Haiyan Huang, PhD
Affiliated with Center for Computational Biology
& Graduate Group in Biostatistics
University of California, Berkeley
CA, 94720, USA
AT stat DOT berkeley DOT edu
· Study Group on Deep Learning [Link]
· Ongoing Projects [Link]
Current Students & Postdocs & Visitors:
· Tom Hu (PhD, Biostatistics)
· Shuni Li (PhD, Statistics)
· Aidan McLoughlin (PhD, Biostatistics)
· Seraphina Shi (PhD, Biostatistics)
· Huong Vu (PhD, Statistics)
· Andy Shen (PhD, Statistics)
Former Graduate Students:
· Melinda Siew-leng Teng, PhD, 2007 Summer (Thesis Title: Statistical methods in integrative analysis of gene expression data with applications to biological pathways; Current Position: Associate Director at Pharmacyclics, an AbbVie Company)
· Na Xu, PhD, 2008 summer, co-advised by Prof. Peter Bickel (Thesis Title: Transcriptome Detection by Multiple RNA Tiling Array Analysis and Identifying Functional Conserved Non-coding Elements by Statistical Testing; Current Position: Statistician, Genentech, Inc.)
· Kyungpil Kim, PhD, 2013 (Thesis Title: Application of Statistical Methods to Integrative Analysis of Genomic Data; Current Position: Postdoctoral Research Fellow, Children’s Hospital Oakland Research Institute)
· Daisy Yan Huang, PhD (Thesis Title: Overcoming the Small Sample Size Challenge in Differential Gene Expression Analysis Studies; Current Position: Lecturer, Princeton University)
· Jingyi Jessica Li, PhD, 2013, co-advised by Prof. Peter Bickel (Thesis Title: Statistical Methods for Analyzing High-throughput Biological Data; Current Position: Assistant Professor, Department of Statistics, UC Los Angeles)
· Y.X. Rachel Wang, PhD, 2015, co-advised by Prof. Peter Bickel (Thesis Title: Problems in Network Modeling: Estimating Edges and Community Detection; Current Position: faculty member, School of Mathematics and Statistics, University of Sydney, Australia)
· Christine Ho, PhD, 2016 Winter, co-advised by Prof. Elizabeth Purdom (Thesis Title: Statistical Modeling and Analysis for Biomedical Applications; Current Position: Data Scientist, Pandora)
· Funan Shi, PhD, 2018 (Thesis Title: High Dimensional Statistical and Computational Methods for Knowledge Discovery and Data Mining in Biomedical Data; Current Position: Quantitative Analyst, Google)
· Courtney Schiffman, PhD, 2019, co-advised by Professor Sandrine Dudoit (Thesis Title: The Role of Exploratory Data Analysis and Pre-processing in Omics Studies; Current Position: Biostatistician, Genentech, Inc.)
· Calvin Chi, PhD, 2020, co-advised by Professor Lisa Barcellos (Thesis Title: Statistical and Computational Methods in Epidemiological and Pharmacogenomic Studies: from Application to Method Development; Current Position: Data Analyst, Amazon.)
· Zoe Vernon, PhD, 2021, co-advised by Professor Peter Bickel (Thesis Title: Methodology development in medical and genomics data; Current Position: Data Analyst, Team of Oklahoma City Thunder, NBA League)
· Yun Zhou, PhD, 2021, (Thesis Title: Statistical Learning Methods to Identify Latent Patterns in Sequential and High-dimensional Biological Data; Current Position: Data Analyst, Amazon.)
