Dr Namshik Han
University of Cambridge
Milner Therapeutics Institute
Position: Head of Computational Biology
Personal home page:
Email:
n.han@milner.cam.ac.uk
PubMed journal articles - click here
Dr Namshik Han is pleased to consider applications from prospective PhD students.
Research description:
My role is to lead the computational biology group at the Milner Therapeutics Institute University of Cambridge. I have responsibility to develop and deliver the Milner’s computational biology and bioinformatics strategy. I lead implementation of large scale data analysis which will involve collation and analysis of data from a variety of sources including third-party data, in-house data and publicly generated datasets. The main aim of my group at the Milner is to facilitate access of partner organisations to cutting-edge bioinformatics technology and to develop new computational methods fulfilling the global mission of identifying new or better therapies from the analysis of biological data. This will contribute to the inter-disciplinary environment of the Milner, allowing dynamic translation and validation of findings from in silico to in vitro models, and from one therapeutic area to another. The main activity of the group is the development and application of machine learning, statistical and mathematical approaches to pharmacogenomics and drug discovery, strongly focusing on the use of publicly available big data, and utilising experimental data generated on purpose by the Milner Consortium partner organisations. Projects within the group include (1) identification of new therapeutic targets in a variety of diseases, (2) stratification of patients to improve personalised medicine, (3) prediction of efficacy and safety of new and existing drugs and (4) identification of drug positioning/repositioning opportunities.
Research Programme:
Onco-Innovation
Methods and technologies:
Bioinformatics
Computational modelling
DNA sequencing
Gene expression profiling
Genomics
Metabolomics
Microarray
PCR
Proteomics
Public health
RNAi
Statistical analysis
X-ray crystallography
Other
Tumour type interests:
Brain and central nervous system
Breast
Colorectal
Kidney
Leukemia
Liver
Lung
Melanoma
Oesophagus
Pancreas
Prostate
Stomach
Keywords:
Computational Biology
Bioinformatics
Machine Learning
Drug Discovery
Recent publications:
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Key publications:
Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci
P Amaral*, T Leonardi*, N Han*, E Vire, D K Gascoigne, … and T Kouzarides (2018) Genome Biology
Long non-coding RNA ChRO1 facilitates ATRX/DAXX-dependent H3.3 deposition for transcription-associated heterochromatin reorganization
J Park, H Lee, N Han†, S Kwak, … and E J Cho (2018) Nucleic Acid Research
DDX3X RNA helicase affects breast cancer cell cycle progression by regulating expression of KLF4
E Cannizzaro*, A J Bannister*, N Han†, and T Kouzarides (2018) FEBS Letters
TIGERi: Modeling and visualizing the responses to perturbation of a transcription factor network
N Han§, H Noyes, A Brass§ (2017) BMC Bioinformatics
Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control
I Barbieri*, K Tzelepis*, L Pandolfini*, … N Han†, … G Vassiliou§ and T Kouzarides§ (2017) Nature
FOXM1 and polo-like kinase 1 are co-ordinately overexpressed in patients with gastric adenocarcinomas
M Dibb, N Han†, J Choudhury, … and A D Sharrocks (2015) BMC research notes
Deregulation of the FOXM1 target gene network and its coregulatory partners in oesophageal adenocarcinoma
E F Wiseman, X Chen, N Han†, A Webber, … and A D Sharrocks (2015) Molecular Cancer
The forkhead transcription factor FOXK2 acts as a chromatin targeting factor for the BAP1-containing histone deubiquitinase complex
Z Ji, H Mohammed, … N Han, … and A D Sharrocks (2014) Nucleic acids research
The Forkhead TF FOXM1 Controls Cell Cycle-Dependent Gene Expression through an Atypical Chromatin Binding Mechanism
X Chen, G A Muller, … N Han, … and A D Sharrocks (2013) Molecular and Cellular Biology
Progressive lung cancer determined by expression profiling and transcriptional regulation
N Han*, Z Dol*, O Vasieva, … and J K Field (2012) International Journal of Oncology
The FOXM1-PLK1 axis is upregulated in oesophageal adenocarcinoma
M Dibb, N Han†, J Choudury, … and A D Sharrocks (2012) British Journal of Cancer
Protein kinase C regulates late cell cycle-dependent gene expression
Z Darieva, N Han†, K Doris, B A Morgan, A D Sharrocks (2012) Molecular and Cellular Biology
Ultradian cortisol pulsatility encodes a distinct, biologically import signal
A McMaster, M Jangani, P Sommer, N Han, … and D W Ray (2011) PLoS ONE
Prediction of binding sites in protein-nucleic acid complexes
N Han and K Han (2004) Lecture Notes in Computer Science
Computational approach to structural analysis of protein-RNA complexes
N Han, H Kim, and K Han (2003) Lecture Notes in Computer Science
* Co-first author
§ Co-corresponding author
† Lead bioinformatician
Combining mathematics and biology in computer science can produce new biology. Computational approaches not only ensure implementation of highly elaborated mathematical model using large scale genome-wide datasets generated by the high-throughput experiments, but also practicably analyse and visualize the results from the mathematical modelling process. The computationally derived results provide comprehensive understanding of transcriptional regulatory mechanism. Image courtesy of Namshik Han