[Selected publications] [Major works in one slide]

Journal(*equal contribution)

  1. DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing.
    Y Li*, S Wang*, C Bi, Z Qiu, M Li, X Gao. Bioinformatics, 2020. [Code] [PDF]
  2. A Self-adaptive Deep Learning Algorithm for Accelerating Multi-component Flash Calculation.
    T Zhang, Y Li, Y Li, S Sun, and X Gao. Computer Methods in Applied Mechanics and Engineering, 2020, accepted.
  3. Modern Deep Learning in Bioinformatics.
    H Li*, S Tian*, Y Li*, R Tan, Y Pan, C Huang, Y Xu, and X Gao. Journal of Molecular Cell Biology, 2020, accepted.
  4. DeeReCT-APA: prediction of alternative polyadenylation site usage through deep learning.
    Z Li, Y Li, B Zhang, Y Li, Y Long, X Zou, M Zhang, Y Hu, W Chen, X Gao. Genomics, Proteomics & Bioinformatics (GPB), 2020, accepted.
  5. A deep learning framework to predict binding preference of RNA constituents on protein surface.
    J Lam*, Y Li*, L Zhu, R Umarov, H Jiang, A Heliou, F Sheong, T Liu, Y Long, Y Li, L Fang, R Altman, W Chen, X Huang, X Gao. Nature Communications, 2019.
    [KAUST news] [Chinese introduction] [PDF] [Code] [Server]
  6. Estimating heritability and genetic correlations from large health datasets in the absence of genetic data.
    G Jia, Y Li, H Zhang, I Chattopadhyay, A Jensen, D Blair, L Davis, P Robinson, T Dahlén, S Brunak, M Benson, G Edgren, N Cox, X Gao, A Rzhetsky. Nature Communications, 2019. [PDF]
    [UChicago news] [Chinese introduction]
  7. Two symmetric Arginine residues play distinct roles in Thermus thermophilus Argonaute DNA guide strand-mediated DNA target cleavage.
    J Lei, G Sheng, P Cheung, S Wang, Y Li, X Gao, Y Zhang, Y Wang, X Huang. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019.
  8. Accelerating Flash Calculation through Deep Learning Methods.
    Y Li, T Zhang, S Sun, X Gao. Journal of Computational Physics, 2019. [PDF]
  9. Deep learning in bioinformatics: introduction, application, and perspective in big data era.
    Y Li, C Huang, L Ding, Z Li, Y Pan, X Gao. Methods, 2019. [PDF] [Code]
    Cover article of the Methods issue: Deep Learning in Bioinformatics
  10. mlDEEPre: Multi-functional enzyme function prediction with hierarchical multi-label deep learning.
    Z Zou, S Tian, X Gao, Y Li#. Frontiers in Genetics, 2019. [PDF] [Server]
  11. Promoter analysis and prediction in the human genome using sequence-based deep learning models.
    R Umarov, H Kuwahara, Y Li, X Gao, V Solovyev. Bioinformatics, 2019. [PDF] [Code]
  12. H-NS uses an autoinhibitory conformational switch to achieve environment-controlled gene silencing.
    U Hameed, C Liao, A Radhakrishnan, F Huser, S Aljedani, X Zhao, A Momin, F Melo, X Guo, C Brooks, Y Li, X Cui, X Gao, J Ladury, L Jaremko, M Jaremko, J Li, S, Arold. Nucleic Acids Research (NAR), 2018.
  13. DeeReCT-PolyA: a robust and generic deep learning method for PAS identification.
    Z Xia, Y Li, B Zhang, Z Li, Y Hu, W Chen, X Gao. Bioinformatics, 2018. [PDF] [Code]
  14. DeepSimulator: a deep simulator for nanopore sequencing.
    Y Li, R Han, C Bi, M Li, S Wang, X Gao. Bioinformatics, 2018. [PDF] [Code]
  15. DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy.
    Y Li, F Xu, F Zhang, P Xu, M Fan, L Li, X Gao, R Han. Bioinformatics, 2018. [PDF] [Code]
  16. PredMP: a web server for de novo prediction and visualization of membrane proteins.
    S Wang, S Fei, Z Wang, Y Li, J Xu, F Zhao, X Gao. Bioinformatics, 2018. [PDF] [Server]
  17. An accurate and rapid continuous wavelet dynamic time warping algorithm for end-to-end mapping in ultra-long nanopore sequencing.
    R Han, Y Li, X Gao, S Wang. Bioinformatics, 2018. [PDF] [Code]
  18. DES-Mutation: System for Exploring Links of Mutations and Diseases.
    V Kordopati, A Salhi, R Razali, A Radovanovic, F Tifratene, M Uludag, Y Li, A Bokhari, A AlSaieedi, A Raies, C Neste, M Essack, V Bajic. Scientific Reports, 2018. [PDF] [Server]
  19. AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction.
    R Han, X Wan, L Li, A Lawrence, P Yang, Y Li, S Wang, F Sun, Z Liu, X Gao, F Zhang. Bioinformatics, 2018.
  20. DEEPre: sequence-based enzyme EC number prediction by deep learning.
    Y Li, S Wang, R Umarov, B Xie, M Fan, L Li, X Gao. Bioinformatics, 2017. [PDF] [Server]
  21. Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape.
    H Dai, R Umarov, H Kuwahara, Y Li, L Song, X Gao. Bioinformatics, 2017. [PDF] [Code]
  22. The dynamic multisite interactions between two intrinsically disordered proteins.
    S Wu, D Wang, J Liu, Y Feng, J Weng, Y Li, X Gao, J Liu, W Wang. Angewandte Chemie, 2017.
  23. Reward sensitivity predicts ice cream-related attentional bias assessed by inattentional blindness.
    X Li, Q Tao, Y Fang, C Cheng, Y Hao, J Qi, Y Li, W Zhang, Y Wang, X Zhang. Appetite, 2015.

