Ming Hu Laboratory

I am now an Assistant Staff at Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation. I am also an Assistant Professor (non-tenure track) at Department of Medicine, Cleveland Clinic Lerner College of Medicine at Case Western Reserve University, an Associate Member of Molecular Oncology Program at Case Comprehensive Cancer Center, and a joint faculty member of Institute for Computational Biology at Case Western Reserve University School of Medicine.

I grew up in Hefei, a beautiful city in China at the foot of the world famous Mountain Huangshan. I got my B.S. in Statistics from University of Science and Technology of China in 2006. I obtained my Ph.D. in Biostatistics from University of Michigan in 2010, under the supervision of Dr. Zhaohui Steve Qin. Before joining Cleveland Clinic, I did three year postdoctoral training (2010 ~ 2013) with Dr. Jun S. Liu at Statistics Department, Harvard University, and was Assistant Professor (2013 ~ 2016) at Department of Population Health, Division of Biostatistics, New York University School of Medicine.


My research interests lie in the development the statistical methods and computation tools, and their applications to genetic and epigenetic studies. My recent work focuses on genome-wide mapping and analysis of chromosome architecture. Currently, I am the PI of NHGRI 2021 Genomic Innovator Award (R35HG011922), the sub-contract PI of the NIH 4D Nucleome Consortium Phase II Grant (UM1HG011585, PI: Ren), and the sub-contract PI of the NHGRI Small Business Innovation Research Grant (R44HG011897, PI: Schmitt).

I have developed data normalization method HiCNorm (PMID: 23023982) which has been widely used in the analysis of genome-wide chromatin interactomic data. I have also developed methods for inferring three-dimensional chromatin organization and its dynamics, detecting long-range chromatin interactions, and jointly analyzing compendium of chromatin interactomic data. I played a key role in the discovery of topologically associating domains (TADs) (PMID: 22495300) and frequently interacting regions (FIREs) (PMID: 27851967). My work on a compendium of chromatin contact maps across 21 human cell lines and primary tissues (PMID: 27851967) has been selected as a “Research Highlight” by Nature Reviews Genetics (PMID: 27956750). I have published a review paper on chromosome architecture in Nature Reviews Molecular Cell Biology (PMID: 27580841). I have developed MAPS, a model-based method to identify long-range chromatin interactions from PLAC-Seq and HiChIP experiments (PMID: 30986246), which as been approved as the production pipeline for PLAC-seq and HiChIP data in the 4D Nucleome project. I have performed the first study of chromatin interactome variations across multiple individuals (PMID: 31779666).

Most recently, I performed integrative analysis of multi-omics data from developing human cortex and discovered super-interactive promoters, which fine-tune transcription in a cell-type-specific manner. This work is published in Nature (PMID: 33057195). I have developed SnapHiC, the first method to identify chromatin loops from single cell Hi-C data, which is published in Nature Methods (PMID: 34446921). I have also developed methods for analyzing ChIP-seq data, bulk cell RNA-seq data and single cell RNA-seq data. As a biostatistician, I have contributed to multiple clinical studies in the area of ophthalmology and emergency medicine.

Ming Hu's latest CV

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Model-based analysis of long-range chromatin interactions from PLAC-Seq and HiChIP experiments
a Bayesian mixture model for clustering droplet-based single cell transcriptomic data from multiple studies

a Dirichlet mixture model for clustering droplet-based single cell transcrip tomic data
(Hi-C Unifying Genomic INterrogator): a genome browser of the integrative analysis of Hi-C data, SNP data and epigenetic data from 7 human cell lines and 14 human tissues

a fast algorithm to detect long-range chromosomal interactions from Hi-C data
inferring spatial organizations of chromosomes via helix models

a genome browser for the integrative analysis of Hi-C data, SNP data and epigenetic data
A hidden Markov random field based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data

infer chromosome 3D structures and characterize chromatin structural variations
removing biases in Hi-C data via Poisson regression

An ultra-fast and energy-efficient motif analysis program using graphics processing units
quantifying exon-level gene expression in RNA-Seq

de novo motif discovery using ChIP-Seq data
An R package for detecting frequently interacting regions from Hi-C data
TWO-component SInGle cell Model-based Association method

Bold lists Hu lab members.

First author and corresponding author papers

27. Zhong W*, Liu W*, Chen J, Sun Q, Hu M# and Li Y# (2022). Understanding the function of regulatory DNA interactions in interpretation of non-coding GWAS variants. In press. Frontiers in Cell and Developmental Biology. *Co-first author. #Co-corresponding author.

