RNAfinder
cfRNAfinder
App, AI Model Pengfei Bao, Taiwei Wang, et al. Genome Biology (2025)

cfPeak is a CNN model finding fragmented cell-free RNAs for disease diagnosis and prognosis.

Database Mingyang Li, Tianxiu Zhou, Mingfei Han, et al. Nucleic Acids Research (2024)

Multi-Omics data and diagnosis panels for liquid biopsy of cancer and other diseases.

App, AI Model Xiaofan Liu, Yuhuan Tao, et al. Bioinformatics (2024)

PathFormer is a Transformer model integrating multiomics data for disease diagnosis and prognosis.

ncRNAfinder
App Qing Zhan, Pengfei Bao, Yuhuan Tao, et al. (2025)

A tool to identify double-stranded RNAs (dsRNAs) in human.

App Zhiyu Xu, Long Hu, Binbin Shi, SiSi Geng, et al. Nucleic Acids Research (2018)

RiboWave analyses Ribosome profiling data (Ribo-seq). It utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes (i.e. signal frequency) and precisely locate their footprint.

App, Machine Learning Model Long Hu, et al. Nucleic Acids Research (2017)

COME is a tool to calculate COding potential from Multiple fEatures for a given transcript. The models in COME were trained on mRNAs and long ncRNAs (lncRNAs).

App, Machine Learning Model Long Hu, et al. Nucleic Acids Research (2015)

RNAfeature provides a common set of conserved features for ncRNAs across multiple species. The models in RNAfeature were trained on canonical ncRNAs (e.g., tRNAs, rRNAs, miRNAs, snRNAs, snoRNAs, 7SK RNAs, Y RNAs).

RNAtalk
RNA-RNA
App, AI Model Yilan Bai et al. Bioinformatics (2024)

OligoFormer is AI model designing small RNA drug targeting RNA.

RNA-Ligand
App, AI Model Hongli Ma et al. Nature Computational Science (2025)

RNAsmol is an AI model designing small molecule drug targeting RNA.

RNA-Protein
App Yang Eric Li, Mu Xiao, Binbin Shi, Yu-Cheng T. Yang, et al. Genome Biology (2017)

RBPgroup is a soft-clustering method on various CLIP-seq datasets, in order to group together RBPs that specifically bind the same RNA sites. Our approach links proteins and RNA motifs known to possess similar biochemical and cellular properties and can, when used in conjunction with additional experimental data, identify high-confidence RBP groups and their associated RNA regulatory elements.

Database V3: Weihao Zhao, Shang Zhang, et al. Nucleic Acids Research (2022)
V2: Yumin Zhu, Gang Xu, Yu-Cheng T. Yang, et al. Nucleic Acids Research (2017)
V1: Boqin Hu, Yu-Cheng T. Yang, et al. Nucleic Acids Research (2017)
V0 (CLIPdb): Yu-Cheng T. Yang, Chao Di, Boqin Hu, et al. BMC Genomics (2015)

POSTAR is a platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins. It enables experimental biologists to connect protein-RNA interactions with multi-layer information of post-transcriptional regulation and functional genes, and helps them generate novel hypotheses about the post-regulatory mechanisms of phenotypes and diseases.

POSTAR was upgraded from CLIPdb, which is an integrative resource of CLIP-seq studies. It aims to characterize the regulatory networks between RNA binding proteins (RBPs) and various RNA transcript classes by integrating large amounts of CLIP-seq (including HITS-CLIP, PAR-CLIP and iCLIP as variations) data sets.

Others
App Yang Wu, Binbin Shi, et al. Nucleic Acids Research (2015)

RME is a tool for RNA secondary structure prediction with multiple types of experimental probing data. It is based on the RNAstructure package. It also provides preprocessing scripts for transforming the SHAPE, PARS and DMS-seq data into pairing probability according a posterior probabilistic model. Moreover, it also contains a utility for optimizing the parameters of RME by RME-Optimize.

RNAstructure: RNAex
Web Server Yang Wu, Rihao Qu, Yiming Huang, et al. Nucleic Acids Research (2016)

RNAex is an RNA secondary structure prediction server enhanced by high-throughput experimental data. We have re-mapped raw data of the published probing experiments to the whole genome, thus users can predict secondary structures for novel RNA transcripts.

RNAmed: CCG
Web Server Mengrong Liu, Yu-Cheng T. Yang, et al. Discovery Medicine (2016)

CCG, Catalogue of Cancer Genes/lncRNAs, is an assembly resource of coding and noncoding genes associated with cancer. In addition, drug-gene information in CCG provides a useful guide to the development of new anti-cancer drugs.