Conference(*equal contribution)

  1. RNA Secondary Structure Prediction By Learning Unrolled Algorithms.
    X Chen*, Y Li*, R Umarov, X Gao, L Song. Eighth International Conference on Learning Representations ( ICLR-20),
    Oral(Accpetance rate=48/2599=1.85%)
    [GaTech news] [Chinese news] [Chinese introduction] [Plain explanation]
  2. Learning to Stop While Learning to Predict.
    X Chen, H Dai, Y Li, X Gao, and L Song. Thirty-seventh International Conference on Machine Learning ( ICML-20).
  3. Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test.
    L Ding, M Yu, L Liu, F Zhu, Y Liu, Y Li, L Shao. Thirty-third Conference on Neural Information Processing Systems ( NeurIPS-19)
  4. Linear Kernel Tests via Empirical Likelihood for High Dimensional Data.
    L Ding, Z Liu, Y Li, S Liao, Y Liu, P Yang, G Yu, L Shao, X Gao. The Thirty-Third AAAI Conference on Artificial Intelligence ( AAAI-19)
  5. Approximate Kernel Selection with Strong Approximate Consistency.
    L Ding, S Liao, Y Liu, Y Li, P Yang, Y Pan, C Huang, L Shao, X Gao. The Thirty-Third AAAI Conference on Artificial Intelligence ( AAAI-19)
  6. DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy.
    Y Li*, F Xu*, F Zhang, P Xu, M Fan, L Li, X Gao, R Han. The Twenty-Sixth Conference on Intelligent Systems for Molecular Biology ( ISMB-18)
  7. An accurate and rapid continuous wavelet dynamic time warping algorithm for end-to-end mapping in ultra-long nanopore sequencing.
    R Han, Y Li, X Gao, S Wang. The Seventeenth European Conference on Computational Biology ( ECCB-18)

Preprint or under review(*equal contribution)

  1. HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes.
    Y Li, Z Xu, W Han, H Cao, R Umarov, A Yan, M Fan, H Chen, L Li, P Ho, X Gao. Gut, under review.
  2. Long-read Individual-molecule Sequencing Reveals CRISPR-induced Genetic Heterogeneity in Human ESCs.
    C Bi, L Wang, B Yuan, X Zhou, Y Li, S Wang, Y Pang, X Gao, Y Huang, M Li. bioRxiv 942151, 2020.
  3. SupportNet: solving catastrophic forgetting in class incremental learning with support data.
    Y Li, Z Li, L Ding, Y Hu, W Chen, X Gao. arxiv.org/abs/1806.02942
  4. On the decision boundary of deep neural networks.
    Y Li, L Ding, X Gao. arxiv.org/abs/1808.05385
  5. PGCN: Disease gene prioritization by disease and gene embedding through graph convolutional neural networks.
    Y Li, H Kuwahara, P Yang, L Song, X Gao. bioRxiv 532226