26. Li X*, Lee L*, Abnousi A, Yu M, Liu W, Huang L, Li Y# and Hu M# (2022). SnapHiC2: a computationally efficient loop caller for single cell Hi-C data. Computational and Structural Biotechnology Journal. 20:2778-2783. *Co-first author. #Co-corresponding author.

25. Huang L*, Yang Y*, Li G, Jiang M, Wen J, Abnousi A, Rosen J, Hu M# and Li Y# (2022). A systematic evaluation of Hi-C data enhancement methods for enhancing PLAC-seq and HiChIP data. Briefings in Bioinformatics. 23(3):bbac145. *Co-first author. #Co-corresponding author. 

24. Liu W*, Zhong W*, Chen J, Huang B, Hu M# and Li Y# (2022). Understanding regulatory mechanisms of brain function and disease through 3D genome organization. Genes. 13(4), 586. *Co-first author. #Co-corresponding author. 

23. Yu M, Li Y and Hu M* (2022). Mapping chromatin loops in single cells. Trends in Genetics. 38(7):637-640. *Corresponding author. 

22. Yu M*, Abnousi A*, Zhang Y, Li G, Lee L, Chen Z, Fang R, Lagler T, Yang Y, Wen J, Sun Q, Li Y, Ren B# and Hu M(2021). SnapHiC: a computational pipeline to identify chromatin loops from single cell Hi-C data. Nature Methods. 18(9):1056-1059. *Co-first author#Co-corresponding author

21. Liu W*, Yang Y*, Abnousi A, Zhang Q, Kubo N, Martin J, Li Yand Hu M# (2021). MUNIn: a statistical framework for identifying long-range chromatin interactions from multiple samples. Human Genetics and Genomics Advances. 2(3):100036 *Co-first author#Co-corresponding author.

20. Song M*, Pebworth MP*, Yang X*Abnousi A, Fang C, Wen J, Rosen J, Choudhary M, Cui X, Jones I, Bergenholtz S, Ugomma CE, Juric I, Li B, Maliskova L, Lee J, Liu W, Pollen A, Li Y, Wang T, Hu M*,#, Kriegstein A# and Shen Y# (2020). Cell-type-specific 3D epigenomes in the developing human cortex. Nature 587(7835):644-649. *Co-first author#Co-corresponding author.

19. Crowley C, Yang Y*, Qiu Y, Hu B, Abnousi A, Lipinski J, Plewczynski D, Won H, Di W, Ren B, Hu M* and Li Y* (2020). FIREcaller: detecting frequently interacting regions from Hi-C data. Computational and Structural Biotechnology Journal. 19:355-362 *Co-corresponding author.

18. Gorkin DU*, Qiu Y*, Hu M*,#, Fletez-Brant K, Liu T, Schmitt AD, Noor A, Sebat J, Li Y, Hansen KD and Ren B#. (2019) Common DNA sequence variation influences 3-dimensional architecture of the human genome. Genome Biology. 20(1):255. *Co-first author#Co-corresponding author.

17. Yu J, Hu M* and Li C*. (2019) Joint analyses of multi-tissue Hi-C and eQTL data demonstrate close spatial proximity between eQTLs and their target genes. BMC Genetics. 20(1):43 *Co-corresponding author.

16. Juric I*, Yu M*, Abnousi A, Raviram R, Fang R, Zhao Y, Zhang Y, Qiu Y, Yang Y, Li Y, Ren B# and Hu M# (2019). MAPS: model-based analysis of long-range chromatin interactions from PLAC-Seq and HiChIP experiments. PLOS Computational Biology. 15(4):e1006982. *Co-first author. #Co-corresponding author.

15. Sun Z, Chen L, Xin H, Jiang Y, Huang Q, Cillo AR, Tabib T, Kolls JK, Bruno TC, Lafyatis R, Vignali DAA, Chen K, Ding Y*, Hu M* and Chen W*. (2019) BAMM-SC: a Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies. Nature Communications. 10(1):1649. *Co-corresponding author. This paper has been selected as one of the International Biometric Society Eastern North American Regions (ENAR) Distinguished Student Paper Awards for the 2019 ENAR Spring Meeting in Philadelphia, PA.

14. Zhang R, Hu M*, Zhu Y*, Qin ZS, Deng K and Liu JS. (2018) Inferring spatial organization of individual topologically associated domains via piecewise helical model.  IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(2), 647-656. *Co-corresponding author. 

