ISMB 2022 - Improving Protein Interaction Prediction on Unseen Proteins

Presenting our RAPPPID manuscript at the Intelligent Systems for Molecular Biology meeting in Madison, Wisconsin, U.S.A. The workshop was attended in-person and virtually between 10-14 July.

Presentation

Presentation Thumbnail

A pre-recorded version of this presentation can be downloaded here:

▶ rapppid_1080p.webm (125 MB)

▶ rapppid_720p.webm (64 MB)

▶ rapppid_480p.webm (33 MB)

You can download the slides in PDF format here:

⇓ 2022_ISMB_RAPPPID.pdf (9 MB)

Poster

You can download the poster we presented at ISMB 2022 here: ⇓ poster.pdf (3 MB)

RAPPPID

Manuscript

You can find our paper published at OUP Bioinformatics:

Szymborski J, Emad A. RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks. Bioinformatics. 2022 Jun 30:btac429. doi: 10.1093/bioinformatics/btac429. Epub ahead of print. PMID: 35771595.

A pre-print can be downloaded from bioRxiv.

References

Presentation References

You can find the references in this presentation within this Zotero Web Collection. You can also download them in BibTeX format: ⇓ references.bib (8.7 KB).

Poster References

  1. Snider, J. et al. (2015) Fundamentals of protein interaction network mapping. Mol Syst Biol, 11, 848. DOI: 10.15252/msb.20156351
  2. Park, Y. and Marcotte, E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat Methods, 9, 1134–1136. DOI: 10.1038/nmeth.2259
  3. Merity, S. et al. (2017) Regularizing and Optimizing LSTM Language Models. arXiv:1708.02182 [cs].
  4. Kudo, T. and Richardson, J. (2018) SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing. In, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics, Brussels, Belgium, pp. 66–71 DOI: 10.18653/v1/D18-2012
  5. Szklarczyk, D. et al. (2019) STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res, 47, D607–D613. DOI: 10.1093/nar/gky1131