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http://bowtie-bio.sourceforge.net/index.shtml

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

Proper citation: Bowtie (RRID:SCR_005476) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/p/treq/home/Home/

A software read mapper for high-throughput DNA sequencing reads, in particular one to several hundred nucleotides in length, and for large edit distance between sequencing read and match in the reference genome. It can cope particularly well with indels for single-best hit recall of 200nt reads simulated from the human reference genome. TreQ performs best at a running time comparable to BWA at large edit distance settings.

Proper citation: TreQ (RRID:SCR_005505) Copy   

•   Source: SciCrunch Registry

http://microbesonline.org/

MicrobesOnline is designed specifically to facilitate comparative studies on prokaryotic genomes. It is an entry point for operon, regulons, cis-regulatory and network predictions based on comparative analysis of genomes. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

Proper citation: MicrobesOnline (RRID:SCR_005507) Copy   

•   Source: SciCrunch Registry

http://diprogb.fli-leibniz.de/

Genome browser that encodes the genome sequence by physico-chemical dinucleotide properties such as stacking energy, melting temperature or twist angle. Analyses can be performed for the + and ?, as well as for the double strand.

Proper citation: DiProGB (RRID:SCR_005651) Copy   

•   Source: SciCrunch Registry

https://cgwb.nci.nih.gov/goldenPath/bamview/documentation/index.html

A variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. Bambino may be launched online via Java Web Start or downloaded and run locally.

Proper citation: Bambino (RRID:SCR_005649) Copy   

•   Source: SciCrunch Registry

http://pellegrini.mcdb.ucla.edu/BS_Seeker/BS_Seeker.html

Software which performs accurate and fast mapping of bisulfite-treated short reads. Supplementary information and examples are provided on the site.

Proper citation: BS Seeker (RRID:SCR_005641) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/DMRforPairs.html

Software for identifying differentially methylated regions between unique samples using array based methylation profiles. It allows researchers to compare n greater than or equal to 2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishesit from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance.

Proper citation: DMRforPairs (RRID:SCR_005702) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.babraham.ac.uk/projects/bismark/

Software tool to map bisulfite converted sequence reads and determine cytosine methylation states. Flexible aligner and methylation caller for Bisulfite-Seq applications. Used to map bisulfite treated sequencing reads to genome of interest and perform methylation calls in single step.

Proper citation: Bismark (RRID:SCR_005604) Copy   

•   Source: SciCrunch Registry

http://tmaj.pathology.jhmi.edu/

Open-source software to support information and images related to tissue micro-arrays. It contains support for multiple organ systems, multiple users, image analysis, and is designed to be compliant with HIPPA regulations. Patients, specimens, blocks, slides, cores, images, and scores can all be stored and viewed. Features include advanced security, custom dynamic fields, and an image analysis program.

Proper citation: TMAJ (RRID:SCR_005601) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

•   Source: SciCrunch Registry

http://maq.sourceforge.net/maqview.shtml

A graphical read alignment viewer specifically designed for the Maq alignment file and allows you to see the mismatches, base qualities and mapping qualities. It is highly efficient in speed, memory and disk usage. Maqview is based on OpenGL and is known to work on both Mac OS X and Linux. Porting to Windows is in principle easy.

Proper citation: Maqview (RRID:SCR_005632) Copy   

•   Source: SciCrunch Registry

http://staden.sourceforge.net/

A fully developed set of DNA sequence assembly (Gap4 and Gap5), editing and analysis tools (Spin) for Unix, Linux, MacOSX and MS Windows.

Proper citation: Staden Package (RRID:SCR_005629) Copy   

•   Source: SciCrunch Registry

http://corneliu.henegar.info/FunCluster.htm

FunCluster is a genomic data analysis algorithm which performs functional analysis of gene expression data obtained from cDNA microarray experiments. Besides automated functional annotation of gene expression data, FunCluster functional analysis aims to detect co-regulated biological processes through a specially designed clustering procedure involving biological annotations and gene expression data. FunCluster''''s functional analysis relies on Gene Ontology and KEGG annotations and is currently available for three organisms: Homo Sapiens, Mus Musculus and Saccharomyces Cerevisiae. FunCluster is provided as a standalone R package, which can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix). Download it from the FunCluster website, or from the worldwide mirrors of CRAN. FunCluster is provided freely under the GNU General Public License 2.0. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FunCluster (RRID:SCR_005774) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

•   Source: SciCrunch Registry

http://toppgene.cchmc.org/

ToppGene Suite is a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network. ToppGene Suite is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis.

