实验室研究方向主要集中在利用高通量的各类-OMIC生物组学大数据,结合生物医学知识,通过计算信息学开发新的生物信息学、计算生物医学方法,去深入了解复杂型疾病的分子机制。 主要研究工作是集成不同的脑基因遗传和表型数据,应用和开发新的分析、数据挖掘方法,通过多维度数据去阐明大脑生物网络。重点集中在利用基因转录组数据等高通量组学数据, 利用网络生物学的方法来了解人类大脑的转录组结构,把有遗传性精神疾病的风险因子,大脑的电路和分子功能,及人类和体内外实验模型系统,有效及系统性关联起来。 目标是开发神经系统和精神疾病,如自闭症、精神分裂症、双向情感障碍和强迫症等的有效疗法。

The main research effort of the lab has been the development and application of new analytic methods that elucidate the underlying network organization in multi-dimensional -omic data, permitting integration of genomic and genetic data with phenotype data on a large scale. One area of basic investigation has been in the analysis of transcriptome data where we use network biology approaches to understand brain transcriptome organization, which connects genetic risk for neuropsychiatric diseases to brain circuitry and molecular function both in humans, and in vitro and in vivo model systems. The goal is to develop effective therapeutics for neurologic and psychiatric disorders, such as autism, schizophrenia, bipolar and obsessive-compulsive disorder (OCD).


实验室研究领域(Research Area)

生物信息学/计算生物学 在复杂型疾病及临床的应用,及生物组学和医学大数据挖掘与分析
Bioinformatics, Computational biology, Machine learning & statistical inference on large high-throughput datasets

实验室科研方向  (Current research projects)


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