Dr Irina Mohorianu, Head of Bioinformatics/Scientific Computing at the CSCI, has been awarded a Turing Fellowship in Computer Science (Machine Learning and Bioinformatics).
Irina’s background in Computer Science was streamlined after she finished her BSc (hons), towards Applied Data Science (Machine Learning and Bioinformatics). During her PhD she studied small non-coding RNAs (sRNAs), first in plants and then in animal systems, too. Soon after completing the first year of post-doc, she was awarded a BBSRC grant on which she was Researcher Co-I. While working on this project she started to integrate mRNA /sRNA expression and became interested in Gene Regulatory Networks (GRNs). She also continued working on developing new methods for the UEA sRNA Workbench.
After her post-doc, she was briefly Bioinformatics Lead at the Oxford Vaccine Group (Department of Paediatrics, School of Medical Sciences, Oxford University) and Lecturer in Computer Science at University College, Oxford, teaching Imperative Programming, Algorithms and Machine Learning.
Here at the Cambridge Stem Cell Institute, she is Head of Bioinformatics & Scientific Computing; she leads a team of Bioinformaticians, (The Core Bioniformatics Group at the CSCI) who develop new Machine Learning & AI methods and also support the CSCI PIs with data analyses. Through her collaborations (both within the University of Cambridge and the community) she aims to understand the intricacies of the underlying GRNs, across time or spatial series and across modalities through analyses of bulk and single cell multi-omics datasets. Integrative analyses are also combined with imaging approaches intertwined with other high throughput measurements. The training of future bioinformaticians, with various backgrounds, is also an important pillar of her group; she is lecturer/ tutor on various modules, with a significant Machine Learning/ Data Science/ Information Theory component.
Starting in October 2021, her research which supports the Turing fellowship, focusses on the characterisation of Gene Regulatory Networks from multi-omics, single cell perspectives using (supervised and unsupervised) Machine Learning methods.
Dr Mohorianu says:
"I am happy to have received a Turing Fellowship in Computer Science – current research done in the Core Bioinformatics group already relies heavily on novel feature selection methods (feamiR) that enhance known classifiers and on an in-depth understanding of unsupervised, clustering outputs (clustAssess). I am looking forward to more collaborations with the CSCI PIs."