Rishika Sen :: Research
Her research interests are in the field of Data Science, Trustworthy AI, Generative AI, Bioinformatics and Computational Biology. She has developed a solution for automated assessment of Trustworthiness of AI systems. She is currently working on Knowledge Distillation techniques of LLMs. She has specialized in the identification of toxins from pathogens and their effect on the host pathways. She has developed several in silico algorithms to identify toxins based on the structure of the molecules. She has also worked on signaling pathways, measuring their robustness, and predicting metabolic pathways from the constituent metabolites. She has been recently working on trying to apply some of these algorithms to discover repurposed drugs that might be effective against COVID-19. Currently, she is a Senior Research Fellow at Machine Intelligence Unit. Her research focus is on using machine learning techniques to solve problems including:
- Designed a mathematically sound system based on boolean networks that analyzes the effect of perturbations by toxins in signaling pathways by toxins.
- Designed a novel over-sampling algorithm to improve 3D structure based classification of effector proteins. Consequently, designed a 3D structure based effector protein identifier based on ensemble learning.
- Designed a mathematically sound system to predict unknown metabolic pathways and the effect of toxins on them, based on the 2D structural similarity of the metabolites
- Developed a deep learning based model to identify Type VII effector proteins.
She was a Junior Research Fellow (2014 – 2016) at Machine Intelligence Unit, Indian Statistical Institute. Her research focus was:
- Developed an ensemble model for the identification of Type VI effector proteins.
- Reviewing the current state of the art for the classification and prediction of host pathogen interactions.
Articles
Rishika Sen, Somnath Tagore, and Rajat Kumar De. "Cluster Quality based Non-Reductional (CQNR) oversampling technique and Effector Protein Predictor based on 3D structure (EPP3D) of proteins." Computers in Biology and Medicine (2019) doi: 10.1016/j.compbiomed.2019.103374, IF: 3.434, SCI Indexed
Rishika Sen, Losiana Nayak, and Rajat Kumar De. "PyPredT6: A Python based Prediction Tool for Identification of Type VI Effector Proteins." Journal of Bioinformatics and Computational biology (2019) doi: 10.1142/S0219720019500197, IF: 0.912, SCI Indexed
Rishika Sen, Somnath Tagore, Rajat Kumar De. “ASAPP:
Architectural Similarity-based Automated Pathway Prediction System and its
Application in Host-Pathogen Interactions.”
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
(2018) doi: 10.1109/TCBB.2018.2872527, IF: 3.015, SCI Indexed
Rishika Sen, Losiana Nayak, and Rajat Kumar De. "A review on
host–pathogen interactions: classification and prediction." European Journal of
Clinical Microbiology & Infectious Diseases 35.10 (2016): 1581-1599, doi:
10.1007/s10096-016-2716-7, IF: 2.837, SCI Indexed
Rishika Sen and Rajat Kumar De. "BNRA: A Boolean logic based Network Robustness Analyzer and its application in the aspect of Host-Pathogen interactions“ (Communicated)
Rishika Sen and Rajat Kumar De. "DeepT7: A Deep Neural Network based System for Identification of Type VII Effector Proteins “ (Communicated)
Posters
Rishika Sen, Losiana Nayak, and Rajat Kumar De. "Classification,
Prediction and Analysis of Type VI Secreted Effector Proteins". Advanced Lecture
Course - Molecular Mechanisms of Host-Pathogens Interactions and Virulence in
Human Fungal Pathogens, University of Aberdeen, Nice, France. (2017)
[PDF]
[BiBTeX]
Rishika Sen, Losiana Nayak, and Rajat Kumar De.
"Signature Pattern Mining of Type VI effector Proteins". EMBO Global Exchange
Lecture Course: Malaria Genomics and Public Health. (2017) DOI:
10.13140/RG.2.2.15231.61601
[PDF]
[BiBTeX]
Workshops/Symposiums attended
India|EMBO Symposium:Regulatory epigenomics:
From large data to useful models, March 10 to March 13,
2019 Chennai, India
International Symposium on Health Analytics and Disease
Modeling (HADM 2016), 29th February & 1st March, 2016,
Indian Institute of Public Health, Hyderabad (IIPHH), India
3rd IMSc Workshop and Conference on Modeling Infectious Diseases,
November 23 to December 1, 2015, Chennai, India
Acted as a reviewer in
Pattern Recognition and Machine Intelligence 8th International Conference, PReMI 2019, Tezpur, India [book]