DPhil research opportunity
Aleksandr Sahakyan
MRC WIMM Group Leader
computational biology, machine learning, data integration, molecular medicine, genome, transcriptome and proteome
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 and experimental biophysical and sequencing techniques to reach a new level of precision in structural systems biology at both genome and proteome levels.
Recent publications
-
A Spontaneous Ring Opening Reaction Leads to a Repair‐Resistant T Oxidation Product in Genomic DNA
Journal article
Sahakyan A. et al, (2019), ChemBioChem
-
Whole genome experimental maps of DNA G-quadruplexes in multiple species.
Journal article
Marsico G. et al, (2019), Nucleic Acids Res
-
Structural analysis reveals the formation and role of RNA G-quadruplex structures in human mature microRNAs.
Journal article
Chan KL. et al, (2018), Chem Commun (Camb), 54, 10878 - 10881
-
Machine learning model for sequence-driven DNA G-quadruplex formation.
Journal article
Sahakyan AB. et al, (2017), Sci Rep, 7
-
G-quadruplex structures within the 3' UTR of LINE-1 elements stimulate retrotransposition.
Journal article
Sahakyan AB. et al, (2017), Nat Struct Mol Biol, 24, 243 - 247