Post-Doctorate Research Assistant in Bioinformatics
Steve Kelly Lab, the Department of Plant Sciences
University of Oxford
I develop and apply computational methods which address various biological questions by analysing high-throughput datasets, especially the comprehensive and collective cluster analysis of multiple genome-wide transcriptomic (gene expression) datasets. I handle the entire analysis pipeline including fetching data from repositories, pre-processing and normalisation, differential expression analysis, cluster analysis using the algorithms which I developed, numerical and biological validation, biological reasoning of the results by enrichment tools, comparison with the literature, presenting and discussing results in conferences and meetings with biological/biomedical colleagues or collaborators, drawing hypotheses, writing and submitting manuscripts, and contributing to grant applications.
Currently I work in Steve Kelly’s laboratory at the Department of Plant Sciences at the University of Oxford, within the C4 Rice Project which aims to improve photosynthetic efficiency in rice and thus to enhance crop yields. Click for details.
Previously (Summer 2011 to June 2016), I was in the group of Professor Asoke Nandi at the University of Liverpool as a PhD student, and then moved with him to Brunel University London as a PhD student and then as a research assistant. In that group I worked in the analysis of breast cancer in collaboration with Professor Adrian Harris (The Weatherall Institute of Molecular Medicine (WIMM), the University of Oxford), erythropoiesis in collaboration with Professor David Roberts and colleagues (John Radcliffe Hospital, the University of Oxford), budding yeast, and E. coli bacteria. I also performed preliminary analysis of malarial data in collaboration with Professor Taco Kooij (Radboud University, the Netherlands). Additionally, I participated in the analysis of fMRI brain data with my colleague, Chao Liu, and in collaboration with Professor Elvira Brattico (Aarhus University, Denmark).
During that, I developed a sophisticated framework for the analysis of multiple transcriptomic datasets collectively and almost automatically with the minimum need of manual intervention to set parameters. The framework’s pipeline comprises of two main methods run in order: (1) the unification of clustering results from multiple datasets using external specifications (UNCLES), and (2) the M-N scatter plots technique. The methods are freely available in the R package UNCLES downloadable from here.
I have a published research monograph book, seven journal articles, and fourteen peer-reviewed full-length articles in international conferences’ proceedings.
My CV is available here.