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Kai Wang, PhD
Kai Wang
Scientist

Dr. Wang's research focuses on the development of bioinformatics methods to improve the understanding of the genetic basis of human diseases, and the integration of electronic health records and genomic information to facilitate genomic medicine on scale.

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Dr. Wang's research aims to develop novel genomics and bioinformatics methods to improve the diagnosis, treatment, and prognosis of rare diseases, to ultimately facilitate the implementation genomic medicine on scale. His research can be divided into several areas. First, Dr. Wang and his lab are developing analytical pipelines for whole genome and whole exome sequencing data, all the way from FASTQ files to biological insights. Some examples of computational tools used in the lab include SeqMule, ANNOVAR, Phenolyzer, SeqHBase, and InterVar. These approaches facilitate a better understanding of the functional content and clinical insights from sequencing data.

Dr. Wang and his team are also developing genomic assays and methods to analyze long-read data, such as those generated from linked-read sequencing, optical mapping, PacBio, and Nanopore sequencing. These methods help them identify causal genetic variants on cases that failed to be diagnosed by traditional whole genome/exome sequencing approaches, and help map aberrant DNA modifications such as methylations in tissues from patients in comparison to controls. Some examples of computational tools use by the lab for this research approach include RepeatHMM, NextSV, LongSV, LinkedSV, NanoMod, and DeepMod.

Finally, Dr. Wang is developing data mining approaches from clinical phenotypic information in Electronic Health Records (EHR) to correlate genotype and phenotype together, and better understand the phenotypic heterogeneity of inherited diseases. Some examples of computational tools the lab employs include EHR-Phenolyzer, SparkText, Doc2HPO, and Phen2Gene, which use natural language processing on clinical notes to predict possible genetic syndromes and candidate genes.

Titles and Academic Titles

Scientist

Associate Professor of Pathology and Laboratory Medicine

Publication Highlights

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