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https://pan.genomics.cn/ucdisk/s/VjuIRb&code=877833

Pipeline for construction and graphical visualization of annotated pangenome networks from microbial genomes. With the ability to extract and visualize gene contents and gene-gene physical adjacencies of a specific taxon from large-scale metagenomic data provides pangenome analysis to uncultured microbial taxa., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MetaPGN (RRID:SCR_016472) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/biocollections

Registry of bio-collections linked to genomes. Collection of curated dataset of metadata for culture collections, museums, herbaria and other natural history collections, including Darwin Core institution and collection codes, and URL formulae for mapping specimen ids to web pages at the collection site.

Proper citation: NCBI Biocollections (RRID:SCR_016459) Copy   

•   Source: SciCrunch Registry

https://github.com/WGS-TB/MentaLiST

Software for a MLST (multi-locus sequence typing) caller, based on a k-mer counting algorithm and written in the Julia language. Designed and implemented to handle large typing schemes.

Proper citation: MentaLiST (RRID:SCR_016469) Copy   

•   Source: SciCrunch Registry

https://github.com/lh3/fermi

Software assembler and analysis tool for whole-genome short-gun sequencing for Illumina reads. Provides tools for error correction, sequence-to-read alignment and comparison between read sets. Used for large genomes.

Proper citation: fermi (RRID:SCR_016652) Copy   

•   Source: SciCrunch Registry

http://ecogenomics.github.io/CheckM/

Software tool to assess the quality of microbial genomes recovered from isolates, single cells, and metagenomes by using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes.

Proper citation: CheckM (RRID:SCR_016646) Copy   

•   Source: SciCrunch Registry

https://triage.niaid.nih.gov

Platform to facilitate prediction, analysis, and hypothesis generation from genome wide perturbation studies like those designed with RNAi and CRISPR technologies.

Proper citation: TRIAGE (RRID:SCR_016609) Copy   

•   Source: SciCrunch Registry

http://www.dnastar.com/t-genvision.aspx

A genomic visualization application to support easy generation of publication quality graphics and maps. It produces high quality images of annotated genomes but it can also be customized to accentuate specific areas of interest, such as comparing gene functionality, illustrating gene expression levels, and visualizing the coverage in an assembled contig.

Proper citation: GenVision (RRID:SCR_001166) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/genomes

The EBI genomes pages give access to a large number of complete genomes including bacteria, archaea, viruses, phages, plasmids, viroids and eukaryotes. Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. WGS data for a growing number of organisms are being submitted to DDBJ/EMBL/GenBank. Genome entries have been listed in their appropriate category which may be browsed using the website navigation tool bar on the left. While organelles are all listed in a separate category, any from Eukaryota with chromosome entries are also listed in the Eukaryota page. Within each page, entries are grouped and sorted at the species level with links to the taxonomy page for that species separating each group. Within each species, entries whose source organism has been categorized further are grouped and numbered accordingly. Links are made to: * taxonomy * complete EMBL flatfile * CON files * lists of CON segments * Project * Proteomes pages * FASTA file of Proteins * list of Proteins

Proper citation: EBI Genomes (RRID:SCR_002426) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.udel.edu/Research/skategenomeproject

Core facility provides a model for collaborative approaches to use specialized resources and expertise in an integrated process. Core builds on the expertise and resources provided by the Bioinformatics Cores of the five northeastern states that form NECC. The Skate Genome Annotation Workshops and Jamborees offer training and opportunities for faculty and students to work with and annotate genome sequences. Workshops include lectures, tutorials and exercises annotating the genome of the little skate, Leucoraja erinacea.

Proper citation: University of Delaware Skate Genome Project (RRID:SCR_005300) Copy   

•   Source: SciCrunch Registry

http://noble.gs.washington.edu/proj/genomedata/

A format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. They have also developed utilities to load data into this format. Retrieving data from this format is more than 2900 times faster than a naive approach using wiggle files. A reference implementation in Python and C components is available here under the GNU General Public License. The software has only been tested on Linux and Mac systems.

Proper citation: Genomedata (RRID:SCR_004544) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/Fungi/

Fungal genomes available from the Sanger Institute. Data are accessible in a number of ways; for each organism there is a BLAST server, allowing search of the sequences. Sequences can also be down-loaded directly by FTP. In addition, for those organisms being sequenced using a cosmid approach, finished and annotated cosmids are submitted to EMBL and other public databases.

