Juan Almagro Armenteros "DeepLoc 2.0: multi-label subcellular localization prediction using protein language models"
⌚️ Thursday 27 July, 20.00 (Moscow time)
The talk will be in English. (It might be useful for CAFA5 Kaggle competition participants. Announcement on Kaggle.)
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The talk will be based on the recent paper with the same title (Nucleic Acids Res. 2022 ).
The prediction of protein subcellular localization is of great relevance for proteomics research. Here, we propose an update to the popular tool DeepLoc with multi-localization prediction and improvements in both performance and interpretability. For training and validation, we curate eukaryotic and human multi-location protein datasets with stringent homology partitioning and enriched with sorting signal information compiled from the literature. We achieve state-of-the-art performance in DeepLoc 2.0 by using a pre-trained protein language model. It has the further advantage that it uses sequence input rather than relying on slower protein profiles. We provide two means of better interpretability: an attention output along the sequence and highly accurate prediction of nine different types of protein sorting signals. We find that the attention output correlates well with the position of sorting signals. The webserver is available at services.healthtech.dtu.dk/service.php?DeepLoc-2.0.
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Zoom link will be available in https://t.me/sberlogabig shortly before start of the talk.
https://us02web.zoom.us/j/85437399900?pwd=QXZjcGNHaXpiYjRtUTlNMzZ1WXZDdz09
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