About Me

I am a Ph.D. student in Quantitative and Computational Biology ( QCB Graduate Program ) at Lewis-Sigler Institute for Integrative Genomics, Princeton University. Prior to joining Princeton, I received my Bachelor of Science and Economics from Peking University in 2017, received my Master of Science from Department of Biostatistics at Harvard University in 2019.

Research Interest

My major research interests lie in developing statistical and computational methods to measure complex biological system, especially focusing on

Methodology

Causal Inference

Mixed Effects Modeling

Probabilistic Modeling

Applications

Statistical Genomics

Population Genetics

Molecular Ecology

Awards and Honors

  • The King Peh Kwoh Fellowship awarded by Princeton University, 2020

  • Lewis-Sigler Institute Scholars Award in Quantitative and Computational Biology, awarded by Lewis-Sigler Institute, Princeton University, 2019

  • Outstanding Graduate of Beijing as a Bachelor (top 1 in 30), awarded by the Beijing Municipal Commission of Education, 2017

  • Excellent Graduate who has demonstrated outstanding performance, awarded by Peking University, 2017

  • UCLA Cross-disciplinary Scholars in Science and Technology Award in recognition of outstanding research and presentation skills, awarded by University of California, Los Angeles, 2016

  • National Scholarship (top 2 in 1000) awarded twice by Ministry of Education of the People’s Republic of China, 2016 & 2015

  • Merit Student Pacemaker (top 1 in 30) awarded twice by Peking University, 2016 & 2015

  • Wusi Scholarship awarded by Peking University, 2014

Publications

  • [7] Su Z, Wen D, Gu AZ, Zheng Y, Tang Y, and Chen L. (2022) Industrial effluents boosted antibiotic resistome risk in coastal environments [J]. Environment International. 2023 Jan. DOI:10.1016/j.envint.2022.107714

  • [6] Tang Y and Storey JD. (2022) On the polygenic trait model in population-based human genetics studies: What is random and what is fixed [C]. The 72nd Annual Meeting of The American Society of Human Genetics. 2022 Sep. Reviewer’s Choice Abstract Award (PDF)

  • [5] Tang Y, Dai T, Su Z, Hasegawa K, Tian J, Chen L, and Wen D. (2020) A tripartite microbial-environment network indicates how crucial microbes influence the microbial community ecology [J]. Microbial Ecology. 2019 Aug. DOI:10.1007/s00248-019-01421-8

  • [4] Zhao M, Tang Y, Kim H, and Hasegawa K. (2018) Machine learning with k-means dimensional reduction for predicting survival outcomes in patients with breast cancer [J]. Cancer Informatics. 2018 Nov. DOI:10.1177/1176935118810215

  • [3] Dai T, Zhang Y, Ning D, Su Z, Tang Y, Huang B, Mu Q, and Wen D. (2018) Dynamics of sediment microbial functional capacity and community interaction networks in an urbanized coastal estuary [J]. Frontiers in Microbiology. 2018 Nov. DOI:10.3389/fmicb.2018.02731

  • [2] Su Z, Dai T, Tang Y, Tao Y, Huang B, Mu Q, and Wen D. (2018) Sediment bacterial community structures and their predicted functions implied the impacts from natural processes and anthropogenic activities in coastal area [J]. Marine Pollution Bulletin. 2018 Apr. DOI:10.1016/J.MARPOLBUL.2018.04.052

  • [1] Dai T, Zhang Y, Tang Y, Bai Y, Tao, Y, Huang B, and Wen D. (2016) Identifying the key taxonomic categories that characterize microbial community diversity using full-scale classification: a case study of microbial community in the sediments of Hangzhou Bay [J]. FEMS Microbiology Ecology. 2016 Oct. DOI:10.1093/femsec/fiw150

Teaching

Princeton University

QCB508 / QCB408 / Foundations of Statistical Genomics

Course ID: QCB 508 / QCB 408 

Title: Foundations of Statistical Genomics

Semester: 2022 Spring & 2023 Spring

Instructor: Dr. John D. Storey

My Role: Assistant in Instruction
3.1 Course Website: Canvas
3.2 Notes and Office Recap: Notes

Harvard University

STAT215 / STAT115 / BST282 / Introduction to Computational Biology and Bioinformatics

Course ID: STAT 215 / STAT 115 / BST 282

Title: Introduction to Computational Biology and Bioinformatics

Semester: 2019 Spring

Instructor: Dr. X. Shirley Liu

My Role: Teaching Assistant
2.1 Course Website: Canvas
2.2 Evaluation: Students’ comments about Prof. Liu and me

2.3 Chapters Instructed by Me:
Lab 5: Bioinformatic Tools for RNA-seq Analysis, DESeq2, and Cluster Computing ( video and material )
Lab 6: Single Cell RNA-seq Analysis and Optimizing I/O Performance on the Cluster ( video 1, video 2 and material )
Lab 7: ChIP-seq data analysis, Bedtools, UCSC Genome Browser, Cistrome and Odyssey ( video and material )
Lab 8: BETA, VCF, ChIP-seq Motifs Analysis ( video and material )
Lab 9: Hidden Markov Model and TCGA Data ( video 1, video 2 and material )
Lab 10: GWAS, HaploReg, RegulomeDB, Regression, and Feature Selection ( video and material )

BST215 / Linear and Longitudinal Regression

Course ID: BST 215

Title: Linear and Longitudinal Regression

Semester: 2018 Summer

Instructor: Dr. Garrett Fitzmaurice

My Role: Teaching Assistant
1.1 Course Website: Canvas
1.2 Evaluation: Students’ comments about Prof. Fitzmaurice and me