Faculty Profile

Dr. Aziz Mithani

Associate Professor

Department Of Biology

Dr Aziz Mithani started as a computer scientist and received his Masters in Computer Sciences from FAST-NU, Karachi before going to University of Cambridge, UK where he did MPhil in Computational Biology. In summer 2006, he went to Harvard Medical School for a research internship in Paulsson Lab at Department of Systems Biology. Dr Mithani received his DPhil in Statistics (Computational Biology) from University of Oxford, UK in November 2009 under the supervision of Prof Jotun Hein and Dr Gail Preston. His dissertation focused on modelling the evolution and analysis of the properties of metabolic networks. Subsequently, Dr Mithani joined Harberd Lab at the Department of Plant Sciences, University of Oxford, UK as a postdoctoral research associate where he worked for two years on the evolution of bread wheat. 

His research interests include the application of computational and mathematical methods in the area of modern biology. Specifically, he is interested in the development of computational tools and techniques for the analysis of next-generation sequencing data and biological networks, and to investigate how different organisms function and evolve over time.

Title Publication Author Year
Genome-wide RNAi screen in Drosophila reveals Enok as a novel trithorax group regulator Epigenetics and Chromatin Umer Z., Akhtar J., Khan M.H.F., Shaheen N., Haseeb M.A., Mazhar K., Mithani A., Anwar S., Tariq M. 2019
DNA mismatch repair preferentially protects genes from mutation Genome Research Belfield E.J., Ding Z.J., Jamieson F.J.C., Visscher A.M., Zheng S.J., Mithani A., Harberd N.P. 2018
HANDS2: Accurate assignment of homoeallelic base-identity in allopolyploids despite missing data Scientific Reports 2016
Local adaptation is associated with zinc tolerance in Pseudomonas endophytes of the metal-hyperaccumulator plant Noccaea caerulescens Proceedings of the Royal Society B: Biological Sciences Fones H.N., McCurrach H., Mithani A., Smith J.A.C., Preston G.M. 2016
Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat BMC Genomics 2014
Microarray-based ultra-high resolution discovery of genomic deletion mutations BMC Genomics Belfield E.J., Brown C., Gan X., Jiang C., Baban D., Mithani A., Mott R., Ragoussis J., Harberd N.P. 2014
Microarray-based optimization to detect genomic deletion mutations Genomics Data 2014
Environmentally responsive genome-wide accumulation of de novo Arabidopsis thaliana mutations and epimutations Genome Research Jiang C., Mithani A., Belfield E.J., Mott R., Hurst L.D., Harberd N.P. 2014
HANDS: A tool for genome-wide discovery of subgenome-specific base-identity in polyploids BMC Genomics Mithani A., Belfield E.J., Brown C., Jiang C., Leach L.J., Harberd N.P. 2013
Erratum: ROS-mediated vascular homeostatic control of root-to-shoot soil Na delivery in Arabidopsis (EMBO Journal (2012) 31 (4359-4370) DOI: 10.1038/emboj.2012.273) EMBO Journal Jiang C., Belfield E.J., Mithani A., Visscher A., Ragoussis J., Mott R., Andrew Smith J., Harberd N.P. 2013
ROS-mediated vascular homeostatic control of root-to-shoot soil Na delivery in Arabidopsis EMBO Journal Jiang C., Belfield E.J., Mithani A., Visscher A., Ragoussis J., Mott R., Smith J.A.C., Harberd N.P. 2012
Genome-wide analysis of mutations in mutant lineages selected following fast-neutron irradiation mutagenesis of Arabidopsis thaliana Genome Research 2012
Regenerant arabidopsis lineages display a distinct genome-wide spectrum of mutations conferring variant phenotypes Current Biology Jiang C., Mithani A., Gan X., Belfield E.J., Klingler J.P., Zhu J.-K., Ragoussis J., Mott R., Harberd N.P. 2011
Comparative analysis of metabolic networks provides insight into the evolution of plant pathogenic and nonpathogenic lifestyles in Pseudomonas Molecular Biology and Evolution Mithani A., Hein J., Preston G.M. 2011
A Bayesian approach to the evolution of metabolic networks on a phylogeny PLoS Computational Biology Mithani A., Preston G.M., Hein J. 2010
Rahnuma: Hypergraph-based tool for metabolic pathway prediction and network comparison Bioinformatics 2009
A stochastic model for the evolution of metabolic networks with neighbor dependence Bioinformatics 2009