贾耿介课题组

贾耿介课题组

Gengjie (Jay) Jia Lab

　　课题组长

　　贾耿介，研究员、博导。曾在芝加哥大学从事医学信息学博士后研究，获新加坡国立大学博士、中国科大学士。围绕“慢病风险的精准系统化解析”，通过融合系统生物学、自然语言处理等思路方法而开发多维度健康营养大数据人工智能算法。以第一/通讯（含共同）作者在Nature (2025封面)、Nature Computational Science (2023)、Nature Communications (2022, 2019)期刊发表论文；申请专利2项，获软著9项。入选国家重大人才工程计划（青年）、人社部高层次、广东省珠江人才；成为中国计算生物学与生物信息学专委；主持国自然重大研究计划培育、面上项目等。课题组网站https://www.jialab.org.cn/ 。

研究方向

人口老龄化和不健康饮食等促使多种慢病频发共发。传统慢病风险解析与精准营养研究常忽视疾病异质性与共病复杂性。近些年，以电子病历为代表的健康表型组、基因组、膳食等多维度大数据快速规模化，为克服上述局限提供数据基础，也对算法提出挑战。为此，课题组开发多维健康营养大数据人工智能算法：（1）精准识别疾病异质性：通过电子病历分析实现慢病分型，从基因、体检指标和膳食等维度解析亚型间异同。（2）系统解析多疾病关联：为识别涵盖567种疾病并发信息，构建“疾病空间”表现形式：共病间关联可由两点间距离量化表示。进一步从多效基因、遗传与饮食互作、肠道菌群及膳食纤维多角度解析共病。

　　工作经历

　　2021/1至今中国农业科学院深圳农业基因组研究所，研究员

　　2016/6 – 2020/12 芝加哥大学，博士后

　　2013/1 – 2016/5 CGG公司数据处理分部，地球物理学家

　　教育经历

　　2008/7 – 2013/1 新加坡-麻省理工学院联盟，化学与制药工程博士；

　　2011/4 – 2011/10 瑞士苏黎世联邦理工学院，访问学习；

　　2004/9 – 2008/6 中国科学技术大学，生物学学士。

代表论文

(#co-first, *co-corresponding)

1. Jia, G., He, P., Dai, T. et al. Spatial immune scoring system predicts hepatocellular carcinoma recurrence. Nature 640, 1031–1041 (2025).

2. Zhang, X., Liu, H., Li, Y., Wen, Y., Xu, T., Chen, C., Hao, S., Hu, J., Nie, S., Gao, F., Jia, G. Linking dietary fiber to human malady through cumulative profiling of microbiota disturbance. iMeta, 2025. 4(1): p. e70004(2025).

3.G. Jia#*, Y. Li#, …, X. Gao*, A. Rzhetsky*. The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci. Nature Computational Science (2023).

4 .G. Jia, Zhong, X., Im, H.K. et al. Discerning asthma endotypes through comorbidity mapping. Nature Communications 13, 6712 (2022).

5.G. Jia, Y. Li, H. Zhang, I. Chattopadhyay, A. B. Jensen, D. R. Blair, L. Davis, P. N. Robinson, T. Dahlén, S. Brunak, M. Benson, G. Edgren, N. J. Cox, X. Gao, A. Rzhetsky*, Estimating Heritability and Genetic Correlations from Large Health Datasets in the Absence of Genetic Data, Nature Communications, 10, 5508 (2019). (*corresponding authors)

6.G. Jia, G. Stephanopoulos, R. Gunawan*, Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles, Metabolites, 2 (4), 891–912 (2012).

7.G. Jia, G. Stephanopoulos, R. Gunawan*, Incremental Parameter Estimation of Kinetic Metabolic Network Models, BMC Systems Biology, 6, 142 (2012).

8.G. Jia, G. Stephanopoulos, R. Gunawan*, Parameter Estimation of Kinetic Models from Metabolic Profiles: Two-phase Dynamic Decoupling Method, Bioinformatics, 27 (14), 1964–1970 (2011).

9.B. Chicoine, A. Rivelli, V. Fitzpatrick*, L. Chicoine, G. Jia, A. Rzhetsky, Prevalence of Common Disease Conditions in a Large Cohort of Individuals with Down Syndrome in the United States, Journal of Patient-Centered Research and Reviews, 8(2), 86-97 (2021).

10.X. Zhong*, Z. Yin, G. Jia, D. Zhou, Q. Wei, A. Faucon, P. Evans, E. R. Gamazon, B. Li, R. Tao, A. Rzhetsky, L. Bastarache, N. J. Cox*, Electronic Health Record Phenotypes Associated with Genetically Regulated Expression of CFTR and Application to Cystic Fibrosis, Genetics in Medicine, 22, 1191–1200 (2020).

11.C. Zhang, H. Tu, G. Jia, T. Mukhtar, V. Taylor, A. Rzhetsky, S. Tay*, Ultra-multiplexed Analysis of Single-cell Dynamics Reveals Logic Rules in Differentiation, Science Advances, 5 (2019).

12.G. Jia, R. Gunawan*, Construction of Kinetic Model Library of Metabolic Networks, IFAC Proceedings, 45 (15), 952-957 (2012).

13.G. Jia, G. Stephanopoulos*, Incremental Parameter Estimation and Ensemble Kinetic Modeling of Metabolic Networks, Proceedings of AIChE Annual Meeting (2012).

14.G. Jia, G. Stephanopoulos, R. Gunawan*, Construction of Kinetic Model Library of Metabolic Networks from Dynamic Profiles, 8th International Workshop on Computational Systems Biology (2011).

贾耿介课题组更新于2025年11月

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