Anja Conev

Anja Conev

Postdoctoral Researcher (Bioinformatician) in Protein Structure and Variant Modelling

Imperial College London - Center for Integrative Systems Biology and Bioinformatics

Biography

I apply artificial intelligence and machine learning (ML) techniques to the problems in the field of computational structural biology with the goal of aiding drug discovery. In particular, the computational problems I explored include the design of ML-driven molecular scoring functions, search approaches in molecular docking, analysis and visualization of the data generated by biomolecular and macromolecular simulations.

Interests
  • Artificial Intelligence
  • Computational Biology
  • Unsupervised Learning
  • Proteomics
Education
  • PhD in Computer Science, 2024

    Rice University

  • BSc in Electrical Engineering and Computer Technology, 2019

    University of Belgrade

Projects

3DSeqCheck
A lightweight Web Server and Python tool for comparing UniProt sequences with sequences extracted from 3D structures.
3DSeqCheck
3pHLA-score
A machine learning structure-based protocol for predicting binding affinity of peptides to HLA receptors.
3pHLA-score
DINC-Ensemble
DINC-Ensemble takes as input an ensemble of receptors and a ligand. It performs incremental meta-docking to find the most favorable pose of the ligand inside the binding pocket of the given receptors.
DINC-Ensemble
EnGens
EnGens is a tool for end-to-end processing of large protein structural datasets with the aim of generating and analyzing representative protein conformational ensembles.
EnGens
HLA-Arena
A pipeline for structural analysis of class I HLA proteins and their binding to the self peptides.
HLA-Arena