· Yuting Ye, PhD, 2021, co-advised by Professor Peter Bickel (Thesis Title: Decision Making on Noisy Data with Additional Knowledge; Current Position: Assistant Professor, Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China)
· Hua Chen, Master 2008 (Thesis Title: Bayesian Method for Multi-Loci Association Study of Human Disease; Position right after graduation: Research fellow, Harvard University)
· Ling Meng, Master 2009 (Thesis Title: Learning Algorithm and Model Selection for Protein-Protein Interaction Inference in Arabidopsis; Position right after graduation: Research Fellow, UC Berkeley)
· Harold Pimentel, Master 2013 (Thesis Title: Biclustering as an Extension of Sparse Canonical Correlation Analysis; Current Position: Postdoctoral Research Fellow, UCSF)
· Courtney Schiffman, Master 2016 (Thesis Title: Single Cell RNA-Seq Study: A Study on Normalization and Sub-Population Identification Techniques; Current Position: Student in Biostatistics PhD Program, UC Berkeley)
· Yuting Ye, Master 2017 (Thesis Title: Testing and Diagnosis of Neurological Disorders based on Neuroimaging; Current Position: Student in Biostatistics PhD Program, UC Berkeley)
· Ci-Ren Jiang, Postdoc Sept 2009 – Aug 2010 (Current Position: (Tenured) Associate Research Fellow of the Institute of Physics, Academia Sinica, Taipei, Taiwan)
· Qunhua Li, Postdoc Sept 2008 – July 2011, co-advised by Professor Peter Bickel (Current Position: Associate Professor, Department of Statistics, Penn State University)
· Hao Xiong, Postdoc Jan 2012 – Dec 2012, co-advised by Professor Peter Bickel
· Ke Liu, Postdoc Mar 2015 – Mar 2018, co-advised by Professor Peter Bickel and Professor Marisa Wong Medina (Current Position: Research Associate, Department of Pediatrics and Human Development, Michigan State University)
· Prof. Ting Xu, Chemistry & Materials Science and Engineering, UC Berkeley
· Prof. Bin Chen, Pediatrics and Human Development, Michigan State University
· Prof. Peter Bickel, Statistics, UC Berkeley
· Prof. Amy Herr, Bioengineering, UC Berkeley
STAT 152: Survey Sampling (Falls 2003 – 2006)
BIOE/STAT C141: Statistics for Bioinformatics (Springs 2004 – 2008)
STAT 131A: Statistical Inferences for Social and Life Scientists (Spring 2009)
STAT 157: Seminar on Topics in Probability and Statistics (Fall 2009)
STAT 133: Concepts in Computing with Data (Spring 2013)
STAT 158: Experimental Design (Spring 2018)
STAT 200B: Introduction to Probability and Statistics at an Advanced Level (Springs 2006, 2007, 2011, 2012)
STAT 201B: Introduction to Probability and Statistics at an Advanced Level (Falls 2013, 2014, 2016, 2017, 2018, 2019, 2021)
STAT 215A: Statistical Models: Theory and Application (Fall 2011)
STAT 215B: Statistical Models: Theory and Application (Spring 2017)
STAT 210A: Theoretical Statistics (Falls 2008 – 2010)
STAT 246: Statistical Genetics (Spring 2009; co-teaching with Prof. S Dudoit)
STAT C245E/F: Statistical Genomics (Springs 2010, 2012, 2013, 2014, 2021; co-teaching with Prof. S Dudoit, Prof. R Nielson and Prof. B Brown.)
STAT 272: Statistical Consulting (Fall 2010, Spring 2014, Fall 2014, Spring 2015, Spring 2016)
STAT 375: Professional Preparation: Teaching of Probability and Statistics (Falls 2013, 2014)
Google Scholar Citations [Link]
* Corresponding or Co-corresponding author(s)
1. Mcloughlin A, Huang H. Shared Differential Expression-Based Distance Reflects Global Cell Type Relationships in Single-Cell RNA Sequencing Data. Journal of Computational Biology. 2022 Jul 6. PMID: 35793527 [Link]
2. Vlassakis J, Hansen LL, Higuchi-Sanabria R, Zhou Y, Tsui CK, Dillin A, Huang H, Herr AE. Measuring expression heterogeneity of single-cell cytoskeletal protein complexes. bioRxiv. 2021 Jan 1:2020-09. Nature Communications. Conditionally Accepted. [Link]
3. Fang X, Gan HL, Holmes S, Huang H, Peköz E, Röllin A, Tang W (2021). Arcsine laws for random walks generated from random permutations with applications to genomics. Journal of Applied Probability. 2021 Dec;58(4):851-67. [Link]
4. Chi C, Ye Y, Chen B, Huang H (2021). Bipartite graph-based approach for clustering of cell lines by gene expression-drug response associations. Bioinformatics. 2021 Mar 3. [Link]
5. Ahn S, Huang H. Multiregion Sequence Analysis to Predict Intratumor Heterogeneity and Clonal Evolution (2021). In Deep Sequencing Data Analysis 2021 (pp. 283-296). Humana, New York, NY. [Link]
6. Wang YR, Li L, Li JJ, Huang H (2021). Network modeling in biology: statistical methods for gene and brain networks. Statistical Science. 2021 Feb;36(1):89-108. [Link]
7. Geldert A, Huang H, Herr AE (2020). Probe-target hybridization depends on spatial uniformity of initial concentration condition across large-format chips. Scientific reports. 2020 May 29;10(1):1-2. [Link]
8. Jiang T, Hall A, Eres M, Hemmatian Z, Qiao B, Zhou Y, Ruan Z, Couse AD, Heller WT, Huang H, de la Cruz MO, Rolandi M, Xu T (2020). Single-chain heteropolymers transport protons selectively and rapidly. Nature. 2020 Jan;577(7789):216-20. [Link]
9. Liu K, Theusch E, Zhou Y, Ashuach T, Dose AC, Bickel PJ*, Medina MW*, Huang H* (2019). GeneFishing to reconstruct context specific portraits of biological processes. Proceedings of the National Academy of Sciences. 2019 Sep 17;116(38):18943-50. [Link]
10. Chang M, Edmiston EK, Womer FY, Zhou Q, Wei S, Jiang X, Zhou Y, Ye Y, Huang H, Zuo XN, Xu K (2019). Spontaneous low-frequency fluctuations in the neural system for emotional perception in major psychiatric disorders: amplitude similarities and differences across frequency bands. Journal of psychiatry & neuroscience: JPN. 2019 Mar; 44(2):132.
