Dr. Zhao conducted his Postdoc research in the Department of Biochemistry and Molecular Biology at Pennsylvania State University. In 2008, he was appointed as a research associate at Center for Comparative Genomics and Bioinformatics in the same university.He joined Beijing Institutes of Life Science, Chinese Academy of Sciences (BIOLS) in Dec. 2010 as Principal Investigator.His major research interests are developing bioinformatic approaches for understanding human microbiome and noncoding RNAs.Dr. Zhao was recipient of Special Prize of CAS President Award of CAS (2006), National Marine Science & Technology Award (1st Prize, 2012), National Science Fund for Excellent Young Scholars (2017), CAS Award for Outstanding Mentors (2017) He was sponsored by grants from the National Natural Science Foundation of China, National Key R&D Program, and the Strategic Priority Research Program of the Chinese Academy of Sciences.

(1) Metagenomics and Human health

High throughput sequencing technologies enable us to sequence uncultured microbes sampled directly from their habitats, which are expanding and transforming our view of the microbial world. However, extracting meaningful information from tens of millions of very short sequences brings a serious challenge to computational biologists. Current available computational methods for metagenomics are developed based on either low throughput data or a few well-studied microbiomes, which encounter extensive difficulties when applied to novel environmental communities. One of the major challenges is how to assemble and functionally annotate metagenomic sequences without closely related reference genomes. We aim to develop a new strategy to assemble metagenomic sequences by combining shotgun sequencing and single-cell based sequencing approaches, and also to design new algorithms to annotate metagenomes without closely related reference sequences. In addition, we will use parallel computing technologies to set up an integrated platform for metagenomic studies, and to combine the power of genomics, bioinformatics and systems biology to understand human microbiomes. 

(2) Bioinformatics in noncoding RNAs

Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals, and some of them function as microRNA sponges. A comprehensive detection of circRNAs from high throughput RNA transcriptome data is an initial and crucial step to study the biogenesis and function of circular RNAs. We proposed a novel chiastic clipping signal based algorithm to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. In addition, by combining a novel computational algorithm with long-read sequencing data as well as experimental validation, we for the first time comprehensively investigated internal components of circRNAs in ten human cell lines and 62 fruit fly samples. To further explore the diversity and function of circRNAs, an all-around computational tool is urgently required to dig out these cryptic molecules from high throughput but fragmented transcriptome data. We will develop an integrated platform for circRNA identification, assembly and functional annotation.