PLERIO single-protein model weights

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Authors: А.В. Рыбаков, Daniil A. Khlebnikov
Cited by: 0

Abstract

This deposit contains trained model weights for PLERIO, a sequence-based framework for imputing RNA–protein interactions from eCLIP data, as described in the IJMS manuscript: "Sequence-based models for RNA-Protein interactions imputation might be insufficient for novel signal prediction in eCLIP data." The included weights correspond to models trained on eCLIP datasets and are provided to support reproducibility and further benchmarking. These models rely solely on protein and RNA sequence features (e.g., ESM2 and UniRep embeddings) and do not incorporate structural or complex-aware information. Note: As discussed in the paper, PLERIO’s current multiprotein inference mode is prone to false positives/negatives and should not be used for de novo prediction on unseen proteins without caution. For usage instructions, preprocessing pipelines, and evaluation scripts, please refer to the associated GitHub repositories (PLERIO repository and supporting scripts).

Fields of Study & Subjects

RNA Research and Splicing Machine Learning in Bioinformatics Genomics and Chromatin Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
14 January 2026
Document type
Dataset