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http://www.ontobee.org/

Web-based linked data server and browser specifically designed for ontology terms, it supports ontology visualization, query, and development. Ontobee provides a web interface for displaying the details and hierarchy of a specific ontology term. Meanwhile, Ontobee provides a RDF source code for the particular web page, which supports remote query of the ontology term and the Semantic Web. Ontobee provides an efficient and publicly available method to promote ontology sharing, interoperability, and data integration.

Proper citation: Ontobee (RRID:SCR_006321) Copy   

•   Source: SciCrunch Registry

http://www.genome.wisc.edu/

The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments.

Proper citation: E. coli Genome project (RRID:SCR_008139) Copy   

•   Source: SciCrunch Registry

http://www.genome.ou.edu/cneo.html

Cryptococcus neoformans is an encapsulated yeast that infects the human host via the respiratory tract where it usually causes an inapparent infection. In the susceptible host, it may disseminate, typically producing a chronic and life-threatening meningitis. The Cryptococcus neoformans serotypes A and D are responsible for the overwhelming majority of pulmonary infections in AIDS patients. Cryptococcus neoformans strain H99 Latest Data Release - May 19, 2004 To date, we have isolated ca. 3750 cDNA clones from Cryptococcus neoformans strain H99 in collaboration with Drs. Juneann Murphy and Dave Dyer at the University of Oklahoma Health Sciences Center''s Department of Microbiology and Immunology in Oklahoma City and Kent Buchanan at the Tulane University Medical School, New Orleans, LA. The Cryptococcus neoformans strain H99 EST''s have been generated by Doris Kupfer, Heather Bell, Sunkyoung So, Yuong Tang, and Jennifer Lewis at the University of Oklahoma''s Advanced Center for Genome Technology, in the Department of Chemistry and Biochemistry. We now have end sequenced all available templates (ca. 7500 reactions) from both ends of the directionally cloned inserts after excision into pBlueScript SK-. . All of our data is available from our ftp site, and we now have added the ability to perform blast searches on this data. A keyword search of a blastx search of GenBank with this data also is available but we have not yet linked this to a unigene database as the number of EST''s sequenced doesn''t warrent this yet.

Proper citation: Cryptococcus Neoformans cDNA Sequencing (RRID:SCR_008462) Copy   

•   Source: SciCrunch Registry

http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

•   Source: SciCrunch Registry

http://www.datamonkey.org/

Web-based suite of phylogenetic analysis tools for use in evolutionary biology. Web application for comparative analysis of sequence alignments using statistical models. Used for analyzing evolutionary signatures in sequence data. Datamonkey 2.0 provides curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application.

Proper citation: Datamonkey (RRID:SCR_010278) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IMMDIS

Ontology generated as part of the Bioinformatics Integration Support Contract (BISC) that is based on the National Library of Medicine (NLM) Medical Subject Headings; National Cancer Institute Thesaurus; International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM); ICD-10; and other open source public databases. Specific information may be available about a class, including Preferred_Name, DEFINITION, Synonym, etc.

Proper citation: Immune Disorder Ontology (RRID:SCR_010344) Copy   

•   Source: SciCrunch Registry

http://hiv-web.lanl.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023. HIV Sequence Database is a database of annotated HIV sequences, plus a variety of tools and information for researchers studying HIV and SIV. The main aim of this website is to provide easy access to our sequence database, alignments, and the tools and interfaces we have produced. The HIV Sequence Database focuses on five primary goals: * Collecting HIV and SIV sequence data (all sequences since 1987) * Curating and annotating this data, and making it available to the scientific community * Computer analysis of HIV and related sequences * Production of software for the analysis of (sequence) data * The data and analyses on this site and published in a yearly printed publication, the HIV sequence Compendium, which is available free of charge.

Proper citation: HIV Sequence Database (RRID:SCR_002906) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/index

Contains comprehensive data on HIV genetic sequences and immunological epitopes. This collection of databases contains tools to visualize and analyze HIV-related data.

Proper citation: HIV Databases (RRID:SCR_000614) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ap_seg_2013_nih/

A MATLAB GUI for segmenting and quantifying PET images with multi-focal and diffuse uptakes. It imports a PET image and allows the user to draw region of interests (ROIs) in 2D or 3D to roughly separate the object of interest from the background. The areas are then segmented using a PET image segmentation method based on Affinity Propagation clustering to cluster the image intensities into meaningful groups. For quantification, the Standardized Uptake Value measurements of the binary or the user defined ROI are SUVmax, SUVmean, and Volume (mm^3) and can be exported into an excel sheet.

Proper citation: NIH-CIDI Segmentation of PET Images based on Affinity Propagation Clustering (RRID:SCR_014151) Copy   

•   Source: SciCrunch Registry

https://www.immport.org/home

Data sharing repository of clinical trials, associated mechanistic studies, and other basic and applied immunology research programs. Platform to store, analyze, and exchange datasets for immune mediated diseases. Data supplied by NIAID/DAIT funded investigators and genomic, proteomic, and other data relevant to research of these programs extracted from public databases. Provides data analysis tools and immunology focused ontology to advance research in basic and clinical immunology.

