RNA interference (RNAi) has become a powerful genetic approach to systematically dissect gene function on a genome-wide scale. Owing to the penetrance and efficiency of RNAi in invertebrates, model organisms such as Drosophila melanogaster and Caenorhabditis elegans have contributed significantly to the identification of novel components of diverse biological pathways, ranging from early development to fat storage and aging.
DSAP is an automated multiple-task web service designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. DSAP uses a tab-delimited file as an input format, which holds the unique sequence reads (tags) and their corresponding number of copies generated by the Solexa sequencing platform.
Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes.
Standard DNA alignment programs are inadequate to manage the data produced by new generation DNA sequencers. To answer this problem, we developed PASS with the objective of improving execution time and sensitivity when compared with other available programs. PASS performs fast gapped and ungapped alignments of short DNA sequences onto a reference DNA, typically a genomic sequence. It is designed to handle a huge amount of reads such as those generated by Solexa, SOLiD or 454 technologies.
The CluePedia Cytoscape plugin is a search tool for new markers potentially associated to pathways. CluePedia calculates linear and non-linear statistical dependencies from experimental data. Genes, proteins and miRNAs can be connected based on in silico and/or experimental information and integrated into a ClueGO network of terms/pathways. Interrelations within each pathway can be investigated, and new potential associations may be revealed through gene/protein/miRNA enrichments. A pathway-like visualization can be created using the Cerebral plugin layout.
Piwi-interacting RNAs (piRNAs) are expressed in mammalian germline cells and have been identified as key players in germline development. These molecules, typically of length 25-33 nt, associate with Piwi proteins of the Argonaute family to form the Piwi-interacting RNA complex. These small regulatory RNAs have been implicated in spermatogenesis, repression of retrotransposon transposition in germline cells, epigenetic regulation and positive regulation of translation and mRNA stability.
Most computational methodologies for microRNA gene prediction utilize techniques based on sequence conservation and/or structural similarity. In this study we describe a new technique, which is applicable across several species, for predicting miRNA genes. This technique is based on machine learning, using the Naive Bayes classifier. It automatically generates a model from the training data, which consists of sequence and structure information of known miRNAs from a variety of species.
GeneSet2miRNA is the first web-based tool which is able to identify whether or not a gene list has a signature of miRNA-regulatory activity. As input, GeneSet2miRNA accepts a list of genes. As output, a list of miRNA-regulatory models is provided. A miRNA-regulatory model is a group of miRNAs (single, pair, triplet or quadruplet) that is predicted to regulate a significant subset of genes from the submitted list. GeneSet2miRNA provides a user friendly dialog-driven web page submission available for several model organisms.
To facilitate the designing process for vector-based siRNA and siRNA cassette, a tool set has been developed consisting of a siRNA target finder, a siRNA construct builder and a siRNA sequence scrambler. The siRNA target finder is used to identify candidate siRNA target sites. The program automates homology filtering, minimizes non-specific cross-reaction, filters target sites based on RNA duplex internal stability and siRNA sense/anti-sense strand secondary structure.
With the increasing use of post-genomics techniques to examine a wide variety of biological systems in laboratories throughout the world, scientists are often presented with lists of genes that they must make sense of. A consistently challenging problem is that of defining co-regulated genes within those gene lists. In recent years, microRNAs have emerged as a mechanism for regulating several cellular processes.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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