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https://github.com/BackofenLab/GraphClust-2

Software tool for scalable clustering of RNAs based on sequence and secondary structures similarities. Implemented within Galaxy framework. Used for studying RNA function.

Proper citation: GraphClust2 (RRID:SCR_017286) Copy   

•   Source: SciCrunch Registry

http://heimanlab.com/cut2.html

Software tool to find restriction endonucleases. Helps restriction map nucleotide sequences. Tool with customizable interface, platform independent accessibility, interfaces to NCBI's GenBank, DNA sequence database, and NEB's REBase, and restriction enzyme database. In addition to restriction site mapping, Webcutter 2 also performs degenerate digests, including option of finding restriction sites that can be introduced into sequence by silent mutagenesis.

Proper citation: Webcutter (RRID:SCR_017638) Copy   

•   Source: SciCrunch Registry

http://refgenie.databio.org

Software tool to organize, retrieve, and share genome analysis resources. Reference genome assembly asset manager. In addition to genome indexes, can manage any files related to reference genomes, including sequences and annotation files. Includes command line interface and server application that provides RESTful API, so it is useful for both tool development and analysis.

Proper citation: refgenie (RRID:SCR_017574) Copy   

•   Source: SciCrunch Registry

http://crispr.dbcls.jp/

Software for designing CRISPR/Cas guide RNA with reduced off target sites. Used for rational design of CRISPR/Cas target. Web server for selecting rational CRISPR/Cas targets from input sequence. Server currently incorporates genomic sequences of human, mouse, rat, marmoset, pig, chicken, frog, zebrafish, Ciona, fruit fly, silkworm, Caenorhabditis elegans, Arabidopsis, rice, Sorghum and budding yeast.

Proper citation: CRISPRdirect (RRID:SCR_018186) Copy   

•   Source: SciCrunch Registry

http://www.bx.psu.edu/miller_lab/dist/README.lastz-1.02.00/README.lastz-1.02.00a.html#install

Software package for sequence alignment. Pairwise aligner for aligning DNA sequences. Designed to handle sequences size of human chromosomes and from different species. Useful for sequences produced by NGS sequencing technologies.

Proper citation: LASTZ (RRID:SCR_018556) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/services/BepiPred/index.php

Sequential B-Cell Epitope Predictor. Web server predicts B-cell epitopes from protein sequence. Sequence-based B-cell epitope prediction using conformational epitopes. Sequences of protein of interest should be in fasta format. BepiPred 2.0 is available as stand alone software package, with same functionality as web service., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BepiPred-2.0 (RRID:SCR_018499) Copy   

•   Source: SciCrunch Registry

http://faculty.ucr.edu/~mmaduro/random.htm

Web application to generate random DNA sequences.

Proper citation: Random DNA Sequence Generator (RRID:SCR_018768) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.brown.edu/projects/gasv/

Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.

Proper citation: GASVPro (RRID:SCR_005259) Copy   

•   Source: SciCrunch Registry

http://www.pazar.info/

Database that unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein-DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ''boutiques'' within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PAZAR (RRID:SCR_005410) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/cgi-bin/tigrfams/index.cgi

Consists curated multiple sequence alignments, Hidden Markov Models (HMMs) for protein sequence classification, and associated information designed to support automated annotation of (mostly prokaryotic) proteins. Starting with release 10.0, TIGRFAMs models use HMMER3, which provides excellent search speed as well as exquisite search sensitivity. See the "TIGRFAMs Complete Listing" page to review the accession, protein name, model type, and EC number (if assigned) of all models. TIGRFAMs is a member database in InterPro. The HMM libraries and supporting files are available to download and use for free from our FTP site.

Proper citation: TIGRFAMS (RRID:SCR_005493) Copy   

•   Source: SciCrunch Registry

http://www.genexplain.com/

An online toolbox and workflow management system for a broad range of bioinformatic and systems biology applications. The individual modules, or Bricks, are unified under a standardized interface, with a consistent look-and-feel and can flexibly be put together to comprehensive workflows. The workflow management is intuitively handled through a simple drag-and-drop system. With this system, you can edit the predefined workflows or compose your own workflows from scratch. Your own Bricks can easily be added as scripts or plug-ins and can be used in combination with pre-existing analyses. GeneXplain GmbH provides a number of state-of-the-art bricks; some of them can be obtained free of charge, while others require licensing for small fee in order to guarantee active maintenance and dynamic adaptation to the rapidly developing know-how in this field.

