Curator Dashboard

A Hidden Markov Model-based algorithm for the purpose of defining genome-wide ChIP-enriched peaks in the human genome using short sequence reads.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A Hidden Markov Model based software tool that is developed to detect histone modification in cancer ChIP-seq data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software application that can be used for converting Eland, Maq (.map), BED or other files into WIG files and identifying areas of enrichment (ChIP-Seq analysis).

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A Python package for doing RNA-seq and ChIP-seq (hence the dual-use).

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A high resolution transcription factor binding site (TFBS) identification (deconvolution) algorithm. dPeak implements a probabilistic model that accurately describes ChIP-exo and ChIP-Seq data generation process for both the SET and PET assays.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A Plant MicroRNA Target Expression Database to study the microRNA (miRNA) functions by inferring their target gene expression profiles among the large amount of existing microarray data. You may also predict your miRNA targets and retrieve their microarray expression data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Catalogs of predicted microRNA targets in worm (based on ce6 genome assembly), fly (dm3), mouse (mm9) and human (hg18). We follow standard seed parameter settings and consider seeds of length 6-8 bases, beginning at position 2 of the microRNA. No mismatches or loops are allowed, but a single G:U wobble is allowed in 7- or 8-mers. In genes missing a 3' UTR annotation, 500 bp (fly), 800 bp (human and mouse) or 300 bp (worm) downstream of the annotated end of the coding sequence were used as the predicted UTR. For each organism, a catalog with zero flank and with a flank of 3 and 15 bases upstream and downstream.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software for detecting Co-Occurrence and Spatial Arrangement of Transcription Factor Binding Motifs in Genome-Wide Datasets.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

An integrated web server for identifying miRNA-target interactions in human. The tool enables biologists easily to identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. It also provides perspective of information on the miRNA targets on alternatively spliced transcripts.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A web-based tool used for homologous miRNA gene search in several species. The code is available on request.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Data set of 2003 and 2005 miRNA-Target predictions for Drosophila miRNAs.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

An online database for miRNA target prediction and functional annotations.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software for a specific model, implemented within the MUMMIE framework, for predicting micro-RNA binding sites using PAR-CLIP data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Database of computationally predicted targets for microRNAs across many species.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Web tool to predict biological targets of miRNAs by searching for presence of conserved 8mer, 7mer and 6mer sites that match seed region of each miRNA. Nonconserved sites are also predicted and sites with mismatches in seed region that are compensated by conserved 3' pairing. Used to search for predicted microRNA targets in mammals.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Accurate mapping of RNA-seq reads for splice junction discovery.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A clustering software package for identification of enriched domains from histone modification ChIP-Seq data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Database serving as a tool for microRNA target prediction. The HOCTAR procedure is based on the integration of expression profiling and sequence-based miRNA target recognition softwares. HOCTAR database (db) is the first and unique database to use transcriptomic data to score putative miRNA targets looking at the expression behaviour of their host genes, and it includes and re-analyzes all miRNA target predictions generated by softwares such as miRanda, TargetScan and PicTar. The HOCTARdb contains the prediction target lists for 290 human intragenic miRNAs and also provides tentative assignments of miRNA function based on Gene Ontology analyses of their predicted targets. There are two ways to interrogate HOCTARdb: (i) by selecting a miRNA using either an alphabetically sorted pull-down menu in the microRNA query, or (ii) by typing a target gene symbol (HUGO Gene Name-approved) in the Target Gene Name query.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Manually curated database of experimentally supported animal microRNA targets. Collection of experimentally supported miRNA gene interactions.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Database that hosts elaborated information for both predicted and experimentally verified, miRNA-lncRNA interactions. The database consists of two distinct modules. The Experimental Module contains detailed information for more than 5,000 interactions, between 2,958 lncRNAs and 120 miRNAs, ranging from miRNA and lncRNA related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. The Prediction Module, which is based on the latest version of DIANA-microT target prediction algorithm (DIANA-microT-CDS), contains detailed information for more than 10 million interactions, between 56,097 lncRNAs and 3,078 miRNAs, ranging from miRNA and lncRNA related details to specific information regarding their interaction sites, graphical representation of their binding and the predicted score. This module exhibits a unique feature for searching the database. Users are able to add genomic locations to their queries thus browsing every miRNA-lncRNA interaction that has at least one MRE located inside the queried locus.

• Resource
• SciCrunch
• 13 years ago - by Anonymous