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Making Sense of Biology Using BioInformatics 

Vision of our Lab

The advances of sequencing and other bio-technologies are revolutionizing our understanding of biology to an unprecedented extent. Our lab aims to take full advantage of these technologies to explore meaningful biological insights from our genomes, both healthy and unhealthy ones. The ultimate goal is to improve the health of every individual with our expertise in Bioinformatics.

Research Interests

Develop algorithms for sequencing data analysis

Although there are many tools available for next-generation sequencing data analysis, the vast volumes of sequencing data which are being generated at a decreasing cost still require more sensitive and specific algorithms to analyze in an efficient manner. The third-generation sequencing (TGS) platforms (PacBio, Oxford nanopore, etc.) can generate reads of thousands of basepairs, which can cover a large proportion of the genome in a haplotype. However, the error rates of the TGS platforms are very high (e.g. ~15% for PacBio), which is extremely challenging for data analysis. But there are many open questions for Bioinformaticians to develop novel methods to overcome the drawbacks and fully exploit the properties of the TGS data. Besides, there are newly developed biotechniques, such as 10X genomics, strand-seq, improved single cell sequencing, etc., which are generating miscellaneous of sequencing data types. We are also interested in providing efficient solutions to deal with these types of data.

Functions and mechanisms of genomic rearrangements

Compared to single nucleotide variants and short indels, genomic rearrangements or structural variations (SVs) can contribute more polymorphisms within species and more divergence between species. However, it is still an open question in terms of the functions and mechanisms of SVs. For example, the observation and hypothesis of chromothripsis is still mysterious. We are interested in in-depth analysis of SVs in a hypothesis-driven manner.

Disease genomics

Disease is an abnormal phenotype. There is a long-lasting complex problem regarding how the genotype (mixing with epigenetic alterations and modifications and environment) determines the phenotype. We are interested in a wide range of questions, for examples, discovering the causing variants, pan-cancer/disease genomics data analysis, integrated data analysis, etc.


We have extensive collaborations around UAB campus, around the country and abroad.