13. Sun Z, Wang T, Deng K, Wang X, Layfatis R, Ding Y, Hu M* and Chen W* (2017). DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data. Bioinformatics. 34(1): 139-146. *Co-corresponding author.

12. Martin J, Xu Z, Reiner AP, Mohlke KL, Sullivan P, Ren B, Hu M* and Li Y* (2017) HUGIn: Hi-C unifying genomic interrogator. Bioinformatics. 33(23): 3793-3795. *Co-corresponding author.

11. Schmitt AD, Hu M* and Ren B* (2016) Genome-wide mapping and analysis of chromosome architecture. Nature Reviews Molecular Cell Biology. 17: 743-755. *Co-corresponding author.

10. Schmitt AD*, Hu M*, #, Jung I, Xu Z, Qiu Y, Tan CL, Li Y, Lin S, Lin Y, Barr CL and Ren B#. (2016) A compendium of chromatin contact maps reveal spatially active regions in the human genome. Cell Reports. 17(8): 2042-2059. *Co-first author. #Co-corresponding author. 

9. Xu Z, Zhang G, Wu C, Li Y* and Hu M*. (2016) FastHiC: a fast algorithm to detect long-range chromosomal interactions from Hi-C data. Bioinformatics. 32(17): 2692-2695. *Co-corresponding author. 

8. Xu Z, Zhang G, Duan Q, Chai S, Zhang B, Wu C, Jin F, Feng Y, Li Y* and Hu M*. (2016) HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants. BMC Research Notes. 9(1): 159. *Co-corresponding author. 

7. Xu Z, Zhang G, Jin F, Chen M, Furey TS, Sullivan PF, Qin ZS, Hu M* and Li Y*. (2016) A hidden Markov random field based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data. Bioinformatics. 32(5): 650-656. *Co-corresponding author.

6. Hu M, Deng K, Qin ZS and Liu JS. (2013) Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data. Quantitative Biology, 1(2): 156-174. Featured cover image for this issue in Quantitative Biology. Selected as one of the two featured articles for this issue in Quantitative Biology. 

5. Hu M, Deng K, Qin ZS, Dixon J, Selvaraj S, Fang J, Ren B and Liu JS. (2013) Bayesian inference of spatial organizations of chromosomes. PLOS Computational Biology, 9(1): e1002893. 

4. Hu M, Deng K, Selvaraj S, Qin ZS, Ren B and Liu JS. (2012) HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics, 28(23): 3131-3133. 

3. Hu M, Zhu Y, Taylor JMG, Liu JS and Qin ZS. (2012) Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq. Bioinformatics, 28(1): 63-68. 

2. Hu M, Yu J, Taylor JMG, Chinnaiyan AM and Qin ZS. (2010) On the detection and refinement of transcription factor binding sites using ChIP-Seq data. Nucleic Acids Research, 38(7), 2154-2167.

1. Hu M and Qin ZS. (2009) Query large scale microarray compendium datasets using a model-based bayesian approach with variable selection. PLOS One, 4(2): e4495. 

Collaboration papers

70. Kalra G, Talcott KE, Kaiser S, Uguegbu O, Hu M, Srivastava SK and Ehlers JP (2022). Automated machine learning detection of hydroxychloroquine toxicity and prediction of future toxicity using higher order OCT biomakers. In press. Ophthalmology Retina.

69. Arepalli S, Wykoff CC, Abrahma JR, Lunasco L, Yu H, Hu M, Srivastava SK, Reese JL, Brown DM and Ehlers JP (2022). Longitudinal analysis of aqueous humor cytokine expression and OCT-based imaging biomarkers in retinal vein occlusions treated with anti-vascular endothelial growth factor therapy in the IMAGE DME study. In press. Eye.

68. Jiang AC, Sevgi DD, Mugnaini C, Whitney J, Srivastava SK, Talcott KE, Hu M, Reese JL and Ehlers JP (2022). Predictive assessment of quantitative ultra-widefield angiographic features for future need for anti-VEGF therapy in diabetic eye disease.  Journal of Personalized Medicine. 12(4):608.

67. Ehlers J, Patel N, Kaiser P, Heier J, Brown D, Meng X, Reese J, Lunasco L, Le T, Hu M and Srivastava SK (2022). The association of fluid volatility with subretinal hyperreflective material and ellipsoid zone integrity in neovascular AMD. Investigative Ophthalmology & Visual Science. Vol 63, 17.

