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Creators/Authors contains: "Bastani, Osbert"

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  1. ; ; ( , POPL)
  2. ; ; ; ; ; ; ( , Genome Biology)
    Abstract

    Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions. Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity models for 79 human RBPs and the annotated human genome to produce improved models of RBP binding and activity. Binding and activity are modeled by separate Motif and Aggregator components that can be mixed and matched, enforcing sparsity to improve interpretability. Training a new Adjusted Motif (AM) architecture on the splicing task not only yields better splicing predictions but also improves prediction of RBP-binding sites in vivo and of splicing activity, assessed using independent data.

     
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  3. ; ; ( , ICML)
  4. ; ; ; ( , CAV)
  5. ; ; ; ( , Proceedings of the AAAI Conference on Artificial Intelligence)
    Free, publicly-accessible full text available June 30, 2024
  6. ; ; ; ; ( , AISTATS)
  7. ; ; ; ( , International Conference on Learning Representations)
    Accepted Manuscript Full Text Available
  8. ; ; ; ( , Annual Meeting of the Association for Computational Linguistics)
    Accepted Manuscript Full Text Available
  9. ; ; ; ( , 60th Annual Meeting of the Association for Computational Linguistics)
    Accepted Manuscript Full Text Available
  10. ; ; ; ( , International Conference on Machine Learning)
    Accepted Manuscript Full Text Available