Proper citation: Fungi Sequencing Projects (RRID:SCR_008524) Copy   

•   Source: SciCrunch Registry

http://www.scripps.edu/florida/technologies/cbs/index.html

Core facility that provides access to genome-wide collections of cDNAs and siRNAs that can be used to interrogate cellular models of signal transduction pathways and phenotypes. Services include cell lines, hit-picking clones and various screening sets, and access to equipment.Provides instruments:Analyst Molecular Devices,Embla Molecular Devices, Envision Perkin Elmer, Platemate Matrix, Tecan M200, Wellmate Matrix.

Proper citation: Scripps Research Institute Florida Cell Based High Throughput Screening Core Facility (RRID:SCR_014877) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/annotation/genome/magnaporthe_comparative/MultiHome.html

The Magnaporthe comparative genomics database provides accesses to multiple fungal genomes from the Magnaporthaceae family to facilitate the comparative analysis. As part of the Broad Fungal Genome Initiative, the Magnaporthe comparative project includes the finished M. oryzae (formerly M. grisea) genome, as well as the draft assemblies of Gaeumannomyces graminis var. tritici and M. poae. It provides users the tools to BLAST search, browse genome regions (to retrieve DNA, find clones, and graphically view sequence regions), and provides gene indexes and genome statistics. We were funded to attempt 7x sequence coverage comprising paired end reads from plasmids, Fosmids and BACs. Our strategy involves Whole Genome Shotgun (WGS) sequencing, in which sequence from the entire genome is generated and reassembled. Our specific aims are as follows: 1. Generate and assemble sequence reads yielding 7X coverage of the Magnaporthe oryzae genome through whole genome shotgun sequencing. 2. Generate and incorporate BAC and Fosmid end sequences into the genome assembly to provide a paired-end of average every 2 kb. 3. Integrate the genome sequence with existing physical and genetic map information. 4. Perform automated annotation of the sequence assembly. 5. Distribute the sequence assembly and results of our annotation and analysis through a freely accessible, public web server and by deposition of the sequence assembly in GenBank.

Proper citation: Magnaporthe comparative Database (RRID:SCR_003079) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

•   Source: SciCrunch Registry

http://bibiserv.techfak.uni-bielefeld.de/dialign/

Tool for multiple sequence alignment using various sources of external information that is particularly useful to detect local homologies in sequences with low overall similarity. While standard alignment methods rely on comparing single residues and imposing gap penalties, DIALIGN constructs pairwise and multiple alignments by comparing entire segments of the sequences. No gap penalty is used. This approach can be used for both global and local alignment, but it is particularly successful in situations where sequences share only local homologies. Several versions of DIALIGN are available online at GOBICS, http://dialign.gobics.de/

Proper citation: DIALIGN (RRID:SCR_003041) Copy   

•   Source: SciCrunch Registry

http://resexomedb.bioinf-dz.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. An online catalog for whole-exome sequencing (WES) results including mutations and gene-disease associations identified by WES. It is browsable and searchable by mutation, gene, study or publication. In addition, it centralizes all publications, software, platforms related to exome / whole genome sequencing.

Proper citation: resExomeDB (RRID:SCR_003224) Copy   

•   Source: SciCrunch Registry

http://www.nematodes.org/

Nematode & Neglected Genomics (at) The Blaxter Lab is a nematode related portal including databases and services. Resources include genomic and transcriptomic databases for nematodes and other metazoan phyla and freely downloadable software tools for expressed sequence tag analysis, DNA barcode analysis and phylogenomics. Major categories include: * GenePool * 959 Nematode Genomes * Teaching * Research Projects * Bioinformatics Software Tools * Lab Personnel * Lab Wiki * Genomics Databases * NEMBASE4 * Tardigrada: Hypsibius dujardini * Earthworm: Lumbricus rubellus * MolluscDB * ArthropodDB * other Neglected Genomes

Proper citation: nematodes.org (RRID:SCR_003267) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/phenotree/

Web server to search for genes involved in given phenotypic difference between mammalian species. The mouse-referenced multiple alignment data files used to perform the forward genomics screen is also available. The webserver implements one strategy of a Forward Genomics approach aiming at matching phenotype to genotype. Forward genomics matches a given pattern of phenotypic differences between species to genomic differences using a genome-wide screen. In the implementation, the divergence of the coding region of genes in mammals is measured. Given an ancestral phenotypic trait that is lost in independent mammalian lineages, it is shown that searching for genes that are more diverged in all trait-loss species can discover genes that are involved in the given phenotype.

Proper citation: Phenotree (RRID:SCR_003591) Copy   

•   Source: SciCrunch Registry