Search Results - "Yu, Wenbao"

Refine Results
  1. 1

    Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test by Yu, Wenbao, He, Bing, Tan, Kai

    Published in Nature communications (14-09-2017)
    “…The spatial organization of the genome plays a critical role in regulating gene expression. Recent chromatin interaction mapping studies have revealed that…”
    Get full text
    Journal Article
  2. 2

    scATAC-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data by Yu, Wenbao, Uzun, Yasin, Zhu, Qin, Chen, Changya, Tan, Kai

    Published in Genome Biology (20-04-2020)
    “…Single-cell chromatin accessibility sequencing has become a powerful technology for understanding epigenetic heterogeneity of complex tissues. However, there…”
    Get full text
    Journal Article
  3. 3

    A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions by Yu, Wenbao, Lee, Seungyeoun, Park, Taesung

    Published in Bioinformatics (Oxford, England) (01-09-2016)
    “…Gene-gene interaction (GGI) is one of the most popular approaches for finding and explaining the missing heritability of common complex traits in genome-wide…”
    Get full text
    Journal Article
  4. 4

    Spatial Genome Re-organization between Fetal and Adult Hematopoietic Stem Cells by Chen, Changya, Yu, Wenbao, Tober, Joanna, Gao, Peng, He, Bing, Lee, Kiwon, Trieu, Tuan, Blobel, Gerd A., Speck, Nancy A., Tan, Kai

    Published in Cell reports (Cambridge) (17-12-2019)
    “…Fetal hematopoietic stem cells (HSCs) undergo a developmental switch to become adult HSCs with distinct functional properties. To better understand the…”
    Get full text
    Journal Article
  5. 5

    Bistable switch in let-7 miRNA biogenesis pathway involving Lin28 by Shi, Fei, Yu, Wenbao, Wang, Xia

    “…miRNAs are small noncoding RNAs capable of regulating gene expression at the post-transcriptional level. A growing body of evidence demonstrated that let-7…”
    Get full text
    Journal Article
  6. 6

    Unified Cox model based multifactor dimensionality reduction method for gene-gene interaction analysis of the survival phenotype by Lee, Seungyeoun, Son, Donghee, Kim, Yongkang, Yu, Wenbao, Park, Taesung

    Published in BioData mining (14-12-2018)
    “…One strategy for addressing missing heritability in genome-wide association study is gene-gene interaction analysis, which, unlike a single gene approach,…”
    Get full text
    Journal Article
  7. 7

    Multivariate Quantitative Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions by Yu, Wenbao, Kwon, Min-Seok, Park, Taesung

    Published in Human heredity (01-01-2015)
    “…To determine gene-gene interactions and missing heritability of complex diseases is a challenging topic in genome-wide association studies. The multifactor…”
    Get more information
    Journal Article
  8. 8
  9. 9

    Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method by Lee, Seungyeoun, Son, Donghee, Yu, Wenbao, Park, Taesung

    Published in Genomics & informatics (01-12-2016)
    “…Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still…”
    Get full text
    Journal Article
  10. 10

    Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method by Lee, Seungyeoun, Son, Donghee, Yu, Wenbao, Park, Taesung

    Published in Genomics & informatics (2016)
    “…Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still…”
    Get full text
    Journal Article
  11. 11

    AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data by Yu, Wenbao, Park, Taesung

    Published in BMC genomics (12-12-2014)
    “…It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on…”
    Get full text
    Journal Article
  12. 12

    Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve by Yu, Wenbao, Park, Taesung

    Published in Computational statistics & data analysis (01-08-2015)
    “…In clinical practices, it is common that several biomakers are related to a specific disease and each single marker does not have enough diagnostic power. An…”
    Get full text
    Journal Article
  13. 13

    Developmental trajectory of prehematopoietic stem cell formation from endothelium by Zhu, Qin, Gao, Peng, Tober, Joanna, Bennett, Laura, Chen, Changya, Uzun, Yasin, Li, Yan, Howell, Elizabeth D., Mumau, Melanie, Yu, Wenbao, He, Bing, Speck, Nancy A., Tan, Kai