Proper citation: geneXplain (RRID:SCR_005573) Copy   

•   Source: SciCrunch Registry

http://www.yandell-lab.org/software/mwas.html

The MAKER Web Annotation Service (MWAS) is an easily configurable web-accessible genome annotation pipeline. It''''s purpose is to allow research groups with small to intermediate amounts of eukaryotic and prokaryotic genome sequence (i.e. BAC clones, small whole genomes, preliminary sequencing data, etc.) to independently annotate and analyze their data and produce output that can be loaded into a genome database. MWAS is build on the stand alone genome annotation pipeline MAKER, and users who wish to annotate larger datasets and whole genomes are free to download MAKER for use on their own systems. MWAS identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MWAS can also automatically train popular gene prediction algorithms for use on new genomes for which pre-existing information is limited. MAKER is a member of the Generic Model Organism Database (GMOD) project and output produced by this site can be directly used with other GMOD tools. Annotations can be directly viewed online by the user via GBrowse, JBrowse, and Apollo, or they can be downloaded for local analysis and integration into a genome database. MWAS also supplies summary statistics on sequence features via the Sequence Ontology tool SOBA. MWAS should prove especially useful for emerging model organism genome projects with minimal bioinformatics expertise and computer resources, since a user can produce final genome annotations without having to install and configure any software locally.

Proper citation: MAKER Web Annotation Service (RRID:SCR_005318) Copy   

•   Source: SciCrunch Registry

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://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) 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

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) 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

http://www.nematodes.org/nembase4/

NEMBASE is a comprehensive Nematode Transcriptome Database including 63 nematode species, over 600,000 ESTs and over 250,000 proteins. Nematode parasites are of major importance in human health and agriculture, and free-living species deliver essential ecosystem services. The genomics revolution has resulted in the production of many datasets of expressed sequence tags (ESTs) from a phylogenetically wide range of nematode species, but these are not easily compared. NEMBASE4 presents a single portal into extensively functionally annotated, EST-derived transcriptomes from over 60 species of nematodes, including plant and animal parasites and free-living taxa. Using the PartiGene suite of tools, we have assembled the publicly available ESTs for each species into a high-quality set of putative transcripts. These transcripts have been translated to produce a protein sequence resource and each is annotated with functional information derived from comparison with well-studied nematode species such as Caenorhabditis elegans and other non-nematode resources. By cross-comparing the sequences within NEMBASE4, we have also generated a protein family assignment for each translation. The data are presented in an openly accessible, interactive database. An example of the utility of NEMBASE4 is that it can examine the uniqueness of the transcriptomes of major clades of parasitic nematodes, identifying lineage-restricted genes that may underpin particular parasitic phenotypes, possible viral pathogens of nematodes, and nematode-unique protein families that may be developed as drug targets.

Proper citation: NEMBASE (RRID:SCR_006070) Copy   

•   Source: SciCrunch Registry

http://hfv.lanl.gov/content/index

The Hemorrhagic Fever Viruses (HFV) sequence database collects and stores sequence data and provides a user-friendly search interface and a large number of sequence analysis tools, following the model of the highly regarded and widely used Los Alamos HIV database. The database uses an algorithm that aligns each sequence to a species-wide reference sequence. The NCBI RefSeq database is used for this; if a reference sequence is not available, a Blast search finds the best candidate. Using this method, sequences in each genus can be retrieved pre-aligned. Hemorrhagic fever viruses (HFVs) are a diverse set of over 80 viral species, found in 10 different genera comprising five different families: arena-, bunya-, flavi-, filo- and togaviridae. All these viruses are highly variable and evolve rapidly, making them elusive targets for the immune system and for vaccine and drug design. About 55,000 HFV sequences exist in the public domain today. A central website that provides annotated sequences and analysis tools will be helpful to HFV researchers worldwide.

Proper citation: HFV Database (RRID:SCR_006017) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/DAM-Bio/

An integrated environment designed to support protein sequence and structure analysis on the web.

Proper citation: DAM-Bio (RRID:SCR_006226) Copy   

•   Source: SciCrunch Registry