Academic Publications by Cen Wan

Google Scholar         Short Biography


  1. C. Wan and A.A. Freitas
    Hierarchical Dependency Constrained Tree Augmented Naive Bayes Classifiers for Hierarchical Feature Spaces
    arXiv:2202.04105 , 2022. Preprint
  2. Research-oriented Books

  3. C. Wan
    Hierarchical Feature Selection for Knowledge Discovery: Application of Data Mining to the Biology of Ageing
    Springer, 2019. ISBN: 978-3-319-97918-2. Publisher's webpage
  4. Journals

  5. C. Wan and D.T. Jones
    Protein function prediction is improved by creating synthetic feature samples with generative adversarial networks
    Nature Machine Intelligence, 2:540-550, 2020.
    DOI: 10.1038/s42256-020-0222-1. Reprint
    (*SJR quartile 1 – the 2nd top-ranked artificial intelligence journal).
  6. N. Zhou, Y. Jiang, ..., C. Wan, ..., and I. Friedberg
    The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
    Genome Biology, 20(1):244, 2019.
    DOI:10.1186/s13059-019-1835-8. PubMed
    (*SJR quartile 1 – the 5th top-ranked genetics journal).
  7. C. Wan, D. Cozzetto, R. Fa, and D.T. Jones
    Using Deep Maxout Neural Networks to Improve the Accuracy of Function Prediction from Protein Interaction Networks
    PLOS One, 14(7): e0209958, 2019.
    DOI:10.1371/journal.pone.0209958. PubMed
    (*SJR quartile 1).
  8. C. Wan and A.A. Freitas
    An Empirical Evaluation of Hierarchical Feature Selection Methods for Classification in Bioinformatics Datasets with Gene Ontology-based Features
    Artificial Intelligence Review, 50(2):201-240, 2018.
    DOI:10.1007/s10462-017-9541-y. Preprint (original research article, source code available onGitHub)
    (*SJR quartile 1).
  9. R. Fa, D. Cozzetto, C. Wan, and D.T. Jones
    Predicting Human Protein Function with Multi-task Deep Neural Networks
    PLOS One, 13(6): e0198216, 2018.
    DOI:10.1371/journal.pone.0198216. PubMed
    (*SJR quartile 1).
  10. C. Wan, J.G. Lees, F. Minneci, C.A. Orengo, and D.T. Jones
    Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster
    PLOS Computational Biology, 13(10): e1005791, 2017.
    DOI:10.1371/journal.pcbi.1005791. PubMed (novel fly protein function predictions)
    (*SJR quartile 1 – the 8th top-ranked computational theory and mathematics journal).
  11. M. Fernandes, C. Wan, R. Tacutu, D. Barardo, A. Rajput, J. Wang, H. Thoppil, C. Yang, A.A. Freitas, and J.P. de Magalhaes
    Systematic analysis of the gerontome reveals links between aging and age-related diseases
    Human Molecular Genetics, 25(21), 4804-4818, 2016.
    DOI:10.1093/hmg/ddw307. PubMed
    (*SJR quartile 1 – the 8th top-ranked Genetics (clinical) journal).
  12. C. Wan, A.A. Freitas, and J.P. de Magalhaes
    Predicting the pro-longevity or anti-longevity effect of model organism genes with new hierarchical feature selection methods
    IEEE/ACM Transactions on Computational Biology and Bioinformatics, 12(2):262-275, 2015.
    DOI:10.1109/TCBB.2014.2355218. PubMed (Datasets Used in the Experiments)
    (*SJR quartile 2).
  13. Conferences/Workshops (focusing on machine learning algorithmic novelty)

  14. C. Wan and A.A. Freitas
    Hierarchical Dependency Constrained Averaged One-Dependence Estimators Classifiers for Hierarchical Feature Spaces
    In: Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020), online (Aalborg, Denmark), PMLR, 138:557-568, 2020. Reprint
  15. C. Wan and A.A. Freitas
    A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features
    In: Proceedings of the 33rd International Conference on Machine Learning (ICML 2016) Workshop on Computational Biology, New York, USA. (paper, poster, selected for spotlight talk). Reprint
  16. C. Wan and A.A. Freitas
    Two Methods for Constructing a Gene Ontology-based Feature Selection Network for a Bayesian Network Classifier and Applications to Datasets of Aging-related Genes.
    In: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB 2015), Atlanta, USA, pages: 27-36, 2015.
    DOI:10.1145/2808719.2808722. Reprint
  17. C. Wan and A.A. Freitas
    Prediction of the pro-longevity or anti-longevity effect of Caenorhabditis Elegans genes based on Bayesian classification methods
    In: Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine (IEEE-BIBM 2013), Shanghai, China, pages: 373-380, 2013.
    DOI:10.1109/BIBM.2013.6732521. PubMed
  18. Newsletter & Others

  19. C. Wan
    Novel Hierarchical Feature Selection Algorithms for Predicting Genes' Aging-related Function
    AI Matters, 2(3):23-24, 2016.
    DOI:10.1145/2911172.2911180. Reprint
  20. C. Wan and I.V. Biktasheva and S. Lane
    The application of a perceptron model to classify an individual's response to a proposed loading dose regimen of Warfarin
    arXiv:1211.2945, 2012. Reprint
  21. PhD Thesis

  22. C. Wan
    Novel Hierarchical Feature Selection Methods for Classification and Their Application to Datasets of Ageing-Related Genes
    Doctor of Philosophy (PhD) thesis, University of Kent, 2015. Reprint