MRC WIMM Group Leader and Principal Investigator in RDM
computational biology, machine learning, data integration, molecular medicine, genome, transcriptome and proteome
Alex is a principal investigator leading a group focused on integrative computational biology and machine learning in the MRC Weatherall Institute of Molecular Medicine and Radcliffe Department of Medicine. In past, he did his undergraduate studies in pharmaceutical sciences while actively researching in the area of quantum/structural chemistry and NMR spectroscopy. He next moved to the University of Cambridge, first obtaining an MPhil degree in computational biology with distinction (Department of Applied Mathematics and Theoretical Physics, supported by Cambridge Trust), followed by a PhD in theoretical chemical biology (Department of Chemistry) as a Herchel Smith Scholar. He then became an interdisciplinary research fellow in computational genomics and epigenetics (Department of Chemistry and Cancer Research UK Cambridge Institute), before joining the University of Oxford. His research aims at combining machine learning, computational biology, computational chemistry, experimental data from genomics and biophysical techniques to reach a new level of precision in biology at both genome and proteome levels.
Generalised interrelations among mutation rates drive the genomic compliance of Chargaff's second parity rule.
Pflughaupt P. and Sahakyan AB., (2023), Nucleic Acids Res
ROptimus: a parallel general-purpose adaptive optimisation engine.
Johnson NAG. et al, (2023), Bioinformatics
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
Masuda K. et al, (2023)
Generalised interrelations among mutation rates drive the genomic compliance of Chargaff’s second parity rule
Pflughaupt P. and Sahakyan AB., (2022)
Optimus: a general purpose adaptive optimisation engine in R
Johnson N. et al, (2022)