66. Rowlan B, Huh R, Hou Z, Crowley C, Wen J, Shen Y, Hu M, Giusti-Rodriguez P, Sulivan PF and Li Y (2022). THUNDER: a reference-free deconvolution method to infer cell type proportions from bulk Hi-C data. PLOS Genetics. 18(3):e1010102. 

65. Buren EV, Hu M, Cheng L, Wrobel J, Wilhelmsen K, Su L, Li Y and Wu D (2022). TWO-SIGMA-G: a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell-cell correlation. Briefings in Bioinformatics. 23(3):bbac084.

64. Wen J, Lagler T, Sun Q, Yang Y, Chen J, Harigaya Y, Sankaran V, Hu M, Reiner A, Raffiel L and Li Y (2021). Super interactive promoters provide insights into cell type-specific regulatory networks in blood lineage cell types. PLOS Genetics. 18(1):e1009984.

63. Ypsilanti A, Pattabiraman K, Catto-Pretta R, Golonzhka O, Lindtner S, Tang K, Jones I, Abnousi A, Juric IHu M, Shen Y, Dickel DE, Visel A, Pennachio LA, Hawrylycz M, Thompson C, Zeng H, Barozzi I, Nord A and Rubenstein J (2021). Transcriptional network orchestrating regional patterning of cortical progenitors.  Proceedings of the National Academy of Sciences of the United States of America. 118(51):e2024795118.

62. Babiuch A, Wjkoff C, Yordi S, Yu H, Srivastava SK, Hu M, Le TK, Lunasco L, Resse J, Nittala M, Sadda S and Ehlers JP (2021). The two-year leakage index and quantitative microaneurysm results of the RECOVERY study: quantitative ultra-widefield findings in proliferative diabetic retinopathy treated with intravitreal aflibercept. Journal of Personalized Medicine. 11(11), 1126. 

61. Rosen J, Yang Y, Abnousi A, Chen J, Song M, Jones I, Shen Y, Hu M and Li Y (2021) HPrep: quantifying reproducibility in HiChIP and PLAC-seq datasets. Current Issues in Molecular Biology. 43(2), 1156-1170.

60. Sevgi D, Srivastava SK, Whitney J, O'Connel M, Kar S, Hu M, Reese J, Madabhushi A and Ehlers J (2021). Characterization of ultra-widefield angiographic vascular features in diabetic retinopathy with automated severity classification. Ophthalmology Science. 1(3):100049.

59. Wang F, Wang Y, Zhang K, Hu M and Zhang H (2021). Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation. Environmental Research. 202:111660.

58. Ren X, Wang M, Li B, Jamieson K, Zheng L, Jones I, Li B, Takagi MA, Lee J, Maliskova L, Tam TW, Yu M, Hu R, Lee L, Abnousi A, Li G, Li Y, Hu M, Ren B, Wang W and Shen Y (2021). Parallel characterization of cis-regulatory elements in multiple genes using CRISPRpath. Science Advances. 7(38):eabi4360.

57. Abraham J, Wykoff C, Apepalli S, Lunasco L, Yu H, Martin A, Mugnaini C, Hu M, Reese J, Srivastava S, Brown D and Ehlers J (2021). Exploring the angiographic-biologic phenotype in the IMAGE DME study: quantitative UWFA and cytokine expression. In press. British Journal of Ophthalmology. 

56. Mokarram M, Pourghasemi HR, Hu M and Zhang H (2021). Determining and forecasting drought-prone areas in southwestern Iran using fuzzy-AHP method coupled with CA-Markov mode. Science of the Total Environment. 781:146703. 

55. Huang H, Zhu Q, Jussila A, Han Y, Bintu B, Kern C, Conte M, Zhang Y, Bianco S, Chiariello A, Yu M, Hu R, Tastemel M, Juric I, Hu M, Nicodemi M, Zhuang X and Ren B (2021). CTCF mediates dosage and sequence-context-dependent transcriptional insulation through formation of local chromatin domains. Nature Genetics. 53, 1064-1074.

54. Ehlers JP, Zahid R, Kaiser PK, Heier JS, Brown DM, Meng X, Reese JL, Le T, Lunasco L, Hu M and Srivastava SK (2021). Longitudinal assessment of ellipsoid zone integrity, subretinal hyperreflective material, and sub-RPE disease in neovascular age-related macular degeneration.  Ophthalmology Retina. S2468-6530(21)00066-X.

