Tools   Select Another Resource Report Type

https://www.unafold.org/

Software package for nucleic acid folding and hybridization prediction. It has capabilities to predict folding for single-stranded RNA or DNA through a combination of free energy minimization, partition function calculations and stochastic sampling. The program runs on Unix and Linux platforms as well as Mac OS X and Windows.

Proper citation: UNAFold (RRID:SCR_001360) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/aroma.light.html

Light-weight software package for normalization and visualization of microarray data using only basic R data types. Software can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Proper citation: aroma.light (RRID:SCR_001312) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.13/bioc/html/BeadDataPackR.html

Software that provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform.

Proper citation: BeadDataPackR (RRID:SCR_001310) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/OLIN.html

Software functions for normalization of two-color microarrays by optimised local regression and for detection of artifacts in microarray data.

Proper citation: OLIN (RRID:SCR_001304) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/qcmetrics.html

Software package that provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.

Proper citation: qcmetrics (RRID:SCR_001303) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages//2.12/bioc/html/dexus.html

Software package that identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. It works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. It does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power.

Proper citation: DEXUS (RRID:SCR_001309) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Enrichr/

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

Proper citation: Enrichr (RRID:SCR_001575) Copy   

•   Source: SciCrunch Registry

http://www.biostat.jhsph.edu/~hji/cisgenome/index.htm

Integrated software tool for tiling array, ChIP-seq, genome and cis-regulatory element analysis.

Proper citation: CisGenome (RRID:SCR_001558) Copy   

•   Source: SciCrunch Registry

http://intermine.org/

An open source data warehouse system built for the integration and analysis of complex biological data that enables the creation of biological databases accessed by sophisticated web query tools. Parsers are provided for integrating data from many common biological data sources and formats, and there is a framework for adding data. InterMine includes a user-friendly web interface that works "out of the box" and can be easily customized for specific needs, as well as a powerful, scriptable web-service API to allow programmatic access to data.

Proper citation: InterMine (RRID:SCR_001772) Copy   

•   Source: SciCrunch Registry

http://ilyinlab.org/friend/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Friend is a bioinformatics application designed for simultaneous analysis and visualization of multiple structures and sequences of proteins and/or DNA/RNA. The application provides basic functionalities such as: structure visualization with different rendering and coloring, sequence alignment, and simple phylogeny analysis, along with a number of extended features to perform more complex analyses of sequence structure relationships, including: structural alignment of proteins, investigation of specific interaction motifs, studies of protein-protein and protein-DNA interactions, and protein super-families. Friend is also useful for the functional annotation of proteins, protein modeling, and protein folding studies. Friend provides three levels of usage; 1) an extensive GUI for a scientist with no programming experience, 2) a command line interface for scripting for a scientist with some programming experience, and 3) the ability to extend Friend with user written libraries for an experienced programmer. The application is linked and communicates with local and remote sequence and structure databases.

Proper citation: An Integrated Multiple Structure Visualization and Multiple Sequence Alignment Application (RRID:SCR_001646) Copy   

•   Source: SciCrunch Registry

http://protein.bio.unipd.it/pasta2/

Online interface that utilizes an algorithm to predict the most aggregation-prone portions and the corresponding beta-strand inter-molecular pairing for a given input sequence. Users can paste the sequence into the interface and output the appropriate sequence.

Proper citation: Prediction of Amyloid Structure Aggregation (RRID:SCR_001768) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/unifiedWMWqPCR.html

Software package that implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.

Proper citation: unifiedWMWqPCR (RRID:SCR_001706) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.13/bioc/html/cqn.html

A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method.

Proper citation: CQN (RRID:SCR_001786) Copy   

•   Source: SciCrunch Registry

http://meme-suite.org/

Suite of motif-based sequence analysis tools to discover motifs using MEME, DREME (DNA only) or GLAM2 on groups of related DNA or protein sequences; search sequence databases with motifs using MAST, FIMO, MCAST or GLAM2SCAN; compare a motif to all motifs in a database of motifs; associate motifs with Gene Ontology terms via their putative target genes, and analyze motif enrichment using SpaMo or CentriMo. Source code, binaries and a web server are freely available for noncommercial use.

Proper citation: MEME Suite - Motif-based sequence analysis tools (RRID:SCR_001783) Copy   

•   Source: SciCrunch Registry

http://cmb.gis.a-star.edu.sg/ChIPSeq/paperCCAT.htm

THIS RESOURCE IS OUT OF SERVICE, documented on April 5, 2017, A software package for the analysis of ChIP-seq data with negative control., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CCAT (RRID:SCR_001843) Copy   

•   Source: SciCrunch Registry

https://urgi.versailles.inra.fr/Tools/S-Mart

Software toolbox that manages your RNA-Seq and ChIP-Seq data and also produces many different plots to visualize your data. It performs several tasks that are usually required during the analysis of mapped RNA-Seq and ChIP-Seq reads, including data selection and data visualization. It includes the selection (or the exclusion) of the data that overlaps with a reference set, clustering and comparative analysis. It also provides many ways to visualize data: size of the reads, density on the genome, distance with respect to a reference set, and the correlation of two data sets (with cloud plots). A computer science background is not required to run it through a graphical interface and it can be run on any personal computer, yielding results within an hour for most queries.

Proper citation: S-MART (RRID:SCR_001908) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/SamSPECTRAL.html

Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.

Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy   

•   Source: SciCrunch Registry

http://sharcgs.molgen.mpg.de/

Software package for a DNA assembly program designed for de novo assembly of 25-40mer input fragments and deep sequence coverage.

Proper citation: SHARCGS (RRID:SCR_002026) Copy   

•   Source: SciCrunch Registry

http://www.cs.sunysb.edu/~skiena/shorty/

Software for targeted de novo assembly of microreads with mate pair information and sequencing errors.

Proper citation: SHORTY (RRID:SCR_002048) Copy   

•   Source: SciCrunch Registry

http://www.aspgd.org/

Database of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus including information about genes and proteins of Aspergillus nidulans and Aspergillus fumigatus; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Sgenus species. Also available are Gene Ontology (GO) and community resources. Based on the Candida Genome Database, the Aspergillus Genome Database is a resource for genomic sequence data and gene and protein information for Aspergilli. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). Search options allow you to: *Search AspGD database using keywords. *Find chromosomal features that match specific properties or annotations. *Find AspGD web pages using keywords located on the page. *Find information on one gene from many databases. *Search for keywords related to a phenotype (e.g., conidiation), an allele (such as veA1), or an experimental condition (e.g., light). Analysis and Tools allow you to: *Find similarities between a sequence of interest and Aspergillus DNA or protein sequences. *Display and analyze an Aspergillus sequence (or other sequence) in many ways. *Navigate the chromosomes set. View nucleotide and protein sequence. *Find short DNA/protein sequence matches in Aspergillus. *Design sequencing and PCR primers for Aspergillus or other input sequences. *Display the restriction map for a Aspergillus or other input sequence. *Find similarities between a sequence of interest and fungal nucleotide or protein sequences. AspGD welcomes data submissions.

Proper citation: ASPGD (RRID:SCR_002047) Copy   

•   Source: SciCrunch Registry