PHD, University of Hyderabad India
Anubha Dey is a dedicated Ph.D. researcher at the University of Hyderabad with a strong background in computational biology and machine learning. She has contributed significantly to understanding genetic interactions and cancer research through advanced modeling techniques. With a passion for teaching and mentoring, Anubha aspires to inspire future leaders in scientific innovation.
Professional Profile
Scopus
Scholar
Education
Ph.D. (Pursuing), University of Hyderabad, 2019-present. Master of Technology, Anna University, 2017-2019. Bachelor of Technology, Maulana Abul Kalam Azad University of Technology, West Bengal
Experience
Researcher: Developing machine learning models for cancer biology and genetic interactions. Assistant System Engineer-Trainee, Tata Consultancy Services, 2016-2017. Presented findings at renowned conferences like ICGA and CSHL
Award and Honor
Best Oral Presentation, BioAnveshna 2024. Best Poster Presentation, International Cancer Symposium 2022. Selected for HySci 2024 Oral Talk, IIT Hyderabad. Qualified JEST 2019, a prestigious entrance test
Research Focus
Machine learning in genetic interaction prediction. Synthetic lethal interactions in cancer. Transcript complexity and RNA splicing. Chromatin loop dynamics and epigenetics
Publications Top Noted
- Title: Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features
Year: 2023
Authors: ML Bond, ES Davis, IY Quiroga, A Dey, M Kiran, MI Love, H Won
Citation: Genome Research 33 (8), 1258-1268
- Title: Inefficient splicing of long non-coding RNAs is associated with higher transcript complexity in human and mouse
Year: 2023
Authors: K Basu, A Dey, M Kiran
Citation: RNA Biology 20 (1), 563-572
- Title: MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network
Year: 2024
Authors: A Dey, S Mudunuri, M Kiran
Citation: PLOS Computational Biology 20 (8), e1012336
- Title: CaTCH: Calculating transcript complexity of human genes
Year: 2024
Authors: K Koushiki Basu, Anubha Dey
Citation: Methodx