Dr Hung-Ming Lai

Former PhD Student

Feature Selection for Large Scale Cancer Associated Gene Expression Profiling Data

Hung-Ming's main research is focused on developing a framework for high-throughput gene signatures for a certain disease phenotype prediction using feature selection techniques. The framework is aimed at providing biologically meaningful gene sets having good classification performance and stable selection, and will be expected to signature identification derived from multi �omics heterogeneous profiles. His research interests include Microarray/Next Generation Sequencing Data Analysis, High Throughput Gene/Probe Selection and Preprocessing, Genome Wide miRNA-mRNA Interactions, and Cancer Genomics.

Presentations, Seminars and Posters

  • Hung-Ming Lai (7th Feb 2014) Feature Selection and Cancer Classification. Presentation at Seminar on Bioinformatics, King's College London (Guy Campus), London.
  • Hung-Ming Lai (12th Dec 2013) Feature Selection for Microarray-based Cancer Classification. Presentation at Seminar on Computational Modelling and Simulation, Middlesex University, London.
  • Hung-Ming Lai, Andreas Albrecht and Kathleen Steinh�fel (6th Dec 2013) A Study of Performance Measures on Large Scale Gene Selection. Abstract Presented at the PhD Symposium in Computational Biology & Innovation, Dublin.

Personal webpage


hung-ming.lai [at] kcl.ac.uk