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Showing 1–6 of 6 results
Advanced filters: Author: Duolin Wang Clear advanced filters

  • Single-cell multi-omics and deep learning could lead to the inference of biological networks across specific cell types. Here, the authors develop DeepMAPS, a deep learning, graph-based approach for cell-type specific network inference from single-cell multi-omics data that is tested on healthy and tumour tissue datasets.

    • Anjun Ma
    • Xiaoying Wang
    • Qin Ma
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-18

  • Pachytene Piwi-interacting RNAs (piRNAs) expressed in mammalian germ lines are abundant, but their evolution and function are not fully understood. Here, the authors find that pachytene piRNA loci are hotspots of structural variation, which underlies rapid piRNA birth, divergence, and loss.

    • Yu H. Sun
    • Hongxiao Cui
    • Xin Zhiguo Li
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-16

  • Predicting whether T cell receptors bind to specific peptides is a challenging problem because most binding examples in the training data involve only a few peptides. A new approach uses meta-learning to improve predictions for binding to peptides for which no or little binding data exists.

    • Duolin Wang
    • Fei He
    • Dong Xu
    News & Views
    Nature Machine Intelligence
    Volume: 5, P: 337-339

  • Diffusion models are deep-learning-based generative models that can generate new data from input parameters. This Review discusses applications of diffusion models in bioinformatics and computational biology.

    • Zhiye Guo
    • Jian Liu
    • Jianlin Cheng
    Reviews
    Nature Reviews Bioengineering
    Volume: 2, P: 136-154