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Biochimica Et Biophysica Acta. Molecular Basis of Disease|April 27, 2023
MutBLESS: A tool to identify disease-prone sites in cancer using deep learningMedha Pandey, M Michael GromihaMutation Research|January 28, 2021
Predicting potential residues associated with lung cancer using deep neural networkMedha Pandey, M Michael GromihaBioinformatics Advances|March 17, 2026
Classification of driver and passenger mutations in different cancer types using deep neural networksMedha Pandey, Anoosha Paruchuri, M Michael GromihaAdvances in Protein Chemistry and Structural Biology|March 6, 2024
Computational approaches for identifying disease-causing mutations in proteinsMedha Pandey, Suraj Kumar Shah, M Michael GromihaBriefings in Bioinformatics|October 20, 2022
Identification of potential driver mutations in glioblastoma using machine learningMedha Pandey, P Anoosha, Dhanusha Yesudhas, et al.Methods (San Diego, Calif.)|February 5, 2025
ZFP-CanPred: Predicting the effect of mutations in zinc-finger proteins in cancers using protein language modelsAmit Phogat, Sowmya Ramaswamy Krishnan, Medha Pandey, et al.Computers in Biology and Medicine|December 5, 2024
Progress on the development of prediction tools for detecting disease causing mutations in proteinsM Michael Gromiha, Medha Pandey, A Kulandaisamy, et al.Computers in Biology and Medicine|June 17, 2022
Understanding the mutational frequency in SARS-CoV-2 proteome using structural featuresPuneet Rawat, Divya Sharma, Medha Pandey, et al.Journal of Chemical Information and Computer Sciences|September 23, 2003
Importance of native-state topology for determining the folding rate of two-state proteinsM Michael GromihaBiophysical Chemistry|May 3, 2003
Influence of cation-pi interactions in different folding types of membrane proteinsM Michael GromihaPageof 27