Xin Wang

Xin works on probabilistic models to analyze high-dimensional phenotyping screens. In particular, he develops scalable and dynamic extensions of Nested Effect Models. In collaboration with the Watt Lab in CRI, he also works on statistical models to predict association networks of functional interactions that control stem cell fate.

Vita

since 10/2009
PhD student at Cambridge University working at the Cancer Research UK Cambridge Research Institute

2007-2009
Visiting Research Associate in Center for Computational Biology and Bioinformatics, Indiana University School of Medicine. Advisors: Dr. Yunlong Liu & Dr. Jeremy Sanford

2005-2008
M.Sc. in Pattern Recognition and Intelligent System, College of Automation, Harbin Engineering University. Advisor: Prof. Kejun Wang

2003-2005
Double major in Business Administration, College of Economics & Management, Harbin Engineering University

2002-2005
B.Sc. in Automation, College of Automation, Harbin Engineering University

2001-2002
Major in Mechanic Design, Manufacturing and its Automation, College of Mechanical Electrical Engineering, Harbin Engineering University, Harbin, China

Degrees

Pattern Recognition and Intelligent Systems: M.Sc.
Harbin Engineering University College of Automation

Business Administration: B.Sc.
Harbin Engineering University College of Economics & Management

Automation: B.Sc.
Harbin Engineering University College of Automation

Awards and Honors

  • Best Student Paper in BIOCOMP'07 (International Conference on Bioinformatics & Computational Biology), Las Vegas, USA, 2007
  • Travel Award for visiting INRIA (Institut National de Recherche en Informatique et Automatique), Paris, France, 2005
  • First Prize in SCILAB Contest, Wuhan, China, 2005
    • Xin Wang

    Xin Wang
    CR UK - CRI
    Li Ka Shing Centre
    Robinson Way
    Cambridge, CB2 0RE, UK
    e: first.last@cancer.org.uk
    p: +44 (0) 1223 40 4318

    Funded by CRUK logo Affiliated with Cambridge University

    Software

    1. HTSanalyzeR Network analysis of high-throughput screens
    2. PAN Posterior association networks
    3. RedeR Bridging the gap between functional analyses and hierarchical network visualization

    Recent talks and teaching

    1. Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations, CWI (Center for Mathematics and Computer Science) and NKI (Netherlands Cancer Institute), Oct 2011
    2. Capturing dynamics of evolving signalling pathways, 5th International PhD Student Cancer Conference, Glasgow, Jun 2011

    Publications

    Journal Papers

    1. Wang X, Juan L, Lv J, Wang K, Sanford J and Liu Y: Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SRSF1. BMC Genomics 2011, 12(S5):S8.
    2. Wang K, Lv J, Feng W, Wang X, He B: A New Method for Identification of Eukaryotic Gene Splice Sites. Acta Electronica Sinica 2011, 39(5):1210-1213.
    3. Wang X, Terfve C, Rose JC, Markowetz F: HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens. Bioinformatics 2011, 27(6):879.
    4. Wang X, Wang K, Radovich M, Wang Y, Wang G, Feng W, Sanford J, Liu Y: Genome-wide prediction of cis-acting RNA elements regulating tissue-specific pre-mRNA alternative splicing. BMC Genomics 2009, 10(S1):S4.
    5. Sanford J, Wang X, Mort M, VanDuyn N, Cooper D, Mooney S, Edenberg H, Liu Y: Splicing factor SFRS1 recognizes a functionally diverse landscape of RNA transcripts. Genome Research 2009, 19(3):381
    6. Sanford J, Coutinho P, Hackett J, Wang X, Ranahan W, Caceres J: Identification of nuclear and cytoplasmic mRNA targets for the shuttling protein SF2/ASF. PLoS ONE 2008, 3(10)
    7. Wang G, Wang Y, Feng W, Wang X, Yang JY, Zhao Y, Wang Y, Liu Y: Transcription factor and microRNA regulation in androgen-dependent and -independent prostate cancer cells. BMC Genomics 2008, 9 (S 2):S22
    8. Wang X, Wang G, Shen C, Li L, Mooney S, Edenberg H, Sanford J, Liu Y: Using RNase sequence specificity to refine the identification of RNA-protein binding regions. BMC Genomics 2008, 9(S1):S17
    9. Wang G, Wang X, Wang Y, Yang J, Li L, Nephew K, Edenberg H, Zhou F, Liu Y: Identification of transcription factor and microRNA binding sites in responsible to fetal alcohol syndrome. BMC Genomics 2008, 9(S1):S19

    Conference Abstracts and Proceedings

    1. Wang K, Lv J, Feng W, Wang X: A Novel Method for Splice Sites Recognition Using Comprehensive Information. In proceeding of the 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, 2010
    2. Wang X, Teng M, Wang G, Zhao Y, Han X, Feng W, Li L, Sanford J, Liu Y: xIP-seq platform: an integrative framework for high-throughput sequencing data analysis. In proceeding of the 2009 Ohio Collaborative Conference on Bioinformatics, 2009
    3. Wang X, Li L, Sanford, J, Liu Y: Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SFRS1, Cold Spring Harbor Laboratory Meetings, 2009
    4. Wang X, Wang K, Wang G, Sanford J, Liu Y: Model-based prediction of cis-acting RNA elements regulating tissue-specific alternative splicing. In proceeding of the 8th IEEE International Conference on Bioinformatics and Bioengineering, 2008
    5. Wang X, Sanford, Liu Y: SplicingModeler: A computational model for cis-acting RNA element prediction, 16th Annual International Conference Intelligent Systems for Molecular Biology, 2008
    6. Sanford J, Wang X, Wang X, Liu Y: Mapping the in situ RNA binding specificity of the SR protein SF2/ASF using CLIP-Seq, Rustbelt RNA Meeting, 2007
    7. Wang X, Wang X G, Liu Y, Sanford J: Genome-wide analysis of in vivo RNA-protein interactions by cross-linking immunoprecipitation and pyrosequencing, Cold Spring Harbor Laboratory Meetings, 2007
    8. Wang X, Wang K: Campus Emergency Management System based on Scilab, Proceedings of International Workshop on Open Source SCILAB and Its Engineering Application, 2006