53. Ehlers JP, Clark J, Uchida A, Figueiredo N, Babiuch A, Talcott KE, Lunasco L, Le TK, Meng X, Hu M, Reese JL and Srivastava SK (2021). Longitudinal higher-order OCT assessment of quantitative fluid dynamics and the total retinal fluid index in neovascular AMD. Translational Vision Science & Technology. 10(3):29.

52. Lagler T, Abnousi A, Hu M, Yang Y and Li Y (2021). HiC-ACT: improved detection of chromatin interactions from Hi-C data via aggregated Cauchy test. American Journal of Human Genetics. Volume 108, Issue 2, pages 257-268.

51. Ehlers JP, Uchida A, Sevgi D, Hu M, Reed K, Berliner A, Vitti R, Chu K and Srivastava SK (2020). Retinal fluid volatility associated with interval tolerance and visual outcomes in diabetic macular edema in the VISTA phase III trial.  American Journal of Ophthalmology. Volume 224, page 217-227.

50. Kubo N, Ishii H, Xiong X, Bianco S, Meitinger F, Hu R, Hocker J, Conte M, Gorkin D, Yu M, Li M, Dixon J, Hu M, Nicodemi M, Zhao H and Ren B (2020). Promoter-proximal CTCF-binding promotes long-range-enhancer dependent gene activation. Nature Structural & Molecular Biology. 28(2):152-161.

49. Buren EV, Hu M, Weng C, Jin F, Li Y, Wu D and Li Y (2020). TWO-SIGMA: a novel TWO-component SInGle cell Model-based Association method for single cell RNA-seq data. Genetic Epidemiology. Volume 45, Issue 2, 142-153.

48. Abraham J, Wykoff C, Arepalli S, Lunasco L, Yu H, Hu M, Reese JL, Srivastava SK, Brown D and Ehlers JP (2020). Aqueous cytokine expression and higher-order OCT biomarkers: assessment of the anatomic-biologic bridge in the IMAGINE DME study. American Journal of Ophthalmology 222:328-339. 

47. Babiuch A, Wykoff CC, Hach J, Srivastava S, Talcott K, Yu H, Nittala M, Sadda S, Ip MS, Le T, Hu M, Reese JL and Ehlers JP (2020). Longitudinal panretinal microaneurysm dynamics on ultra-widefield fluorescein angiography in eyes treated with intravitreal aflibercept for proliferative diabetic retinopathy in the RECOVERY study. British Journal of Ophthalmology. 105(8):1111-1115.

46. Liu C, Abnousi A, Bazeley P, Ni Y, Morely M, Morvec C, Hu M and Tang W (2020). Global analysis of histone modifications and long-range chromatin interaction revealed the differential cistrome changes and novel transcriptional players in human dilated cardiomyopathy. Journal of Molecular and Cellular Cardiology. 145:30-42.

45. Lu L, Liu X, Huang WK, Giusti-Rodriguez P, Cui J, Zhang S, Xu W, Wen Z, Ma S, Rosen J, Xu Z, Bartels C, Kawaguchi R, Hu M, Scacheri P, Rong Z, Li Y, Sullivan P, Song H, Ming G, Li Y and Jin F (2020). Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases. Molecular Cell. 79(3):521-534.

44. Babiuch AS, Uchida A, Hu M, Mehnaz K, Srivastava SK, Singh RP, Kaiser PK, Rachitskaya A, Reese JL and Ehlers JP (2020). Use of OCTA capillary perfusion density measurements to detect and grade macular ischemia. Ophthalmic Surgery, Lasers and Imaging Retina. 51(4):S30-S36.

43. Figueiredo N, Talcott KE, Srivastava SK, Hu M, Rachitskay A, Sharma S, Singh RP, Yuan A, Reese JL and Ehlers JP (2020). Conventional microscope-integrated intraoperative OCT versus digitally enabled intraoperative OCT in vitreorential surgery in the DISCOVER study. Ophthalmic Surgery, Lasers and Imaging Retina. 51(4):S37-S43.

42. Browne AW, Ansari W, Hu M, Baynes K, Lowder CY, Ehlers JP and Srivastava SK (2020). Quantitative analysis of ellipsoid zone in acute posterior multifocal placoid pigment epitheliopathy. Journal of VitreoRential Diseases. 4(3): 192-201.