    Published in Blood (13-08-2020)
    “…Hematopoietic stem and progenitor cells (HSPCs) in the bone marrow are derived from a small population of hemogenic endothelial (HE) cells located in the major…”
    Get full text
    Journal Article
  14. 14

    ESTIMATION OF AREA UNDER THE ROC CURVE UNDER NONIGNORABLE VERIFICATION BIAS by Yu, Wenbao, Kim, Jae Kwang, Park, Taesung

    Published in Statistica Sinica (01-10-2018)
    “…The Area Under the Receiving Operating Characteristic Curve (AUC) is frequently used for assessing the overall accuracy of a diagnostic marker. However,…”
    Get full text
    Journal Article
  15. 15
  16. 16

    Absence of biopolymers in surface waters inhibits flocs growth in winter: A secret of coagulation over decades by Su, Zhaoyang, Wu, Xiaoting, Yu, Wenbao, Liu, Ting, Li, Xing, Liu, Muyang, Yu, Wenzheng

    Published in Journal of cleaner production (15-11-2022)
    “…Factors responsible for undesirable coagulation performance in winter have not been well understood by far. The aim of this work is to identify the critical…”
    Get full text
    Journal Article
  17. 17

    The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution by Rood, Jennifer E., Coffey, Robert J., Demir, Emek, Ghosh, Sharmistha, Iacobuzio-Donahue, Christine A., Jané-Valbuena, Judit, Mazzilli, Sarah A., Pe’er, Dana, Tan, Kai, Aguilar, Ruben A., Babur, Ozgun, Boland, Genevieve, Bosse, Kristopher, Bott, Matthew, Boyden, Ed, Brooks, James, Cerami, Ethan, Chang, Young Hwan, Chaudhary, Ojasvi, Chen, Alyce A., Chen, Feng, Chun, Jaeyoung, Cisneros, Luis, Contrepois, Kevin, Creason, Allison L., Demir, Emek, Diskin, Sharon, Drewes, Julia, Eng, Jennifer, Erwin, Graham, Flaherty, Keith, Gao, Jianjiong, Gao, Vianne R., Giannakis, Marios, Gowers, Kate, Gray, Joe W., Greenleaf, William, Gresham, Jeremy, Hacohen, Nir, Harris, Kathleen A., Hayashi, Akimasa, Herndon, John M., Huh, Won Jae, Ijaz, Heba, Izar, Benjamin, Johnson, Brett E., Kaestner, Klaus, Kim, Albert H., Kopytra, Mateusz, Kundaje, Anshul, Lau, Ken S., Lee, Hayan, Lenburg, Marc, Lim, Kian-Huat, Lin, Yiyun, Lively, Tracy, Longabaugh, William J.R., Ma, Cynthia X., Marks, Jeffrey, Masilionais, Ignas, McKinley, Eliot T., McMichael, Joshua F., Mosse, Yael, Ness, Reid, Nikolov, Milen, Oberdoerffer, Philipp, Offin, Michael, Olson, Anastasiya, Ossandon, Miguel, Polyak, Kornelia, Reid, Mary, Roy, Sudipta, Ryser, Marc D., Schrag, Deborah, Sears, Rosalie C., Shalek, Alex, Sheng, Jeff, Shoghi, Kooresh I., Sibley, Alexander B., Sorger, Peter K., Southard-Smith, Austin, Srivastava, Sudhir, Storm, Phillip, Sullivan, Ryan, Suvà, Mario, Thorsson, Vésteinn, Tran, Linh, Veis, Deborah J., Vossough, Arastoo, Wagle, Nikhil, Wang, Liang-Bo, West, Robert, Wu, Chi-yun, Wyczalkowski, Matthew A., Xie, Yubin, Yang, Xiaolu, Zhang, Mianlei, Zhang, Yantian, Zhou, Daniel Cui, Zhuang, Xiaowei

    Published in Cell (16-04-2020)
    “…Crucial transitions in cancer—including tumor initiation, local expansion, metastasis, and therapeutic resistance—involve complex interactions between cells…”
    Get full text
    Journal Article
  18. 18
  19. 19
  20. 20