MicroRNA target site identification software tools | CLIP sequecing data analysis
MicroRNAs (miRNAs) play a critical role in down-regulating gene expression. By coupling with Argonaute family proteins, miRNAs bind to target sites on mRNAs and employ translational repression. A large amount of miRNA-target interactions (MTIs) have been identified by the crosslinking and immunoprecipitation (CLIP) and the photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) along with the next-generation sequencing (NGS).
A biophysical model of miRNA-target interaction and infer its energy parameters from Ago-CLIP data. MIRZA includes parameters associated with base pairs and loops and specific miRNA position–dependent energy parameters that reflect the constraints imposed by the Argonaute protein on miRNA-mRNA interaction. MIRZA predicts the frequencies with which RNA-induced silencing complexes (RISCs) bind to different mRNA fragments in the mRNA pool.
Identifies canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter extracts peak sequences, annotates on the genome and converts miRNA sequences in Homer format by using Homer software. This pipeline works for mouse and human miRNA-mRNA pairs. miRBShunter is a valuable resource for researchers working on miRNA biology due to its easy applicability and reliability of the results.
Allows users simultaneously perform mRNA and miRNA expression analysis. wapRNA is a web application that includes major processes for the next-generation mRNA or miRNA data analysis, including preprocessing raw sequenced reads, mapping tags to reference sequences, gene expression annotation, and other downstream functional analysis such as detecting differentially expressed genes, Gene Ontology and KEGG pathway analysis for RNA, novel miRNA predication and miRNA target prediction. Executable packages are available for users to build their pipeline locally.
A model for miRNA target prediction through discriminative learning on transcriptome-wide AGO CLIP and CLASH profiles. Our goal was to learn to accurately predict biochemical miRNA-target site interactions, rather than the extent of regulation, in order to increase the sensitivity of miRNA target prediction and learn physiological targeting rules. chimiRic produces more accurate predictions than state-of-the-art methods based on indirect measurements. Moreover, interpretation of the learned model reveals novel features of miRNA-mRNA interactions, including potential cooperativity with specific RNA-binding proteins.
A systematic approach for mining miRNA-target sites from CLIP-Seq and PAR-CLIP sequencing data, and integrated the workflow with a graphical web-based browser, which provides a user friendly interface and detailed annotations of MTIs.
Predicts human-specific miRNA-mRNA target pair. Context-MMIA utilizes both expression profiles and the literature information from the user-specified experimental design goals. It employs a set of keywords from the user to specify the context of the experiment using a context score. The tool’s performance depends on how the keywords to specify context are related to the goal of the experiment.
Allows the discovery of circRNAs and their interactions with miRNAs. circTools investigates the high-throughput AGO CLIP-Seq and RNA-Seq data to proceed. It employs functionalities of circSeeker, circAnno, clipSearch and offers a web interface to simplify their utilization. This tool was designed to ease the study of circRNA-miRNA interactions.
Recognizes back-splicing junctions of circular RNAs (circRNAs) from crosslinking and immunoprecipitation (CLIP-seq) datasets. circScan creates full read alignments with back-splicing signals. It can identify bona fide circRNAs rather than false positives. It was applied to CLIP-seq datasets derived from mouse, and discovered more than 1000 novel interactions between 36 RNA-binding proteins (RBPs) and 918 circRNAs.
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