Proper citation: ToppGene Suite (RRID:SCR_005726) Copy   

•   Source: SciCrunch Registry

http://crdd.osdd.net/raghava/ccpdb/

ccPDB (Compilation and Creation of datasets from PDB) is designed to provide service to scientific community working in the field of function or structure annoation of proteins. This database of datasets is based on Protein Data Bank (PDB), where all datasets were derived from PDB. ccPDB have four modules; i) compilation of datasets, ii) creation of datasets, iii) web services and iv) Important links. * Compilation of Datasets: Datasets at ccPDB can be classified in two categories, i) datasets collected from literature and ii) datasets compiled from PDB. We are in process of collecting PDB datasetsfrom literature and maintaining at ccPDB. We are also requesting community to suggest datasets. In addition, we generate datasets from PDB, these datasets were generated using commonly used standard protocols like non-redundant chains, structures solved at high resolution. * Creation of datasets: This module developed for creating customized datasets where user can create a dataset using his/her conditions from PDB. This module will be useful for those users who wish to create a new dataset as per ones requirement. This module have six steps, which are described in help page. * Web Services: We integrated following web services in ccPDB; i) Analyze of PDB ID service allows user to submit their PDB on around 40 servers from single point, ii) BLAST search allows user to perform BLAST search of their protein against PDB, iii) Structural information service is designed for annotating a protein structure from PDB ID, iv) Search in PDB facilitate user in searching structures in PDB, v)Generate patterns service facility to generate different types of patterns required for machine learning techniques and vi) Download useful information allows user to download various types of information for a given set of proteins (PDB IDs). * Important Links: One of major objectives of this web site is to provide links to web servers related to functional annotation of proteins. In first phase we have collected and compiled these links in different categories. In future attempt will be made to collect as many links as possible.

Proper citation: ccPDB - Compilation and Creation of datasets from PDB (RRID:SCR_005870) Copy   

•   Source: SciCrunch Registry

http://utrdb.ba.itb.cnr.it/

UTRdb/UTRsite is a portal to other databases, including Nucleotide Sequence Databases, Protein Sequence Databases, other Sequence databanks, Untranslated Nucleotide Sequence Databases, Mitochondrial Databases, Mutation Databases, and others. The site also allows users to start long-term permanent projects or just to do quick searches, depending on the user''s needs.

Proper citation: UTRdb/UTRsite (RRID:SCR_005868) Copy   

•   Source: SciCrunch Registry

http://bio-bigdata.hrbmu.edu.cn/diseasemeth/

Human disease methylation database. DiseaseMeth version 2.0 is focused on aberrant methylomes of human diseases. Used for understanding of DNA methylation driven human diseases.

Proper citation: DiseaseMeth (RRID:SCR_005942) Copy   

•   Source: SciCrunch Registry

http://distild.jensenlab.org/

The DistiLD database aims to increase the usage of existing genome-wide association studies (GWAS) results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database performs three important tasks: # published GWAS are collected from several sources and linked to standardized, international disease codes ICD10 codes) # data from the International HapMap Project are analyzed to define linkage disequilibrium (LD) blocks onto which SNPs and genes are mapped # the web interface makes it easy to query and visualize disease-associated SNPs and genes within LD blocks. Users can query the database by diseases, SNPs or genes. No matter which of the three query modes was used, an intermediate page will be shown listing all the studies that matched the search with a link to the corresponding publication. The user can select either all studies related to a certain disease or one specific study for which to view the related LD blocks. The DistiLD resource integrates information on: * Associations between Single Nucleotide Polymorphisms (SNPs) and diseases from genome-wide association studies (GWAS) * Links between SNPs and genes based on linkage disequilibrium (LD) data from HapMap For convenience, we provide the complete datasets as two (zipped) tab-delimited files. The first file contains GWAS results mapped to LD blocks. The second file contains all SNPs and genes assigned to each LD block.

Proper citation: DistiLD - Diseases and Traits in LD (RRID:SCR_005943) Copy   

•   Source: SciCrunch Registry

http://newt-omics.mpi-bn.mpg.de/index.php

Newt-omics is a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centered database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ~50,000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13,810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise. The newt Notopthalmus viridescens is the master of regeneration. This organism is known for more than 200 years for its exceptional regenerative capabilities. Newts can completely replace lost appendages like limb and tail, lens and retina and parts of the central nervous system. Moreover, after cardiac injury newts can rebuild the functional myocardium with no scar formation. To date only very limited information from public databases is available. Newt-Omics aims to provide a comprehensive platform of expressed genes during tissue regeneration, including extensive annotations, expression data and experimentally verified peptide sequences with yet no homology to other publicly available gene sequences. The goal is to obtain a detailed understanding of the molecular processes underlying tissue regeneration in the newt, that may lead to the development of approaches, efficiently stimulating regenerative pathways in mammalians. * Number of contigs: 26594 * Number of est in contigs: 48537 * Number of transcripts with verified peptide: 5291 * Number of peptides: 15169

Proper citation: Newtomics (RRID:SCR_006073) Copy   

•   Source: SciCrunch Registry