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Updated: May 15, 2026

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Published on: December 1, 2023

scRAPID-web: a web server for predicting protein-RNA interactions from single-cell transcriptomics.

Jonathan Fiorentino¹, Alexandros Armaos², Chiara Montrone^1,3

¹Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), Rome, 00161, Italy.

|May 14, 2026

Summary

This summary is machine-generated.

scRAPID-web provides a user-friendly platform for analyzing single-cell RNA sequencing data to predict RNA-binding protein (RBP) interactions. This tool enhances understanding of gene regulation by identifying key RBPs and their RNA targets.

Keywords:

Gene regulatory network Long non-coding RNA Protein–RNA interaction RNA-binding protein Single-cell transcriptomics Web server

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Published on: July 12, 2022

Area of Science:

Computational biology
Genomics
Bioinformatics

Background:

Single-cell RNA sequencing (scRNA-seq) offers high-resolution gene expression analysis at the cellular level.
Previous work established scRAPID, a pipeline for predicting RNA-binding protein (RBP)-RNA interactions and identifying hub RBPs using gene regulatory network (GRN) inference and catRAPID.
scRAPID-web is introduced to broaden access to these analyses.

Purpose of the Study:

To develop a user-friendly web server (scRAPID-web) for predicting RBP-RNA and RBP-RBP interactions.
To enable analysis of scRNA-seq data across eight model organisms.
To democratize access to GRN-based analyses for RBP-RNA interactions.

Main Methods:

scRAPID-web incorporates customizable preprocessing options for scRNA-seq data, including gene selection and cell type filtering.
Users can select from three GRN inference algorithms and specify analysis focus on particular gene types.
The platform includes precompiled libraries for efficient filtering and motif-based validation of inferred interactions.

Main Results:

scRAPID-web generates detailed tables of predicted protein-RNA pairs and hub proteins.
Interactive network visualizations display potential RBP complexes based on shared target analysis.
The server facilitates prediction of RBP-RNA and RBP-RBP interactions from scRNA-seq data.

Conclusions:

scRAPID-web democratizes GRN-based analysis of gene regulation from scRNA-seq data.
The tool provides insights into RBP-RNA interactions and regulatory complexes.
scRAPID-web is freely accessible, supporting broader research in gene regulation.