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Data-Driven Drug Discovery and Molecular Informatics

I joined the group in 2018 through the BBSRC DTP iCASE program with Eli Lilly, after completing the MChem/BSc in Chemistry at the University of Leeds, including a year in industry at Optibrium Ltd.

The aim of my research is to develop methods to better understand the mechanism of action of drugs using biological data (such as transcriptomics data), for e.g. repurposing or target deconvolution following phenotypic screening. This includes the use of systems biology approaches such as causal reasoning on PPI (protein-protein interaction) networks to identify upstream protein perturbations leading to observed compound-induced gene expression changes.

 

Publications

Using biological and chemical information to improve understanding of drug mechanism of action on the systems-level
L Hosseini.Gerami
(2022)
MAVEN: Compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny
L Hosseini-Gerami, RH Ballesteros, A Liu, H Broughton, DA Collier, A Bender
(2022)
Computational analyses of mechanism of action (MoA): data, methods and integration.
M-A Trapotsi, L Hosseini-Gerami, A Bender
– RSC Chemical Biology
(2021)
3,
170
Predicting pKa Using a Combination of Semi-Empirical Quantum Mechanics and Radial Basis Function Methods.
P Hunt, L Hosseini-Gerami, T Chrien, J Plante, DJ Ponting, M Segall
– J Chem Inf Model
(2020)
60,
2989
Combining quantum and QSAR methods for prediction of acid dissociation constants
L Hosseini-Gerami, R Leth, P Hunt, M Segall
– ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2017)
253,

Telephone number

01223 336432