Mathematical modelling of epistasis in proteins using network analysis and statistical learning

Proteins are biopolymers composed of repetitive units (residues) from a set of 20 amino acids that form complex three-dimensional topologies. Protein topologies/structures undergo conformational changes over picosecond to millisecond timescales.

These changes are important for biological function and arise from inter and intra residue interactions and interactions with the solvent. These conformational changes can be modelled, using computer simulations and well-established software, generating millions of 3D structures that are saved as time-dependent trajectories.

To design proteins for novel functions or enhance their existing biological activity, advances in computational protocols for protein design are desired. Towards this goal, understanding the epistasis at the protein level, i.e. networks of synergistic interactions between residues that contribute to the function is the first step.

In this project, using the molecular dynamics simulations and sequence analysis data of a test protein system, the doctoral researcher will develop a mathematical formalism to analyse the complex network of interactions between the protein residues using time series network analysis, which can handle multiple densities of states;

• use graph convolutional networks to learn and predict effects of mutations on structural dynamics
• contributing to biological function 
• integrate this method to select design sites into our computational protocol for the selection of design sites.

The ideal candidate will have BSc and/or MSc degree in mathematics and/or computer science. Knowledge of C/Python and R will be highly desirable.

Research in Computer Science at Brunel is internationally recognised, ranked 5th in the UK in the Performance Ranking of Scientific Papers for World Universities and 1st in the UK for H-index (source NTU 2018). We have particular strengths in research into computing methodologies (Intelligent data analysis, artificial intelligence, simulation and modelling), software engineering, human centred computing (HCI and interactive multimedia systems) and digital economy (including IOT, trust, privacy and cybersecurity). Our research delivers creative computing solutions to industrial and societal challenges, with applications including healthcare, overseas development, education, ecology, finance and manufacturing.

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Doctoral research programmes (PhDs) take a proud place in the world-class research environment and community at Brunel. PhD students are recognised and valued by their supervisors as an essential part of their departments and a key component of the university's overall strategy to develop and deliver world-class research.

A PhD programme is expected to take 3 years full-time or 6 years part-time, with intakes starting in January, April or October.

The general University entrance requirement for registration for a research degree is normally a First or Upper Second Class Honours degree (1st or 2:1) or an international equivalent. A Masters degree is a welcome, but not required, qualification for entry.

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Excellent research support and training

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