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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   

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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   

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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   

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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   

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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   

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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   

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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://www.aetionomy.eu/

Consortium founded to establish mechanism-based taxonomies for Alzheimer's and Parkinson's disease and other neurodegenerative disorders (NDD), with the goal of facilitating development of more effective and targeted treatments. To do this, the consortium collects and analyzes data to: * Create new ways to combine underutilized data currently available in the literature, public databases, and from private companies * Determine how to dynamically organize and structure different types of knowledge about NDD * Determine how to apply this knowledge to construct new patient group classification * Identify correlations between disease features at molecular, tissue or organ-specific, and clinical levels * Identify sub-groups of patients based on the molecular cause of their disease, as opposed to the nature and location of their symptoms * Deliver data, tools, and recommendations for the biomedical community in the treatment of NDD A mechanism-based taxonomy is hoped to advance the: # Description and organization of the indication-specific data # Linking of data to disease models, based on causal and correlative relationships The expected outcome of AETIONOMY is a new NDD taxonomy system that distinguishes mixed pathologies, allowing for new features or classes to be added into the taxonomy, all with the goal of aiding drug and biomarker discovery.

Proper citation: AETIONOMY (RRID:SCR_000232) Copy   

•   Source: SciCrunch Registry
  

http://deweylab.biostat.wisc.edu/rsem/

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

Proper citation: RSEM (RRID:SCR_000262) Copy   

•   Source: SciCrunch Registry
  

http://sourceforge.net/projects/gemsim/

A software package for generating realistic simulated next-generation genome sequencing reads with quality score values. The software is written in Python with a command-line user interface.

Proper citation: GemSIM (RRID:SCR_000167) Copy   

•   Source: SciCrunch Registry
  

http://proteinprophet.sourceforge.net/

Software that automatically validates protein identifications made on the basis of peptides assigned to MS/MS spectra by database search programs such as SEQUEST.

Proper citation: ProteinProphet (RRID:SCR_000286) Copy   

•   Source: SciCrunch Registry
  

http://bioconductor.org/packages/release/bioc/html/DESeq.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Software for differential gene expression analysis based on the negative binomial distribution. It estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression.

Proper citation: DESeq (RRID:SCR_000154) Copy   

•   Source: SciCrunch Registry
  

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software for modeling count data using Dirichlet-multinomial and beta-binomial mixtures with applications to single-cell assays.

Proper citation: MIMOSA (RRID:SCR_000184) Copy   

•   Source: SciCrunch Registry
  

http://acgt.cs.tau.ac.il/modent/

A computational tool that reconstructs gene regulatory networks from high throughput experimental data.

Proper citation: MODENT - A Tool For Reconstructing Gene Regulatory Networks (RRID:SCR_000220) Copy   

•   Source: SciCrunch Registry
  

https://github.com/vahuynh/dynGENIE3

An algorithm for the inference of gene regulatory networks from expression data.

Proper citation: GENIE3 (RRID:SCR_000217) Copy   

•   Source: SciCrunch Registry