Computational Systems Biologist

Abhinav Mishra

Mechanistic models and scientific software for signalling dynamics, multi-omics and drug response.

I combine mathematical modelling, optimization, Bayesian inference and reproducible scientific computing to study dynamic biological systems, particularly cancer signalling, treatment response and pharmacological processes.

Research focus

From biological mechanism to reproducible computation

01

Dynamic signalling

ODE-based representations of phosphorylation, regulatory networks and time-resolved molecular responses.

02

Cancer & drug response

Mechanistic models of treatment response, pharmacokinetics and coupled biological dynamics.

03

Multi-omics inference

Optimization and Bayesian approaches for extracting dynamic structure from proteomic and molecular measurements.

04

Research software

Testable packages, interoperable models and portable workflows that make computational analyses reusable.

Questions driving my research

Problems I want to understand

  1. How can sparse longitudinal omics measurements constrain mechanistic models without hiding uncertainty?
  2. How can signalling-network dynamics be inferred when prior knowledge and measurements are incomplete?
  3. How can mechanistic and statistical models remain interoperable, inspectable and reproducible?
  4. How can molecular perturbations be connected quantitatively to treatment-response dynamics?

Selected work

A connected modelling portfolio

View all research

Working approach

A traceable path from question to output

  1. 01Biological question
  2. 02Mathematical representation
  3. 03Numerical solution
  4. 04Optimization & inference
  5. 05Interpretation
  6. 06Reproducible output