:: DESCRIPTION
pirnaPre is a SVM classifier based on a combination of Miwi CLIP-Seq derived features and position derived features to predict potential targets of piRNAs on mRNAs.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Computational identification of piRNA targets on mouse mRNAs.
Yuan J, Zhang P, Cui Y, Wang J, Skogerbø G, Huang DW, Chen R, He S.
Bioinformatics. 2015 Dec 16. pii: btv729.
:: DESCRIPTION
miRanda is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL. miRanda reads RNA sequences (such as microRNAs) from file1 and genomic DNA/RNA sequences from file2. Both of these files should be in FASTA format.
::DEVELOPER
the Computational Biology Center of Memorial Sloan-Kettering Cancer Center.
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS.,
Human MicroRNA Targets
PLoS Biol. 2005 Jul;3(7):e264.
:: DESCRIPTION
TENET (Target Characterization using Network Topology) first computes a set of topological features and then leverages a SVM-based approach to identify predictive topological features that characterizes known targets.
::DEVELOPER
Computational Systems Biology Research Group (COSBY)
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
TENET: Topological Feature-based Target Characterization in Signaling Networks.
Chua HE, Bhowmick SS, Tucker-Kellogg L, Dewey CF Jr.
Bioinformatics. 2015 Jun 16. pii: btv360
:: DESCRIPTION
RNA22 finds putative microRNA binding sites in the sequence of interest, then identifies the targeting microRNA.
::DEVELOPER
the Computational Medicine Center at the Sidney Kimmel Medical College of Thomas Jefferson University
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Bioinformatics. 2012 Dec 15;28(24):3322-3. doi: 10.1093/bioinformatics/bts615. Epub 2012 Oct 16.
Interactive exploration of RNA22 microRNA target predictions.
Loher P1, Rigoutsos I.
:: DESCRIPTION
psRNATarget is a plant small RNA target analysis server, which features two important analysis functions: 1) reverse complementary matching between miRNA and target transcript using a proven scoring schema, and 2) target site accessibility evaluation by calculating unpaired energy (UPE) required to “open” secondary structure around miRNA’s target site on mRNA.
::DEVELOPER
The Zhao Bioinformaitcs Lab at the Samuel Roberts Noble Foundation
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Nucleic Acids Res. 2011 Jul;39(Web Server issue):W155-9. doi: 10.1093/nar/gkr319. Epub 2011 May 27.
psRNATarget: a plant small RNA target analysis server.
Dai X1, Zhao PX.
:: DESCRIPTION
SVMicrO is a 2-stage SVM based new miRNA target prediction algorithm. It assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SMVicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features.
::DEVELOPER
:: SCREENSHOTS
N/A
::REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2010 Sep 22;11:476. doi: 10.1186/1471-2105-11-476.
Improving performance of mammalian microRNA target prediction.
Liu H1, Yue D, Chen Y, Gao SJ, Huang Y.
:: DESCRIPTION
CT-Finder is a web service that allows a user to upload DNA sequences, set specifications according to experimental goals, and receive candidate guide RNA targets.
CRISPR-DT is a web application that allows a user to upload DNA sequences, set specifications according to experimental goals, and recieve target candidates. Optimal candidates are suggested through consideration of predicted target efficiency and off-target effect. A visualization of on- and off-target matches against the chosen reference genome is provided in JBrowse.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Zhu H, Liang C.
CRISPR-DT: designing gRNAs for the CRISPR-Cpf1 system with improved target efficiency and specificity.
Bioinformatics. 2019 Aug 15;35(16):2783-2789. doi: 10.1093/bioinformatics/bty1061. PMID: 30615056.
CT-Finder: A Web Service for CRISPR Optimal Target Prediction and Visualization.
Zhu H, Misel L, Graham M, Robinson ML, Liang C.
Sci Rep. 2016 May 23;6:25516. doi: 10.1038/srep25516.
:: DESCRIPTION
TargetOrtho provides a cost- and time-efficient in silico approach for the identification of novel TF target genes, and, together with its CRM search function, is poised to unravel the regulatory logic of diverse biological processes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Genetics. 2014 May;197(1):61-76. doi: 10.1534/genetics.113.160721. Epub 2014 Feb 20.
TargetOrtho: a phylogenetic footprinting tool to identify transcription factor targets.
Glenwinkel L1, Wu D, Minevich G, Hobert O.
:: DESCRIPTION
Given a set of input genomic regions, MotifScan scans the sequences to detect the occurrences of known motifs. It can also applies a statistical test on each motif to check whether the motif is significantly over- or under-represented (enriched or depleted) in the input genomic regions compared to another set of control regions.
::DEVELOPER
ShaoLab at CAS-MPG Partner Institute for Computational Biology, SIBS, CAS.
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Sun, H., Wang, J., Gong, Z. et al.
Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters.
Cell Discov 4, 38 (2018).
:: DESCRIPTION
ComiR (Combinatorial miRNA targeting) predicts whether a given mRNA is targeted by a set of miRNAs. ComiR uses miRNA expression to improve and combine multiple miRNA targets for each of the four prediction algorithms: miRanda, PITA, TargetScan and mirSVR.
::DEVELOPER
SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
C. Coronnello, R. Hartmaier, A. Arora, L. Huleihel, K.V. Pandit, A.S Bais, M. Butterworth, N. Kaminski, G.D. Stormo, S. Oesterreich, P.V. Benos (2012),
Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density,
PLoS Comput Bio 8(12): e1002830. doi:10.1371/journal.pcbi.1002830
