We are focused on the annotation of Human Genome and SNP functional analysis, as well as
the development of standards of genomic annotation and related software. Our interests
also include the application of e-Science in life science and the customizable comprehensive
bioinformatics pipeline system built on top of GRID.
Multi-omics analysis of Chinese Medicine effect on the immune microenvironment of cancer and prognostic immune early-warning mechanism.
Our research also includes:
(1) Analysis and prediction of gene transcriptional regulation.
(2) Relationship between multiple SNPs and complex disease.
(3) Bioinformatics in cancer studies.
(4) miRNA prediction and functional analysis.
(5) Multi-omics analysis of single cell data of cancer.
We focus on the public health policy analysis based on the big data of regional Electronic Medical Record(EMR) of different sources. Different machine learning methods have been applied to make better understanding of the population big data. We also use artificial intelligence (AI) and Natural Language Processing (NLP) to analyse the prehospital first aid data in depth.
Also includes:
(1) Population Health big data analysis.
(2) Public health emergency policy.
(3) Health Planning.
Our research focuses on studying the relationship between SNPs and important diseases.
We are now developing a high throughput, low cost SNP genotyping method based on
Gap Ligase Chain Reaction (Gap-LCR) and fluorescent microsphere-based liquid assay.
Developing new methods to mark a large number of gene loci while simple and easy to be used in most laboratories. (Collaborated project)