41. Babiuch AS, Wykoff CC, Srivastava SK, Talcott KE, Zhou B, Hach J, Hu M, Reese JL and Ehlers JP (2020). Retinal leakage index dynamics on ultra-widefield fluorescein angiography in eyes treated intravitreal aflibercept for proliferative diabetic retinopathy in the RECOVERY study. Retina. 40(11):2175-2183.

40. Zhu C, Yu M, Huang H, Juric I, Abnousi A, Lucero J, Behres M, Hu M and Ren B. (2019) An ultra high-througput method for single-cell joint analysis of open chromatin and transcriptome. Nature Structural & Molecular Biology. 26(11):1063-1070.

39. Venkat AG, Singh RP, Eisengart J, Hu M and Babiuch A (2019). Trends in neovascular glaucoma management: practice patterns of glaucoma and retina specialists in the United States. American Journal of Ophthalmic Clinical Trials. 2019;2:7.

38. Figueiredo N, Srivastava S, Singh RP, Babiuch A, Sharma S, Rachitskaya A, Talcott K, Reese J, Hu M and Ehlers JP (2019). Longitudinal panretinal leakage and ischemic indices in retinal vascular disease following aflibercept therapy: The PERMEATE study. Ophthalmology Retina. 4(2), 154-163. 

37. Wu S, Turner K, Nguyen N, Raviram R, Erb M, Santini J, Luebeck J, Rajkumar U, Diao Y, Li B, Zhang W, Jameson N, Corces MR, Granja JM, Chen X, Coruh C, Abnousi A, Houston J, Ye Z, Hu R, Yu M, Kim H, Law J, Verhaak R, Hu M, Furnari F, Chang H, Ren B, Bafna V and Mischel P (2019). Circular ecDNA promotes accessible chromatin and high oncogene expression. Nature. 575(7784):699-703.

36. Jiang A, Srivastava S, Hu M, Figueiredo N, Babiuch A, Boss J, Reese J and Ehlers JP (2019). Quantitative ultra-widefield angiographic features and associations with diabetic macular edema. Ophthalmology Retina. 4(1), 49-56.

35. Ehlers JP, Uchida A, Hu M, Figueiredo N, Kaiser P, Heier JS, Brown DM, Boyer DS, Do DV, Gibson A, Saroj N and Srivastava S (2019). Higher order assessment of OCT in diabetic macular edema from the VISTA Study: ellipsoid zone dynamics and the retinal fluid index. Ophthalmology Retina. 3(12):1056-1066.

34. Xu B, Song B, Lu X, Kim J, Hu M, Zhao JC and Yu J (2019). Altered chromatin recruitment by FOXA1 mutations promotes androgen independence and prostate cancer progression. Cell Research. 29(9):773-775.

33. Jiang A, Srivasava SK, Figueiredo N, Babiuch A, Hu M, Resse J and Ehlers JP (2019). Repeatability of automated leakage quantification and microaneurysm identification utilizing an analysis platform for ultra-widefield fluorescein angiography. British Journal of Ophthalmology. 104(4):500-503.

32. Uchida A, Hu M, Babiuch A, Srivastava SK, Singh SP, Kaiser PK, Talcott K, Rachitskaya A and Ehlers JP (2019). Optical coherence tomography angiography characteristics of choroidal neovascularization requiring varied doseing frequencies in treat-and-extend management: an analysis of the AVATAR study. PLOS One. 14(6):e0218889.

31. Ehlers JP, Jiang A, Boss J, Hu M, Figueiredo N, Babiuch A, Talcott K, Sharma S, Hach J, Le T, Rogozinski A, Lunasco L, Reese J and Srivastava S (2019). Quantitative ultra-widefield angiography and diabetic retinopathy severity: an assessment of panretinal leakage index, ischemic index and microaneurysm count. Ophthalmology. 126(11):1527-1532.

30. Deng X, Wang X, Hu S and Hu M (2019) A general result on complete convergence for weighted sums of linear processes and its statistical applications. Statistics. 53(4):903-920.

29. Yamada T, Yang Y, Valnegri P, Juric I, Abnousi A, Markwalter KY, Guthrie AN, Godec A, Oldenborg A, Hu M, Holy TE and Bonni A. (2019) Sensory experience remodels genome architecture in neural circuit to drive motor learning. Nature. 569(7758):708-713.

28. Babiuch A, Uchida A, Figueiredo N, Hu M, Khan M, Srivastava SK, Singh RP, Rachitskaya A, Kaiser PK, Reese JL and Ehlers JP. (2019) Impact of optical coherence tomograhpy angiography review strategy on detection of choroidal neovascularization. Retina. 40(4):672-678.

