AFsample2 predicts multiple conformations and ensembles with AlphaFold2
Kalakoti, Yogesh, Wallner, Björn. (2025). "AFsample2 predicts multiple conformations and ensembles with AlphaFold2." Communications Biology. 8(1), 373.
CV
Education
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
- M.S. in Jekyll, GitHub University, 2014
- B.S. in GitHub, GitHub University, 2012
Work experience
- Spring 2024: Academic Pages Collaborator
- Github University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Prediction of structural variation
Kalakoti, Yogesh, Sanjeev, Airy, Wallner, Björn. (2025). "Prediction of structural variation." Current opinion in structural biology. 91, 103003.
Estimating protein–ligand interactions with geometric deep learning and mixture density models
Eliot, Kalakoti, Yogesh, Gawande, Swaraj, Sundar, Durai. (2024). "Estimating protein--ligand interactions with geometric deep learning and mixture density models." Journal of Biosciences. 49(4), 97.
M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings
Shenoy, Aditi, Kalakoti, Yogesh, Sundar, Durai, Elofsson, Arne. (2024). "M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings." Bioinformatics. 40(1), btad782.
Modulation of DNA-protein Interactions by Proximal Genetic Elements as Uncovered by Interpretable Deep Learning
Kalakoti, Yogesh, Peter, Swathik Clarancia, Gawande, Swaraj, Sundar, Durai. (2023). "Modulation of DNA-protein Interactions by Proximal Genetic Elements as Uncovered by Interpretable Deep Learning." Journal of Molecular Biology. 435(13), 168121.
Computational Methods and Deep Learning for Elucidating Protein Interaction Networks
Vora, Dhvani Sandip, Kalakoti, Yogesh, Sundar, Durai. (2022). "Computational Methods and Deep Learning for Elucidating Protein Interaction Networks." Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology. 285-323.
Genome Sequence of a Potent Biosurfactant-Producing Bacterium, Franconibacter sp. Strain IITDAS19
Sharma, Jyoti, Kalakoti, Yogesh, Srivastava, Preeti, Sundar, Durai. (2022). "Genome Sequence of a Potent Biosurfactant-Producing Bacterium, Franconibacter sp. Strain IITDAS19." Microbiology Resource Announcements. 11(8), e00419-22.
Deep neural network-assisted drug recommendation systems for identifying potential drug–target interactions
Kalakoti, Yogesh, Yadav, Shashank, Sundar, Durai. (2022). "Deep neural network-assisted drug recommendation systems for identifying potential drug--target interactions." ACS omega. 7(14), 12138-12146.
TransDTI: transformer-based language models for estimating DTIs and building a drug recommendation workflow
Kalakoti, Yogesh, Yadav, Shashank, Sundar, Durai. (2022). "TransDTI: transformer-based language models for estimating DTIs and building a drug recommendation workflow." ACS omega. 7(3), 2706-2717.
TransDTI: transformer-based language models for estimating DTIs and building a drug recommendation workflow
Kalakoti, Yogesh, Yadav, Shashank, Sundar, Durai. (2022). "TransDTI: transformer-based language models for estimating DTIs and building a drug recommendation workflow." ACS omega. 7(3), 2706-2717.
SurvCNN: a discrete time-to-event cancer survival estimation framework using image representations of omics data
Kalakoti, Yogesh, Yadav, Shashank, Sundar, Durai. (2021). "SurvCNN: a discrete time-to-event cancer survival estimation framework using image representations of omics data." Cancers. 13(13), 3106.
SurvCNN: a discrete time-to-event cancer survival estimation framework using image representations of omics data
Kalakoti, Yogesh, Yadav, Shashank, Sundar, Durai. (2021). "SurvCNN: a discrete time-to-event cancer survival estimation framework using image representations of omics data." Cancers. 13(13), 3106.
Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer
Malik, Vidhi, Kalakoti, Yogesh, Sundar, Durai. (2021). "Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer." BMC genomics. 22(1), 214.
Multi-omics Integration based Predictive Model for Survival Prediction of Lung Adenocarcinoma
Malik, Vidhi, Dutta, Shayoni, Kalakoti, Yogesh, others. (2019). "Multi-omics Integration based Predictive Model for Survival Prediction of Lung Adenocarcinoma." 2019 Grace Hopper Celebration India (GHCI).
Talks
Improving generative methods to capture conformational diversity in protein ensembles
Talk at 28th Swedish Conference on Macromolecular Structure & Function (SWEPROT 2025), Tällberg, Sweden
Transformer-based molecular embeddings for modeling drug-target interactions and recommending probable leads
Talk at EMBO Workshop: When predictions meet experiments: The future of structure determination, Palermo, Italy
Teaching
Service and leadership
- Currently signed in to 43 different slack teams