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https://github.com/r3fang/SnapTools

Software tool as module for working with snap files in Python. Snap files are designed for storing single nucleus ATAC-seq datasets.

Proper citation: SnapTools (RRID:SCR_018097) Copy   

•   Source: SciCrunch Registry

https://www.ebi.ac.uk/covid-19

EMBL-EBI portal to enable researchers to upload, access and analyse COVID-19 related reference data and specialist datasets submitted to EMBL-EBI and other major centers for biomedical data. Used to facilitate data sharing and analysis to accelerate coronavirus research. The aim of the COVID-19 Data Portal is to facilitate data sharing and analysis, and to accelerate coronavirus research. EMBL-EBI and partners have set up the COVID-19 Data Portal, which will bring together relevant datasets submitted to EMBL-EBI and other major centres for biomedical data. The aim is to facilitate data sharing and analysis, and to accelerate coronavirus research. The COVID-19 Data Portal will enable researchers to upload, access and analyse COVID-19 related reference data and specialist datasets. The COVID-19 Data Portal will be the primary entry point into the functions of a wider project, the European COVID-19 Data Platform.

Proper citation: EMBL-EBI COVID-19 Portal (RRID:SCR_018337) Copy   

•   Source: SciCrunch Registry

https://bigd.big.ac.cn/ncov/?lang=en

Bioinformation related to COVID-19. Site developed and maintained by China National Center for Bioinformation. Collection of sequences, genome variations, publication, clinical resource data.

Proper citation: 2019 Novel Coronavirus Resource (2019nCoVR) by China National Center for Bioinformation (RRID:SCR_018342) Copy   

•   Source: SciCrunch Registry

http://www.vmatch.de/

Software tool for efficiently solving large scale sequence matching tasks.

Proper citation: Vmatch (RRID:SCR_018968) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/MACH/index.html

A Markov Chain based software tool for haplotyping, genotype imputation and disease association analysis that can resolve long haplotypes or infer missing genotypes in samples of unrelated individuals.

Proper citation: MACH 1.0 (RRID:SCR_001759) Copy   

•   Source: SciCrunch Registry

http://www.aspergillus-genomes.org.uk/

A resource for viewing annotated genes arising from various Aspergillus sequencing and annotation projects, resulting from the merging of Central Aspergillus Data REpository (CADRE) and The Aspergillus Website, which took place in June 2008. The principal role of CADRE is to aid the Aspergillus research community by managing Aspergillus genome data and by providing visualization tools, ranging from relatively simple annotation displays to more complex data integration displays. In contrast, The Aspergillus Website provides a range of information to the medical community (i.e., clinicians, patients and scientists) regarding the genus Aspergillus and the diseases, such as Aspergillosis, that it can cause. CADRE has been implemented using the Ensembl v22 suite. This suite comprises: * a database schema, which has been devised for storing annotated eukaryotic genomes. The schema is implemented with the MySQL relational database management system. * several specialized programming modules for building interfaces (i.e., BioPerl and Ensembl API modules). * a series of programs (i.e., Perl CGI scripts using the API modules) for viewing genomic data within a web browser., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Aspergillus Genomes (RRID:SCR_001880) Copy   

•   Source: SciCrunch Registry

http://rgp.dna.affrc.go.jp/E/index.html

Rice Genome Research Program (RGP) is an integral part of the Japanese Ministry of Agriculture, Forestry and Fisheries (MAFF) Genome Research Project. RGP now aims to completely sequence the entire rice genome and subsequently to pursue integrated goals in functional genomics, genome informatics and applied genomics. It is jointly coordinated by the National Institute of Agrobiological Sciences (NIAS), a government research institute under MAFF and the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF), a semi-private research organization managed and supported by MAFF and a consortium of some twenty Japanese companies. The research is funded with yearly grants from MAFF and additional funds from the Japan Racing Association (JRA). It is now the leading member of the International Rice Genome Sequencing Project (IRGSP), a consortium of ten countries sharing the sequencing of the 12 rice chromosomes. The IRGSP adopts the clone-by-clone shotgun sequencing strategy so that each sequenced clone can be associated with a specific position on the genetic map and adheres to the policy of immediate release of the sequence data to the public domain. In December 2004, the IRGSP completed the sequencing of the rice genome. The high-quality and map-based sequence of the entire genome is now available in public databases.

Proper citation: Rice Genome Research Project (RRID:SCR_002268) Copy   

•   Source: SciCrunch Registry

http://www.structuralgenomics.org/

The Structural Genomics Project aims at determination of the 3D structure of all proteins. It also aims to reduce the cost and time required to determine three-dimensional protein structures. It supports selection, registration, and tracking of protein families and representative targets. This aim can be achieved in four steps : -Organize known protein sequences into families. -Select family representatives as targets. -Solve the 3D structure of targets by X-ray crystallography or NMR spectroscopy. -Build models for other proteins by homology to solved 3D structures. PSI has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm. The project has been organized into two separate phases. The first phase was dedicated to demonstrating the feasibility of high-throughput structure determination, solving unique protein structures, and preparing for a subsequent production phase. The second phase, PSI-2, has focused on implementing the high-throughput structure determination methods developed in PSI-1, as well as homology modeling and addressing bottlenecks like modeling membrane proteins. The first phase of the Protein Structure Initiative (PSI-1) saw the establishment of nine pilot centers focusing on structural genomics studies of a range of organisms, including Arabidopsis thaliana, Caenorhabditis elegans and Mycobacterium tuberculosis. During this five-year period over 1,100 protein structures were determined, over 700 of which were classified as unique due to their < 30% sequence similarity with other known protein structures. The primary goal of PSI-1 was to develop methods to streamline the structure determination process, resulted in an array of technical advances. Several methods developed during PSI-1 enhanced expression of recombinant proteins in systems like Escherichia coli, Pichia pastoris and insect cell lines. New streamlined approaches to cell cloning, expression and protein purification were also introduced, in which robotics and software platforms were integrated into the protein production pipeline to minimize required manpower, increase speed, and lower costs. The goal of the second phase of the Protein Structure Initiative (PSI-2) is to use methods introduced in PSI-1 to determine a large number of proteins and continue development in streamlining the structural genomics pipeline. Currently, the third phase of the PSI is being developed and will be called PSI: Biology. The consortia will propose work on substantial biological problems that can benefit from the determination of many protein structures Sponsors: PSI is funded by the U.S. National Institute of General Medical Sciences (NIGMS),