27. Ehlers JP, Uchida A, Srivastava SK and Hu M. (2019) Predictive model for macular hole closure speed: insights from intraoperative optical coherence tomography. Translational Vision Science and Technology. 8(1):18.

26. Koshkin V, Garcia J, Reynolds J, Elson P, Magi-Galluzzi C, McKenney J, Isse K, Bishop E, Saunders L, Balyimez A, Rashid S, Hu M, Stephenson A, Fergany A, Lee B, Haber G, Dowlati A, Gilligan T, Ornstein M, Rini B, Mian O and Grivas P. (2019) Transcriptomic and protein analysis of small cell bladder cancer (SCBC) identifies prognostic biomarkers and DLL3 as a relevant therapeutic target. Clinical Cancer Research. 25(1): 210-221.

25. Ugwuegbu O, Uchida A, Singh RP, Beven L, Hu M, Srivastava SK and Ehlers JP. (2019) Quantitative assessment of outer retinal layers and ellipsoid zone mapping in hydroxychloroquine retinopathy. British Journal of Ophthalmology. 103(1): 3-7.

24. Li M, Santpere G, Kawasawa YI, Evgrafov OV, Gulden FO, Pochareddy S, Sunkin SM, Li Z, Shin Y, Zhu Y, Sousa AMM, Werling DM, Kitchen RR, Kang H, Pletikos M, Choi J, Muchnik S, Xu X, Wang D, Lorente-Galdos B, Liu S, Giusti-Rodríguez P, Won H, Leeuw CA, Pardinas A, BrainSpan Consortium, PsychENCODE Consortium, PsychENCODE Developmental Subgroup, Hu M, Jin F, Li Y, Owen MJ, O'Donovan MC, Walters JTR, Posthuma D, Levitt P, Weinberger DR, Kleinman JE, Geschwind DH, Hawrylycz MJ, State MW, Sanders SJ, Sullivan PF, Gerstein MB, Lein ES, Knowles JA and Sestan N. (2018) Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science. 362 (6420), eaat7615.

23. Wang Y, Song F, Zhong B, Zhang L, Xu J, Kuang D, Li D, Choudhary M, Li Y, Hu M, Hardison R, Wang T and Yue F. (2018) The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biology. 19(1): 151.

22. Arepalli S, Srivastava SK, Hu M, Kaiser PM, Dukles N, Reese JL and Ehlers JP. (2018) Assessment of inner and outer retinal layer metrics on the cirrus HD-OCT platform in normal eyes. PLOS One. 13(10):e0203324.

21. Babiuch AS, Khan M, Hu M, Kaiser PK, Srivastava SK, Singh RP, Watts A, Reese JL and Ehlers JP (2018). Comparison of OCT angiography review strategies to identify vascular abnormalities in the AVATAR study. Ophthalmology Retina. 2(6), 606-612

20. Li Y, Hu M and Shen Y. (2018) Gene regulation in the 3D genome. Human Molecular Genetics. 27(R2), R228-R233.

19. Wray NR, Ripke S, Mattheisen M, Trazskowski M, ..., Hu M, ..., Lewis CM, Levinson DF, Breen G, Borglum AD, Sullivan PF, eQTLGen consortium, 23andMe research team and the major depression disorder working group of the psychiatric genomics consortium. (2018) Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature Genetics. 50(5), 668.

18. Zhang Y, Lin A, Xu J, Zheng JW, Hu M, Tang J and Yue F. (2018) Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus. Nature Communications. 9(1), 750.

17. Yan J, Chen SA, Local A, Liu T, Qiu Y, Dorighi KM, Preissl S, Rivera CM, Wang C, Ye Z, Ge K, Hu M, Wysocka and Ren B (2018). Histone H3 lysine 4 monomethylation modulates long-range chromatin interactions at enhancers. Cell Research. 28(2), 204.

16. Hui D, Fang Z, Lin J, Duan Q, Li Y, Hu M and Chen W. (2017) LAIT: a local ancestry inference toolkit. BMC Genetics. 18(1): 83.

15. Ehlers JP, Wang K, Vasanji A, Hu M and Srivastava SK. (2017) Automated quantitative characterization of retinal vascular leakage and microaneurysms in ultra-widefield fluorescein angiography. British Journal of Ophthalmology. 101: 696-699.

14. Fong K, Zhao JC, Kim J, Li S, Yang YA, Song B, Rittie L, Hu M, Yang X, Perbal B and Yu J. (2017) Polycomb-mediated disruption of an androgen receptor feedback loop derives castration-resistant prostate cancer. Cancer Research. 77(2): 412-422.

