Haiyan Huang
Affiliations: | Statistics | University of California, Berkeley, Berkeley, CA, United States |
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"Haiyan Huang"
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| Liu K, Theusch E, Zhou Y, et al. (2019) GeneFishing to reconstruct context specific portraits of biological processes. Proceedings of the National Academy of Sciences of the United States of America |
| Schiffman C, Lin C, Shi F, et al. (2017) SIDEseq: A Cell Similarity Measure Defined by Shared Identified Differentially Expressed Genes for Single-Cell RNA sequencing Data. Statistics in Biosciences. 9: 200-216 |
| Wang YXR, Liu K, Theusch E, et al. (2017) Generalized correlation measure using count statistics for gene expression data with ordered samples. Bioinformatics (Oxford, England) |
| 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 : a Journal of Computational Molecular Cell Biology. 24: 663-674 |
| Rache Wang YX, Jiang K, Feldman LJ, et al. (2015) Inferring gene–gene interactions and functional modules using sparse canonical correlation analysis Annals of Applied Statistics. 9: 300-323 |
| Wang YX, Waterman MS, Huang H. (2014) Gene coexpression measures in large heterogeneous samples using count statistics. Proceedings of the National Academy of Sciences of the United States of America. 111: 16371-6 |
| Boyle AP, Araya CL, Brdlik C, et al. (2014) Comparative analysis of regulatory information and circuits across distant species. Nature. 512: 453-6 |
| Gerstein MB, Rozowsky J, Yan KK, et al. (2014) Comparative analysis of the transcriptome across distant species. Nature. 512: 445-8 |
| Li JJ, Huang H, Bickel PJ, et al. (2014) Comparison of D. melanogaster and C. elegans developmental stages, tissues, and cells by modENCODE RNA-seq data. Genome Research. 24: 1086-101 |
| Wang YX, Huang H. (2014) Review on statistical methods for gene network reconstruction using expression data. Journal of Theoretical Biology. 362: 53-61 |