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NAPP / Nucleic Acids Phylogenetic Profiling
A clustering method that efficiently identifies noncoding RNA (ncRNA) elements in a bacterial genome. This web server enables users to retrieve RNA-rich clusters from any genome in a list of 1000+ sequenced bacterial genomes. RNA-rich clusters can be viewed separately or, alternatively, all tiles from RNA-rich clusters can be contiged into larger elements and retrieved at once as a CSV or GFF file for use in a genome browser or comparison with other predictions/RNA-seq experiments.
RandA / ncRNA Read-and-Analyze
Performs comprehensive ncRNA profiling and differential expression analysis on deep sequencing generated data. RandA reveals the complexity of the ncRNA repertoire in a given cell population. It maps the reads against the newly formed database using a Burrows–Wheeler transform based alignment tool summing the number of reads that mapped uniquely to each of the annotated ncRNA sequence. The tool produces a table comprising of all the mapped ncRNAs in a given sample.
siRNA off-target discovery pipeline
Predicts siRNA off-target interactions and enables off-targeting potential comparisons between different siRNA designs. siRNA off-target discovery pipeline can predict the off-target transcripts and compute the off-targeting potential of a given siRNA in human. This pipeline can easily be tuned for any other organism by simply replacing the input data. This tool is able to calculate siRNA off-targeting potentials on an entire human genome/transcriptome in the time scale of hours thanks to the large-scale prediction capabilities of RIsearch.
MACPath / Model-based Analysis of Competing-endogenous Pathways
Identifies tumor-associated function of thousands ceRNA genes as a whole. MACPath groups ceRNA relationships by competing-endogenous pathways (cePathway). It permits users to calculate dysregulated cePathway relationships between cancer and normal cells. When applied to TCGA breast cancer data, this method also discovers thousands of lost and gained cePathway relationships, which provide biological insights into ceRNA regulations during tumorigenesis.
VIRsiRNApred / Viral siRNA efficacy prediction server
Predicts numerical efficacy of siRNAs targeting different genes of human viruses. VIRsiRNApred is a viral siRNA efficacy prediction algorithm that can classifies a siRNA as effective/non-effective. It offers an updated list of the experimentally validated siRNAs along with their numerical inhibition values reported in scientific literature. It also offers predicted siRNAs against important genes of HIV, Influenza, HCV, HBV and SARS.
GLASSgo / GLobal Automated sRNA Search go
New
Pinpoints small regulatory RNAs (sRNAs) homologs in complex genomic databases starting from a single sequence. GLASSgo is a web application that directly displays the predicted homologs ready for downstream analyses. The sensitivity of this tool can be customized and be enhanced without altering the specificity by re-running GLASSgo with a total true positive (TP) that possesses a low pairwise identity to the query. This software’s aim is to ameliorate the high-throughput functional classification of sRNAs.
Evolinc
Facilitates lincRNA discovery and characterizes aspects of lincRNA evolution. Evolinc is a two-module pipeline. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analyses workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species.
MIRNA-DISTILLER
Allows to compile miRNA data for given target genes from public databases. MIRNA-DISTILLER implements TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available for download.
siPRED / predicting siRNA
Utilizes two layers of support vector regression (SVR) to predict the efficacy of a small interfering RNA (siRNA). siPRED is based on various characteristic methods in the first layer and fusion mechanisms in the second layer. Characteristic methods were constructed by support vector regression from three categories of characteristics, namely sequence, features, and rules. In siPRED, the prediction of siRNA efficacy through integrated methods was better than through any method that utilized only a single method. siPRED is freely available on the web.
NOCORNAc / NOn-COding RNA characterization
Allows users to predict and describe ncRNA transcripts in bacteria. NOCORNAc is a standalone software that can perform strand-specific transcript predictions that can be applied to intergenic regions as well as cis-encoded asRNA transcripts. It accepts as input either the whole chromosome or the coordinates of putative ncRNA. Besides, the application includes additional features such as a way for searching known RNA motifs from the Rfam database.
PreDisRNA
Allows to detect multi-disease associated co-functional microRNA pairs. PreDisRNA focuses on the detection and prioritization of multi-disease associated co-functional miRNA pairs. This tool presents a method which is based on two ideas: (1) the first is the construction of a set of reliable negative samples of disease-miRNA association through miRNA expression comparison between control and diseased subjects, (2) and the second is the use of precomputed kernel matrix for support vector machines (SVM).
Lncident / LncRNAs identification
Identifies Long Non-Coding RNA Identification. Lncident presents an outstanding performance on microorganism, which offers a great application prospect to the analysis of microorganism. It provides an option for the users to train a classifier on users’ own datasets, which greatly facilitates the researches who are interesting on some poor-explored species. The tool outperforms Coding-Potential Calculator, Coding-Potential Assessment Tool, Coding-Noncoding Index, and PLEK.
nRC / non-coding RNA Classifier
Classifies non-coding RNA sequences. nRC is based on deep learning (DL) architecture. It is composed of three steps: the prediction of ncRNAs secondary structures, the extraction of frequent substructures as features and the classification of known ncRNA classes. The tool can obtain better scores when compared to other machine learning algorithms. It is able to produce high scores in terms of accuracy, sensitivity, specificity, precision, F-score and Matthews Correlation Coefficient (MCC).
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ncRNAdb / Noncoding RNAs database
Gathers information about sequences and functions of transcripts which performs regulatory roles in the cell without protein-coding capacity. ncRNAdb contains about 30 000 sequences from 99 organisms. The database includes both documented RNAs and expressed sequences of Non-Coding RNAs (ncRNAs) with unknown role in cells from several class of transcripts or taxonomic groups. Searches can be made by organism name, RNA symbol or GenBank accession number and a BLAST server to perform sequence similarity searches is provided.
GeoSeq
Allows users to find datasets of interest and query them using tiled-search algorithm. Geoseq aggregates and organizes libraries of short-read sequencing data. This application uses exact matches of sub-strings from a string to find inexact matches. Its user-interface provides a controlled vocabulary that assists to locate short-read libraries. The analysis service then allows mapping sequences against the short-read libraries for analysis of genes, miRNAs and other sequence types.
ICeE / Interface for Caenorhabditis elegans Experiments
Permits users to specify a series of pre-defined parameters to provide a complete description of an experiment. ICeE is an online repository simplifying the storage of disparate electronic data files. It is mainly designed to serve C. elegans experiments, but can be adapted to other subjects. It allows a summary document to be produced automatically and could clearly be modified if minimal reporting standards, such as those used for microarrays and proteomics.
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