Projects per year
Personal profile
Research interests
Biology computes... from individual cells deciding how to differentiate during development, to social insects coordinating their actions when scavenging for food; the ability to perform complex computations and process information enables life.
The Biocompute Lab explores the molecular-scale mechanisms that individual cells and groups of cells use to make sense of their world. We apply tools and methods from the field of synthetic biology to create new living systems from the ground-up. By studying these artificial systems using novel techniques we are developing based on sequencing, microfluidics and computational modelling, we aim to better understand the rules governing how biological parts are best pieced together to perform useful computations. Understanding the computational architecture of cells opens new ways of reprogramming them to tackle problems spanning the sustainable production of materials to novel therapeutics. It also provides key insights into how biology controls the complex processes and structures sustaining life.
External positions
Postdoctoral Associate, Massachusetts Institute of Technology
Apr 2014 → Dec 2015
Marie Curie Fellow/Associate Scientist, DSM Biotechnology Center
Apr 2012 → Apr 2014
Keywords
- synthetic biology
- systems biology
- networks
- biotechnology
- sequencing
- computational biology
- translation
- transcription
- visualisation
- biodesign
- biometrology
- collective behaviours
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
8079 BrisEngBio Pilot Project: Nanopore-based physiological monitoring of yeast for bioprocess optimisation
1/08/22 → 31/01/24
Project: Research
-
-
Engineered orthogonal ribosomes for programmable protein modification
1/01/22 → 31/12/22
Project: Research
Research output
-
Bridging the gap between mechanistic biological models and machine learning surrogates
Gherman, I. M., Marucci, L., Gorochowski, T. E., Abdallah, Z. S., Grierson, C. S. & Pang, W., 20 Apr 2023, In: PLoS Computational Biology. 19, 4, p. e1010988 e1010988.Research output: Contribution to journal › Article (Academic Journal) › peer-review
Open Access1 Citation (Scopus) -
Design and Analysis of Massively Parallel Reporter Assays Using FORECAST
Gilliot, P-A. M. A. & Gorochowski, T. E., 2023, Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology. Methods in Molecular Biology. Vol. 2553. p. 41-56 16 p. (Methods in Molecular Biology; vol. 2553).Research output: Chapter in Book/Report/Conference proceeding › Chapter in a book
-
Effective design and inference for cell sorting and sequencing based massively parallel reporter assays
Gilliot, P-A. M. A. & Gorochowski, T. E., 1 May 2023, In: Bioinformatics. 39, 5, btad277.Research output: Contribution to journal › Article (Academic Journal) › peer-review
Open Access