Dr Jitender Cheema
Computational and Systems Biology
The focus of Jitender's work is computational genomics, using advanced skills in data analysis, statistics, machine learning, probabilistic modelling and software development; carrying out research and training in broad areas of genetics and genomics, focused mainly on BIO ISP.
Jitender is currently involved with projects in the increasingly important fields of metagenomics and metatranscriptomics using high performance computing.
Jitender's group are developing novel transcriptomics and metagenomic pipelines in collaboration with bioinformaticians and sequencing teams from Quadram.
The groups have developed novel methods for the analysis and visualisation of community structure using high-throughput metagenomics data.
The group are also currently working on projects involving the de novo genome assembly and transcriptome assembly with Saskia Hogenhout and Jeremy Murray on projects involving transcriptomics data analysis.
Alongside Paul O’Maille’s group, they are developing new computational methodologies to reconstruct catalytic landscapes from partial structure-based combinatorial protein engineering (SCOPE) analyses.
Path analyses on the reconstructed landscapes enabling us to understand potential evolutionary trajectories of enzyme sequences.
They are using linear models, graph theory and the machine learning methods to discover epistatic networks.
With Noel Ellis’s group (ICRISAT), they have developed a new approach to genetic mapping, THREaD Mapper Studio.
The software enables the estimation of visual, global genetic maps that may be integrated visually with genomic sequence.
They're adding THREaD Mapper Studio’s analytical capabilities, most recently for high-throughput genetic mapping datasets consisting of tens of thousands of markers.
Publisher’s version: 10.1016/j.molp.2018.01.008
REVIEW: Epistasis and dominance in the emergence of catalytic function as exemplified by the evolution of plant terpene synthases.
Plant Science 255 p29-38
Publisher’s version: 10.1016/j.plantsci.2016.11.006
Bioinformatics Sep 22 2016 p1-3
Publisher’s version: 10.1093/bioinformatics/btw611
Proceedings of the National Academy of Sciences of the United States of America 27 p3410-3424
Publisher’s version: 10.1105/tpc.15.00461
Proceedings of the National Academy of Sciences of the United States of America 112 p1339013395
Publisher’s version: 10.1073/pnas.1515426112
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