13. Qin ZS, Li B, Conneely KN, Wu H, Hu M, Ayyala D, Park Y, Jin VX, Zhang F, Zhang H, Li L and Lin S. (2016) Statistical challenges in analyzing methylation and long-range chromosomal interaction data. Statistics in Biosciences. 1-26.

12. Grudzen CR, Richardson LD, Johnson PN, Hu M, Wang B, Ortiz JM, Kistler EA, Chen A and Morrison RS. (2016) Emergency department-initiated palliative care in advanced cancer: a randomized clinical trial. JAMA oncology, 2(5): 591-598.

11. Smith SW, Jamin CT, Malik S, Abrukin L, Tupchong KM, Portelli I, Asaeda G, Prezant DJ, Wang B, Hu M, Goldfrank LR and Meyers CM. (2016) Freestanding Emergency Critical Care During the Aftermath of Hurricane Sandy: Implications for Disaster Preparedness and Response. Disaster Medicine and Public Health Preparedness. 10(3): 496-502.

10. Smith SW, Braun J, Portelli I, Malik S, Asaeda G, Lancet E, Wang B, Hu M, Lee CD, Prezant DJ and Goldfrank LR. (2016) Prehospital indicators for disaster preparedness and response: New York City Emergency Medical Services in Hurricane Sandy (CDC-Sandy). Disaster Medicine and Public Health Preparedness. 10(3): 333-343.

9. Li L, Lyu X, Hou C, Takenaka N, Nguyen HQ, Tong OC, Potts CC, Hu M, Lei EP, Bosco G, Qin ZS and Corces VG. (2015) Widespread rearrangement of 3D chromatin organization underlies polycomb-mediated stress-induced silencing. Molecular Cell. 58(2):216-231. Cover image of the April 16, 2015 issue.

8. Lu J, Li H, Hu M, Sasaki T, Baccei A, Gilbert DM, Liu JS, Collins JJ, Lerou PH. (2014) The distribution of genomic variations in human iPSCs is related to replication-timing reorganization during reprogramming. Cell Reports, 7(1): 70-78. 

7. Dixon JR, Selvaraj S, Yue F, Kim A, Li Y, Shen Y, Hu M, Liu JS and Ren B. (2012) Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature, 485, 376-380. 

6. Zhao CJ, Yu J, Runkle C, Wu L, Hu M, Wu D, Liu JS, Wang Q, Qin ZS and Yu J. (2012) Cooperation between polycomb and androgen receptor during oncogenic transformation. Genome Research, 22(2): 322-311. 

5. Zandevakili P, Hu M and Qin ZS. (2012) GPUmotif: An ultra-fast and energy-efficient motif analysis program using graphics processing units. PLOS One, 7(5): e36865. 

4. Kim JH, Dhanasekaran SM, Prensner JR, Cao X, Robinson D, Kalyana-Sundaram S, Huang C, Shankar S, Jing X, Iyer M, Hu M, Sam L, Grasso C, Maher CA, Palanisamy N, Mehra R, Kominsky HD, Siddiqui J, Yu J, Qin ZS and Chinnaiyan AM. (2011) Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer. Genome Research, 21(7): 1028-1041. 

3. Qin ZS, Yu J, Shen J, Maher CA, Hu M, Kalyana-Sundaram S, Yu J and Chinnaiyan AM. (2010) HPeak: An HMM-based algorithm for defining read-enriched regions in ChIP-Seq data. BMC Bioinformatics, 11(1): 369. 

2. Yu J, Yu J, Mani RS, Cao Q, Brenner CJ, Cao X, Wang X, Wu L, Li J, Hu M, Gong Y, Cheng H, Laxman B, Vellaichamy A, Shankar S, Li Y, Dhanasekaran SM, Morey R, Barrette T, Lonigro RJ, Tomlins SA, Varambally S, Qin ZS and Chinnaiyan AM. (2010) An integrated network of androgen receptor, polycomb, and TMPRSS2-ERG gene fusions in prostate cancer progression. Cancer Cell, 17(5): 443-454. 

1. Hu S and Hu M. (2006) A general approach rate to the strong law of large numbers. Statistics and Probability Letters, 76(8): 843-851.

Hye Rin (Lindsay)  Lee  PhD Hye Rin (Lindsay) Lee, PhD
Postdoctoral Fellow