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http://baderlab.org/Software/EnrichmentMap

Source code of a Cytoscape plugin for functional enrichment visualization. It organizes gene-sets, such as pathways and Gene Ontology terms, into a network to reveal which mutually overlapping gene-sets cluster together.

Proper citation: EnrichmentMap (RRID:SCR_016052) Copy   

•   Source: SciCrunch Registry

http://www.xavierdidelot.xtreemhost.com/clonalframe.htm

Software package for the inference of bacterial microevolution using multilocus sequence data. It is used to identify the clonal relationships between the members of a sample, while also estimating the chromosomal position of homologous recombination events that have disrupted the clonal inheritance.

Proper citation: Clonalframe (RRID:SCR_016060) Copy   

•   Source: SciCrunch Registry

http://www.omicsbean.cn

Software tool for multi-omics data analysis that can perform complex and personalized analysis. Network regulation and molecular mechanism models can be customized according to the requirements of the users.

Proper citation: OmicsBean (RRID:SCR_016322) Copy   

•   Source: SciCrunch Registry

http://zzlab.net/blink/index.html

Software for next level of genome wide association studies with both individuals and markers in millions. The method releases the requirement that causative genes are evenly distributed on genome and consequently boosts statistical power.

Proper citation: BLINK (RRID:SCR_016288) Copy   

•   Source: SciCrunch Registry

https://github.com/Sung-Huan/ANNOgesic

Software tool for bacterial/archaeal RNA-Seq based genome annotations. Used for integrating, detecting, predicting, and grouping RNA-Seq data.

Proper citation: ANNOgesic (RRID:SCR_016326) Copy   

•   Source: SciCrunch Registry

https://github.com/MRCIEU/PhenoSpD

Software toolkit for phenotypic correlation estimation and multiple testing correction (Spectral Decomposition, SpD) for human phenome using genome-wide association study (GWAS) summary statistics. It is a command line R based tool.

Proper citation: PhenoSpD (RRID:SCR_016359) Copy   

•   Source: SciCrunch Registry

https://omabrowser.org/oma/

Web based database interface for orthology prediction for the inference of orthologs among complete genomes. Used to relate genes across many species., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMA Orthology database (RRID:SCR_016425) Copy   

•   Source: SciCrunch Registry

https://cm.jefferson.edu/rna22/

Software tool as a pattern based algorithm for detecting microRNA binding sites and their corresponding microRNA and mRNA complexes. Allows interactive exploration and visualization of miRNA target predictions. Permits link-out to external expression repositories and databases.

Proper citation: RNA22 (RRID:SCR_016507) Copy   

•   Source: SciCrunch Registry

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

http://www.biodas.org

The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.

Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy   

•   Source: SciCrunch Registry

http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

http://jjwanglab.org/snvrap

The web portal provides comprehensive local database of human genome variants with a user-friendly web page that provides a one-stop annotating and funtonal prediction service which is both convenient and up-to-date. A query can be accepted as either a dbSNP Id or a chromosomal location and our system will instantly provide all the annotation information in an interactive LD panel. The system can also simultaneously prioritize this variant based on additive effect mode by corresponding annotation information and evaluate the variant effect that is then displayed in a prioritization tree. Furthermore, cohort sequencing continuously produces lots of un-annotated variants such as rare variants or de novo variants, and our system can even fit this data by accepting genomic coordinates (hg19) to offer maximal annotations. Main Functions Over 40 up-to-date annotation items for human single nucleotide variations; Functional prediction for different types of variants; Dynamic LD panel for both HapMap and 1000 Genomes Project populations; Prioritization score and tree viewer based on variant functional model.

Proper citation: SNVrap (RRID:SCR_010512) Copy   

•   Source: SciCrunch Registry

http://fnih.org/work/past-programs/genetic-association-information-network-gain

The Genetic Association Information Network (GAIN) supports a series of Genome-Wide Association Studies (GWAS) designed to identify specific points of DNA variation associated with the occurrence of a particular common disease. Initially focusing on six major common diseases, GAIN focused on combining the results with clinical data to create a significant new resource for genetic researchers.

Proper citation: Genetic Association Information Network (GAIN) (RRID:SCR_013703) Copy   

•   Source: SciCrunch Registry

http://www.vicbioinformatics.com/software.prokka.shtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software tool for the rapid annotation of prokaryotic genomes. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Prokka (RRID:SCR_014732) Copy   

•   Source: SciCrunch Registry

http://gmdd.shgmo.org/Computational-Biology/GRS/

A compression tool for efficient storage of Genome Re-Sequencing data. GRS processes genome sequence data without use of reference SNPs and other variants. It can also automatically rebuild the individual genome sequence data using the reference genome sequence.

Proper citation: GRS (RRID:SCR_001008) Copy   

•   Source: SciCrunch Registry