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  1. HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence.

    Molecular cell · 2023 · 83(14): 2595-2611.e11

    RNA-binding proteins (RBPs) control RNA metabolism to orchestrate gene expression and, when dysfunctional, underlie human diseases. Proteome-wide discovery efforts predict thousands of RBP candidates, many of which lack canonical RNA-binding domains (RBDs). Here, we present a hybrid ensemble RBP classifier …

    PMID 37421941 DOI ↗

  2. Direct RNA sequencing enables m<sup>6</sup>A detection in endogenous transcript isoforms at base-specific resolution.

    RNA (New York, N.Y.) · 2020 · 26(1): 19-28

    Direct RNA sequencing holds great promise for the de novo identification of RNA modifications at single-coordinate resolution; however, interpretation of raw sequencing output to discover modified bases remains a challenge. Using Oxford Nanopore's direct RNA sequencing technology, we developed a …

    PMID 31624092 DOI ↗

Datasets 4

GSE14333 GSE · GEO

Expression data from 290 primary colorectal cancers

Homo sapiens · GPL570

GSE13067 GSE · GEO

Expression data from primary colorectal cancers

Homo sapiens · GPL570

GSE17536 GSE · GEO

Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (Moffitt Samples)

Homo sapiens · GPL570

GSE221870 GSE · GEO

HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

Homo sapiens · GPL16791

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