Sahakyan Group: Integrative Computational Biology and Machine Learning
Combining computational biology, computational chemistry, and machine learning techniques with biological big data to unravel the higher genomic code of life.
Our research targets genomics through the development of highly quantitative methods for describing the structure and dynamics of (epi)genome, gene regulatory pathways, involved macromolecules and their interaction networks. We are interested in combining advanced machine learning, computational biology, computational chemistry (QM, MD), experimental biophysical and sequencing-based big data to reach a new level of precision in structural systems biology at all (genome, transcriptome and proteome) levels. We try to make computational biology maximally independent from empirical data, basing our models and predictions purely on i) genomic sequences and ii) 3-dimensional structures. We strive to achieve this by employing advanced machine learning (supervised and unsupervised) methodologies, coupled with the engineering of derivative biology, chemistry, physics and structure “aware” features. We apply our "ab intio" modelling approaches to better understand gene regulation, mutations, differential DNA damage and repair, and to spot driver DNA alterations in multigenic diseases (such as cancer, autism, cardiomyopathies). Besides the direct benefits, our approach also lets us understand part of the biology that we cannot predict, i.e. the remainder cell-specific factors not tightly inter-linked to our genomic blueprint. This helps us better characterise the genome-invariant factors involved in cell differentiation. We heavily work on the full automation of the workflows for generating our models, creating a tailored AI platform suitable for automatic rule discovery and model development from biological sequence and structure data.
Past members: Yuen Wai Him (visiting student, Chinese University of Hong Kong, 2019), Nancy Yang (visiting student, Princeton University, 2019), William Biggs (research assistant, Oxford University, 2018-2019), Claudia Feng (MPhil student, WIMM and Cambridge University, 2018) and Nicholas Johnson (visiting student, Princeton University, 2018).
Enquiries from prospective students and post-doctoral researchers are welcome.