Brettin, Yitan Zhu, et al.
Cancers
|
January 11, 2024
Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models
Oleksandr Narykov, Yitan Zhu, Thomas Brettin, et al.
BMC Bioinformatics
|
May 18, 2021
Learning curves for drug response prediction in cancer cell lines
Alexander Partin, Thomas Brettin, Yvonne A Evrard, et al.
Scientific Reports
|
February 6, 2023
AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
Austin Clyde, Xuefeng Liu, Thomas Brettin, et al.
Journal of Medicinal Chemistry
|
October 27, 2021
Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease
Daniel W Kneller, Hui Li, Stephanie Galanie, et al.
Briefings in Bioinformatics
|
September 15, 2021
A cross-study analysis of drug response prediction in cancer cell lines
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash, et al.
Journal of Chemical Information and Modeling
|
February 22, 2023
AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2
Rajendra P Joshi, Katherine J Schultz, Jesse William Wilson, et al.
Journal of Chemical Information and Modeling
|
November 18, 2021
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor
Austin Clyde, Stephanie Galanie, Daniel W Kneller, et al.
Page
of 2