11. Hu ZT, Ye Y, Newbury PA, Huang H*, Chen B* (2019). AICM: A Genuine Framework for Correcting Inconsistency Between Large Pharmacogenomics Datasets. In PSB 2019 (pp. 248-259).
12. Jiang H, Sohn L, Huang H*, Chen L* (2018). Single Cell Clustering Based on Cell-Pair Differentiability Correlation and Variance Analysis. Bioinformatics. 2018 May 16;1:11.
13. Kang CC, Ward TM, Bockhorn J, Schiffman C, Huang H, Pegram MD, Herr AE (2018). Electrophoretic cytopathology resolves ERBB2 forms with single-cell resolution. NPJ precision oncology. 2018 Mar 22;2(1):10.
14. Lin JM, Kang CC, Zhou Y, Huang H, Herr AE, Kumar S (2018). Linking invasive motility to protein expression in single tumor cells. Lab on a Chip. 2018;18(2):371-84.
15. Pimentel H, Hu ZT, Huang H* (2018). Biclustering by Sparse Canonical Correlation Analysis. Quantitative Biology. 2018 Mar 1;6(1):56-67.
16. Wang YXR, Liu K, Theusch E, Rotter JI, Medina MW, Waterman M*, Huang H* (2017). Generalized correlation measure using count statistics for gene expression data with ordered samples. Bioinformatics. 2017 Oct 12;34(4):617-24.
17. Huang H*, Yu B* (2017). Data wisdom in computational genomics research. Statistics in Biosciences. 2017; 9(2):646-61.
18. Chang M, Womer FY, Edmiston KE, Bai C, Zhou Q, Jiang X, Wei S, Wei Y, Ye Y, Huang H, He Y, Xu K, Tang Y, Wang F (2017). Neurobiological Commonalities and Distinctions Among Three Major Psychiatric Diagnostic Categories: A Structural MRI Study. Schizophrenia Bulletin. 2017 Jun 13.
19. Shi F, Huang H* (2017). Identifying Cell Subpopulations and Their Genetic Drivers from Single-Cell RNA-Seq Data Using a Biclustering Approach. Journal of Computational Biology. 2017 Jul 1;24(7):663-74.
20. Schiffman C, Lin C, Shi F, Chen L, Sohn L, Huang H* (2017). SIDEseq: A Cell Similarity Measure Defined by Shared Identified Differentially Expressed Genes for Single-cell RNA Sequencing data. Statistics in Biosciences. June 2017, Volume 9, Issue 1, pp 200–216.
21. Sinkala E, Sollier-Christen E, Renier C, Rosàs-Canyelles E, Che J, Heirich K, Duncombe TA, Vlassakis J, Yamauchi KA, Huang H, Jeffrey SS, Herr AE (2017). Profiling protein expression in circulating tumour cells using microfluidic western blotting. Nature Communications, Mar 23;8:14622.
23. National Research Council Committee on Predictive-Toxicology Approaches for Military Assessments of Acute Exposures (2015). “National Academy of Sciences: Application of Modern Toxicology Approaches for Predicting Acute Toxicity for Chemical Defense.” Washington, DC: The National Academies Press. (I served as an NRC Committee member)
· This paper is selected for issue highlight by PNAS: http://www.pnas.org/content/107/15/6553.full.pdf+html (it is under the title "Gene databases mined for diagnoses").
· This paper has been selected for Faculty of 1000 Biology (http://www.f1000biology.com) and evaluated by Dr. Russ Altman from Stanford University: http://www.f1000biology.com/article/id/3925957. (Faculty of 1000 Biology is an award-winning online service that highlights and evaluates the most interesting papers published in the biological sciences, based on the recommendations of over 2000 of the world's top researchers.)
· This paper has also been reported in the following news reports:
· GenomeWeb daily news. “Team Develops Proof-of-Principle Diagnostic Database for Applying Public Gene Expression Data”. March 22, 2010.
· National Cancer Institute. Research News. “Mathematical Modeling Turns Gene Expression Data into Disease Diagnostics” http://physics.cancer.gov/news/2010/april/po_news_b.asp
· Biocentury and Nature publishing group. “GEO: world of diagnostic potential,” Haas, M.J. SciBX 3(14); April 8, 2010
(authors ordered alphabetically)
(authors ordered alphabetically)
#Joint first authors