Academic Publications by Cen Wan

(* corresponding author)

ORCID         Bioinformatics Software Developed by Wan Lab         Home Page

    Preprint

  1. Alsaggaf, I., Freitas, A.A., Magalhaes, J.P. and Wan, C. *
    Functional yeast promoter sequence design using autoregressive generative models
    bioRxiv, 2026.
    DOI: 10.1101/2024.10.22.619701. Preprint

  2. Alsaggaf, I., Buchan, D. and Wan, C. *
    Improving cell-type identification with generative adversarial networks-enhanced augmentation-free single-cell RNA-Seq contrastive learning
    bioRxiv, 2025.
    DOI: 10.64898/2025.11.29.691320. Preprint

  3. Alsaggaf, I., Buchan, D. and Wan, C. *
    An extensive evaluation of single-cell RNA-Seq contrastive learning generative networks for intrinsic cell-types distribution estimation
    bioRxiv, 2025.
    DOI: 10.1101/2025.09.15.675691. Preprint

    4. Research-oriented Books

  4. Wan, C.
    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

    5. Journals

  5. Alsaggaf, I., Buchan, D. and Wan, C. *
    Less is more: Improving cell-type identification with augmentation-free single-cell RNA-Seq contrastive learning
    Bioinformatics, btaf437, 2025.
    DOI: 10.1093/bioinformatics/btaf437. PubMed Software
    (SJR quartile 1, the 4th top-ranked computational mathematics journal; JCR quartile 1, the 6th top-ranked mathematical & computational biology journal).

  6. Bhatti, G., Sufriyana, H., ..., Wan, C., ... and Tarca, A.L.
    Placental epigenetic clocks derived from crowdsourcing: Implications for the study of accelerated aging in obstetrics
    iScience, 8(18), 2025.
    DOI: 10.1016/j.isci.2025.113181. PubMed
    (SJR quartile 1; JCR quartile 1).

  7. Alsaggaf, I., Freitas, A.A. and Wan, C. *
    Predicting the pro-longevity or anti-longevity effect of model organism genes with enhanced Gaussian noise augmentation-based contrastive learning on protein-protein interaction networks
    NAR Genomics and Bioinformatics, lqae153, 2024.
    DOI: 10.1093/nargab/lqae153. Author Accepted Manuscript (AAM) Software
    (SJR quartile 1, the 6th top-ranked structural biology journal; JCR quartile 1, the 10th top-ranked mathematical & computational biology journal).

  8. Rafi, A., Penzar, D., ..., Random Promoter DREAM Challenge Consortium (including Wan, C.), ... and de Boer, C.
    A community effort to optimize sequence-based deep learning models of gene regulation
    Nature Biotechnology, 2024.
    DOI: 10.1038/s41587-024-02414-w. Publisher's webpage
    (SJR quartile 1, the 1st top-ranked biotechnology journal; JCR quartile 1, the 2nd top-ranked biotechnology & applied microbiology journal).

  9. Alsaggaf, I., Buchan, D. and Wan, C. *
    Improving cell-type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning
    Briefings in Functional Genomics, elad059, 2024.
    DOI: 10.1093/bfgp/elad059. PubMed Software Server
    (SJR quartile 2; JCR quartile 2).

  10. Wan, C. and Jones, D.T.
    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; JCR quartile 1, the 2nd top-ranked artificial intelligence journal, and the 1st top-ranked computer science, interdisciplinary applications journal).

  11. Zhou, N., Jiang, Y., ..., Wan, C., ..., and Friedberg, I.
    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 9th top-ranked genetics journal; JCR quartile 1, the 5th top-ranked biotechnology & applied microbiology journal).

  12. Wan, C., Cozzetto, D., Fa, R. and Jones, D.T.
    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; JCR quartile 2).

  13. Wan, C. and Freitas, A.A.
    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 on GitHub)
    (SJR quartile 1; JCR quartile 1, the 7th top-ranked computer science, artificial intelligence journal).

  14. Fa, R., Cozzetto, D. Wan, C., and Jones, D.T.
    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; JCR quartile 2).

  15. Wan, C., Lees, J.G., Minneci, F., Orengo, C.A. and Jones, D.T.
    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; JCR quartile 1, the 12th top-ranked mathematical & computational biology journal).

  16. Fernandes, M., Wan, C., Tacutu, R., Barardo, D., Rajput, A., Wang, J., Thoppil, H., Yang, C., Freitas, A.A. and de Magalhaes, J.P.
    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; JCR quartile 2).

  17. Wan, C., Freitas, A.A. and de Magalhaes, J.P.
    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; JCR quartile 1, the 5th top-ranked biochemical research methods journal).

    18. Conferences/Workshops (focusing on machine learning algorithmic novelty)

  18. Wan, C. and Barton, C.
    A novel hierarchy-based knowledge discovery framework for elucidating human aging-related phenotypic abnormalities
    In: Proceedings of the 39th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2024), Avila, Spain, 2024.

  19. Wan, C.
    Predicting the effect of genes on longevity with novel hierarchical dependency-constrained tree augmented naive Bayes classifiers
    In: Proceedings of the 2023 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2023), Istanbul, Turkey, 2023.

  20. Wan, C.
    Positive Feature Values Prioritized Hierarchical Dependency Constrained Averaged One-dependence Estimators for Gene Ontology Feature Spaces
    In: Proceedings of the 2022 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2022), Las Vegas, USA, pages: 826-829, 2022.
    DOI:10.1109/BIBM55620.2022.9995482

  21. Wan, C.
    Positive Feature Values Prioritized Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Hierarchical Feature Spaces
    In: Proceedings of the 2022 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2022), Prague, Czech Republic, pages: 106-110, 2022.
    DOI:10.1109/SMC53654.2022.9945578. Preprint

  22. Wan, C. and Freitas, A.A.
    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

  23. Wan, C. and Freitas, A.A.
    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

  24. Wan, C. and Freitas, A.A.
    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

  25. Wan, C. and Freitas, A.A.
    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

    26. Newsletter & Others

  26. Wan, C.
    Novel Hierarchical Feature Selection Algorithms for Predicting Genes' Aging-related Function
    AI Matters, 2(3):23-24, 2016.
    DOI:10.1145/2911172.2911180. Reprint

  27. Wan, C. and Biktasheva, I.V. and Lane, S.
    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

    28. PhD Thesis

  28. Wan, C.
    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