Proper citation: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804) Copy   

•   Source: SciCrunch Registry

https://www.archrproject.com/

Software R package for processing and analyzing single-cell ATAC-seq data. Used for integrative single cell chromatin accessibility analysis.Provides intuitive, user focused interface for complex single cell analysis, including doublet removal, single cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing.

Proper citation: ArchR (RRID:SCR_020982) Copy   

•   Source: SciCrunch Registry

https://mibig.secondarymetabolites.org/

MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.

Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/apidots/

Note: ApiDots is currently unavailable. For data on apicomplexan EST assemblies, please see EuPathDB ApiDots is a database integrating mRNA/EST sequences from numerous Apicomplexan parasites. ESTs and mRNAs were clustered and further assembled to generate consensus sequences. These consensus sequences were then subjected to database searches against protein sequences and protein domain sequences. The underlying relational structure of this database allows researchers to analyze these data and pose biologically interesting questions.

Proper citation: ApiDots (RRID:SCR_001778) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/immunology/index

An annotated, searchable collection of HIV-1 cytotoxic and helper T-cell epitopes and antibody binding sites, plus related tools and information. The goal of this database is to provide a comprehensive listing of defined HIV epitopes. These data are also printed in the HIV Molecular Immunology compendium, which is updated yearly and provided free of charge to scientific researchers, both by online download and as a printed copy. The data included in this database are extracted from the HIV immunology literature. HIV-specific B-cell and T-cell responses are summarized and annotated. Immunological responses are divided into three sections, CTL (CD8+), T helper (CD4+), and antibody. Within these sections, defined epitopes are organized by protein and binding sites within each protein, moving from left to right through the coding regions spanning the HIV genome. We include human responses to natural HIV infections, as well as vaccine studies in a range of animal models and human trials. Responses that are not specifically defined, such as responses to whole proteins or monoclonal antibody responses to discontinuous epitopes, are summarized at the end of each protein sub-section. Studies describing general HIV responses to the virus, but not to any specific protein, are included at the end of each section. The annotation includes information such as cross-reactivity, escape mutations, antibody sequence, TCR usage, functional domains that overlap with an epitope, immune response associations with rates of progression and therapy, and how specific epitopes were experimentally defined. Basic information such as HLA specificities for T-cell epitopes, isotypes of monoclonal antibodies, and epitope sequences are included whenever possible. All studies that we can find that incorporate the use of a specific monoclonal antibody are included in the entry for that antibody. A single T-cell epitope can have multiple entries, generally one entry per study. Finally, tables and maps of all defined linear epitopes relative to the HXB2 reference proteins are provided. Alignments of CTL, helper T-cell, and antibody epitopes are available through the search interfaces. Only responses to HIV-1 and HIV-2 are included in the database.

Proper citation: HIV Molecular Immunology Database (RRID:SCR_002893) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/vaccine/home.html

An overview of HIV and SIV vaccine trials and their outcomes. It was developed as a tool for compilation, search and comparison of published studies on SIV, HIV and SHIV vaccine trials in nonhuman primates. We used a set of criteria to scan Pubmed for relevant studies to enter into the database. In selecting studies for entry, priority was given to recently published studies in journals generally regarded as the primary source of information pertaining to HIV and SIV vaccine research in nonhuman primates. In most cases, we give priority to challenge studies, where the animals received a live virus to measure the "efficacy" of the immunogen(s) inoculated during the course of the investigation. The HIV Sequence Database focuses on five primary goals: *Collecting HIV and SIV sequence data (all sequences since 1987) *Curating and annotating this data, and making it available to the scientific community *Computer analysis of HIV and related sequences *Production of software for the analysis of (sequence) data *Publication of the data and analyses on this site and in a yearly printed publication, the HIV sequence Compendium, which is available free of charge

Proper citation: Nonhuman Primate HIV/SIV Vaccine Trials Database (RRID:SCR_002274) Copy   

•   Source: SciCrunch Registry

http://metagenomics.anl.gov/

An automated analysis platform for metagenomes providing quantitative insights into microbial populations based on sequence data. The server primarily provides upload, quality control, automated annotation and analysis for prokaryotic metagenomic shotgun samples.

Proper citation: MG-RAST (RRID:SCR_004814) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/cran/DrInsight/src/R/drug.identification.R

Software connectivity mapping based drug repurposing tool that identifies drugs that can potentially reverse query disease phenotype or have similar functions with query drugs.

Proper citation: DrInsight (RRID:SCR_023871) Copy   

•   Source: SciCrunch Registry

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

•   Source: SciCrunch Registry

https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   

•   Source: SciCrunch Registry