Proper citation: Protein Structure Initiative (RRID:SCR_002161) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/SNP/

Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.

Proper citation: dbSNP (RRID:SCR_002338) Copy   

•   Source: SciCrunch Registry

http://camera.calit2.net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016; however, the URL provides links to associated projects and data. A suite of data query, download, upload, analysis and sharing tools serving the needs of the microbial ecology research community, and other scientists using metagenomics data.

Proper citation: Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (RRID:SCR_002676) Copy   

•   Source: SciCrunch Registry

http://technelysium.com.au/?page_id=27

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31,2023. Software which is able to assemble data from 454 and Illumina next-generation sequencers, with up to 100,000 sequences if 2 Gb RAM is available.

Proper citation: ChromasPro (RRID:SCR_000229) Copy   

•   Source: SciCrunch Registry

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

Software for analysis and DNA sequence assembly of Sanger data. It also provides visualizations and analysis of next-gen projects assembled by SeqMan NGen.

Proper citation: Lasergene's SeqMan Pro (RRID:SCR_000283) Copy   

•   Source: SciCrunch Registry

http://www.isrec.isb-sib.ch/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Computational Cancer Genomics (CCG) group is dedicated to the development of analysis tools and databases relating molecular sequences and biological functions. Sponsors: This group is supported by the Swiss Institute of Bioinformatics (SIB).

Proper citation: Computational Cancer Genomics Group (RRID:SCR_000772) Copy   

•   Source: SciCrunch Registry

http://www.genet.sickkids.on.ca/cftr/

Collection of mutations in CFTR gene for international cystic fibrosis genetics research community. Provides up to date information about individual mutations in CFTR gene. All known CFTR mutations and sequence variants have been converted to standard nomenclature recommended by Human Genome Variation Society. On line process for submission of new mutations has been added.While they continue to ensure quality of data, they urge international community to give them feedback and suggestions. Clinical information in this database relates only to details of discovery of specific mutations. As part of 2010 upgrade, CFTR1 joined new project called CFTR2 - Clinical and Functional TRanslation of CFTR. Links to CFTR2 for many mutations in CFTR1 will provide up-to-date summaries of genotype-phenotype information from patient registries around the world.

Proper citation: Cystic Fibrosis Mutation Database (RRID:SCR_000685) Copy   

•   Source: SciCrunch Registry

http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

•   Source: SciCrunch Registry

http://sfld.rbvi.ucsf.edu/

A database of hierarchical classification of enzymes that relates specific sequence-structure features to specific chemical capabilities. The SFLD classifies evolutionarily related enzymes according to shared chemical functions and maps these shared functions to conserved active site features. The classification is hierarchical, where broader levels encompass more distantly related proteins with fewer shared features. It thus serves as the analysis and archive site for superfamilies targeted by the Enzyme Function Initiative, and is developed by the Babbitt Laboratory in collaboration with the UCSF Resource for Biocomputing, Visualization, and Informatics. The resource also provides a collection of tools and data for investigating sequence-structure-function relationships and hypothesizing function.

Proper citation: Structure-function linkage database (RRID:SCR_001375) Copy   

•   Source: SciCrunch Registry

https://www.ddbj.nig.ac.jp/dra/index-e.html

Archive database for output data generated by next-generation sequencing machines including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, and others. DRA is a member of the International Nucleotide Sequence Database Collaboration (INSDC) and archiving the data in a close collaboration with NCBI Sequence Read Archive (SRA) and EBI Sequence Read Archive (ERA). Please submit the trace data from conventional capillary sequencers to DDBJ Trace Archive., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DDBJ Sequence Read Archive (RRID:SCR_001370) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/services/NetNGlyc-1.0/

Server that predicts N-Glycosylation sites in human proteins using artificial neural networks that examine the sequence context of Asn-Xaa-Ser/Thr sequons. NetNGlyc 1.0 is also available as a stand-alone software package, with the same functionality as the service above. Ready-to-ship packages exist for the most common UNIX platforms.

Proper citation: NetNGlyc (RRID:SCR_001570) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/services/YinOYang-1.2/

Server that produces neural network predictions for O-beta-GlcNAc attachment sites in eukaryotic protein sequences. This server can also use NetPhos, to mark possible phosphorylated sites and hence identify Yin-Yang sites. YinOYang 1.2 is available as a stand-alone software package, with the same functionality. Ready-to-ship packages exist for the most common UNIX platforms.

Proper citation: YinOYang (RRID:SCR_001605) Copy   

•   Source: SciCrunch Registry