Chris Wang

Private Infomation

  • Research Interests: Computational Biology, Bioinformatics, Computer Science, Data Mining/Machine Learning/Deep Learning
  • E-mail: chris@nohup.cc or jiawei.wang@monash.edu
  • Blog: http://chris.nohup.cc
  • Technical Site: http://www.nohup.cc

Education

  • Sep 2012 ~ Jul 2015 Peking University Computer Science Master of Science
  • Sep 2006 ~ Jul 2010 Tongji University Software Engineering Bachelor of Engineering

Research

  • 2017-07 ~ present Identification of secreted effector proteins of Gram-negative bacterial secretion systems
    • Working on the development of machine-learning-based bioinformatics approaches to address several important problems in microbial bioinformatics.
    • Development Environment: Linux, C++, JAVA, Python, R, Perl
  • 2013-09 ~ 2015-07 Research on intelligent forwarding strategy under Named Data Networking
    • Proposed an innovative entropy based forwarding strategy under Named Data Networking (NDN), and implement it in the open source simulator NDNSIM. This project is financially supported by National Basic Research Program of China (973) under Grant. 2011CB302305 and State Key Program of National Natural Science of China (Grant No. 61232004). Published papers are listed in the publication section.
    • Development Environment: Linux, C++, Boost Library, NS3/NDNSIM, Python R

Publications

  • Journal Articles (in Bioinformatics, co-first authorship)

    • Song, J., Wang, H., Wang, J., Leier, A., Marquez-Lago T., Yang,B., Zhang, Z., Akutsu, Webb, G., Daly, R. PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection. Scientific Reports (2017).
    • Wang, J., Yang, B., Revote, J., Leier, A., Marquez-Lago T., Song, J., and Lithgow, T. POSSUM: a central bioinformatics server for generating PSSM profile based numerical representation schemes. Bioinformatics, 2017.
    • An, Y., Wang, J., Li, C., Revote, J., Zhang, Y., Naderer, T., Hayashida, M., Akutsu, T., Webb, G., Lithgow, T. and Song, J. SecretEPDB: a web-based resource for secreted effector proteins of the bacterial types III, IV and VI secretion systems. Scientific Reports 7 (2017).
    • An, Y., Wang, J., Li, C., Leier, A., Marquez-Lago T., Wilksch, J., Zhang, Y., Webb, G., Song, J., and Lithgow, T. Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI. Briefings in Bioinformatics, 2016, 1–14.
  • Conference Papers (in Computer Science)

    • Gong, L. Wang, J., Zhang, X. and Lei, K. Online Machine Learning Based Forwarding Strategy in Named Data
      Networking.
      Parallel and Distributed Processing with Applications (IEEE ISPA-16)
    • Liu, C., Wang, J. and Lei, K. Detecting spam comments posted in micro-blogs using the self-extensible spam dictionary.
      IEEE International Conference on Communications (ICC), 2016.
    • Lei, K., Yuan, J, and Wang, J. MDPF: An NDN Probabilistic Forwarding Strategy Based on Maximizing Deviation
      Method.
      IEEE Global Communications Conference (GLOBECOM), 2015.
    • Lei, K., Wang, J., and Yuan, J. An entropy-based probabilistic forwarding strategy in named data networking. IEEE
      International Conference on Communications (ICC), 2015:5665-5671.

Selected Scholarships & Honors

  • 2017-2020 Monash Graduate Scholarship (MGS)
  • 2017-2020 Monash International Postgraduate Research Scholarship (MIPRS)
  • 2017-2020 Faculty Postgraduate Excellence Award (Top Up)
  • 2015/06/01 Outstanding Graduate of Peking University (top 5%)
  • 2015/07/01 Outstanding Graduate of Beijing City (top 1%)
  • 2013-2014 Community Contribution Award of Peking University
  • 2012-2015 Graduate Admission Special Scholarship (top 10%)
  • 2012-2013 National Scholarship for Graduate Students (top 5%)
  • 2012-2013 Merit Student of Peking University (top 5%)
  • 2012-2013 Champion of 4*100 relay in sports meeting of Peking University

Projects

  • POSSUM

    • Developed by: Chris Wang & Bingjiao Young
    • Developed at: 2017
    • Web Site: http://possum.erc.monash.edu
    • Format: Web Server & Standalone Toolkit
    • Description: A bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles. POSSUM can generate 21 types of PSSM-based feature descriptors, thus contributing to a more effective analysis and modeling pipeline for bioinformatics research.
  • T-booster

    • Developed by: Chris Wang & Bingjiao Young
    • Developed at: 2016
    • Format: Web server
    • Web Site: http://tbooster.erc.monash.edu
    • Description: An ensemble learning-based predictor for secreted effector proteins of the bacterial secretion systems III and IV (termed as T3SEs and T4SEs, respectively). T-booster utilizes the output of a number of currently available T3/T4 predictors as the input and generates the final prediction result of potential T3SEs/T4SEs.
  • SecretEPDB

    • Developed by: Chris Wang & Bingjiao Young
    • Developed at: 2016
    • Format: Web Database
    • Web Site: http://secretepdb.erc.monash.edu
    • Description: A knowledgebase for effector proteins of type III secretion system (T3SS), type IV secretion system (T4SS) and type VI secretion system (T6SS). SecretEPDB provides enriched annotations of the aforementioned three classes of effector proteins by manually extracting and integrating structural and functional information from currently available databases and the literature.
  • Phosphopredict

    • Developed by: Chris Wang & Bingjiao Young
    • Developed at: 2015
    • Format: Web Server
    • Web Site: http://secretepdb.erc.monash.edu
    • Description: A novel bioinformatics approach to predict kinase-specific phosphorylation substrates and sites in the human proteome by combining informative protein sequence and functional features to build the prediction models using random forest (RF).
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