Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session T00: Poster Session III (1pm-4pm PST)
1:00 PM,
Thursday, March 9, 2023
Room: Exhibit Hall (Forum Ballroom)
Sponsoring
Unit:
APS
Abstract: T00.00291 : Machine Learning Assisted Prediction of Physical Properties of Cyclotides*
Presenter:
Sairam Tangirala
(Georgia Gwinnett College)
Authors:
Sairam Tangirala
(Georgia Gwinnett College)
Rachel Schaffer
(Georgia Gwinnett College)
Ajay Mallia
(Georgia Gwinnett College)
Simon Mwongela
(Georgia Gwinnett College)
Neville Forlemu
(Georgia Gwinnett College)
In this study, we use a set of datafiles created by MD study of Kalata-B1 molecule (a type of cyclotide) to create a feature vector(s) consisting of numerical metrics that capture the chemical interactions of Kalata-B1 molecule. As a part of this study, we plan to generate and process the MD data to engineer predictor variables, to generate test/training data sets, and to develop and test machine learning model(s) that predict the simulational results of MD calculations.
*This research is supported by National Science Foundation award number:2107567
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700