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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Kidney Interactive Transcriptomics Resource Report Resource Website 50+ mentions |
Kidney Interactive Transcriptomics (RRID:SCR_017209) | KIT | analysis service resource, data or information resource, production service resource, service resource | Software tool as analyzer for kidney single cell datasets. Allows users to query gene expression from mouse or human kidney and human kidney organoid single cell datasets. For details about datasets visit ReBuilding a Kidney website. | Analyzer, kidney, single, cell, dataset, gene, expression, mouse, human, organoid | Free, Freely available | https://www.rebuildingakidney.org/ | SCR_017209 | 2026-08-29 11:30:46 | 99 | |||||||||
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Biospecimen Repository Access and Data Sharing Resource Report Resource Website 1+ mentions |
Biospecimen Repository Access and Data Sharing (RRID:SCR_017383) | BRADS | data or information resource, database | Access to data from the Division of Intramural Population Health Research (DIPHR) of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) from completed studies, including biospecimens and ancillary data. | child, health, human, development, dataset | NICHD | Restricted | https://brads.nichd.nih.gov/AccessRequest/AccessRequest/ | SCR_017383 | , BRADS, Biospecimen Repository Access and Data Sharing | 2026-08-29 11:30:46 | 1 | |||||||
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The 10000 Immunomes Resource Report Resource Website 1+ mentions |
The 10000 Immunomes (RRID:SCR_016624) | 10KIP | data or information resource, database | Collection of reference datasets for human immunology, derived from control subjects in the NIAID ImmPort database . Available data include flow cytometry, CyTOF, multiplex ELISA, gene expression, HAI titers, clinical lab tests, HLA type, and others. | collection, reference, dataset, human, immunology, control, subject, NIAID, ImmPort, database |
is related to: The Immunology Database and Analysis Portal (ImmPort) is related to: NIAID |
NIAID HHSN272201200028C | PMID:30304689 | Public, Free, Available for download, Freely available | SCR_016624 | 10K Immunomes Project, 000 Immunomes Project, 000 Immunomes, 10 | 2026-08-29 11:30:23 | 1 | ||||||
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Transcriptional Regulatory Relationships Unrevealed by Sentence based Text mining database Resource Report Resource Website 100+ mentions |
Transcriptional Regulatory Relationships Unrevealed by Sentence based Text mining database (RRID:SCR_022554) | TRRUST | data or information resource, database | TRUSST is reference database of human transcriptional regulatory interactions.TRRUST v2 is manually curated expanded reference database of human and mouse transcriptional regulatory interactions. | human and mouse transcriptional regulatory interactions, regulatory networks, transcriptional regulatory networks, human, mouse | Brain Korea 21 PLUS program ; National Research Foundation of Korea |
PMID:26066708 DOI:10.1093/nar/gkx1013 |
Restricted | https://www.grnpedia.org/trrust/v1/ | SCR_022554 | TRRUST database, TRRUSTv2 | 2026-08-29 11:30:48 | 269 | ||||||
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Phenologs Resource Report Resource Website 1+ mentions |
Phenologs (RRID:SCR_005529) | Phenologs | data or information resource, database | Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided. | gene, phenotype, ortholog, genotype, human, mouse, yeast, worm | has parent organization: University of Texas at Austin; Texas; USA | Texas Advanced Research Program ; Welch Foundation ; Packard Fellowship ; March of Dimes ; Texas Institute for Drug and Diagnostic Development ; NSF ; NIH ; NIGMS |
PMID:20308572 | nlx_144624 | SCR_005529 | phenologs.org, Phenologs - Systematic discovery of non-obvious disease models and candidate genes | 2026-08-29 11:29:36 | 4 | ||||||
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Oscillatory Thoughts Resource Report Resource Website |
Oscillatory Thoughts (RRID:SCR_005481) | Oscillatory Thoughts | blog, data or information resource, narrative resource | Bradley Voytek''''s blog is where he tries out new ideas. He will often be wrong, but that''''s the point. He is a Neuroscientist studying human cognition, neuroplasticity, and brain computer interfacing. Into really geeky stuff. World zombie neuroscience expert. Also runs brainSCANr.com with his wife, Jessica. | neuroscience, human, cognition, neuroplasticity, brain computer interfacing | is related to: brainSCANr | nlx_144601 | SCR_005481 | Oscillatory Thoughts - Thoughts of a Neuroscientist | 2026-08-29 11:29:36 | 0 | ||||||||
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DTI White Matter Atlas Resource Report Resource Website |
DTI White Matter Atlas (RRID:SCR_005279) | DTI White Matter Atlas | atlas, data or information resource | DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention. | white matter, brain, template, human, magnetic resonance imaging, diffusion tensor imaging, adult human, male, female, cerebellum, mni, talairach | has parent organization: Johns Hopkins University School of Medicine; Baltimore, Maryland; USA | Normal | NCRR P41RR015241 | Account required | nlx_144313 | SCR_005279 | 2026-08-29 11:29:40 | 0 | ||||||
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TranspoGene Resource Report Resource Website 1+ mentions |
TranspoGene (RRID:SCR_005634) | data or information resource, database | A publicly available database of Transposed elements (TEs) which are located within protein-coding genes of 7 organisms: human, mouse, chicken, zebrafish, fruilt fly, nematode and sea squirt. Using TranspoGene the user can learn about the many aspects of the effect these TEs have on their hosting genes, such as: exonization events (including alternative splicing-related data), insertion of TEs into introns, exons, and promoters, specific location of the TE over the gene, evolutionary divergence of the TE from its consensus sequence and involvement in diseases. TranspoGene database is quickly searchable through its website, enables many kinds of searches and is available for download. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome. | element, eukaryotic, evolutionary, exon, exonization, family, fruit fly, gene, genome, alternative, chicken, coding, disease, divergence, genomic, hosting, human, human genome databases, intron, location, map, maps, mouse, mrna, nematode, organism, pattern, promoter, protein, sea squirt, sequence, splicing, transcript, transcriptome, transposed, viewers, worm, zebrafish | has parent organization: Tel Aviv University; Ramat Aviv; Israel | nif-0000-03579 | SCR_005634 | TranspoGene | 2026-08-29 11:29:36 | 9 | |||||||||
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Laboratory of Neuro Imaging - YouTube Resource Report Resource Website |
Laboratory of Neuro Imaging - YouTube (RRID:SCR_005462) | loniucla - YouTube | data or information resource, video resource | Videos uploaded to YouTube by the Laboratory of Neuro Imaging (LONI). The Laboratory of Neuro Imaging at UCLA strives to improve our understanding of the brain in health and disease. LONI is a leader in the development of advanced computational algorithms and scientific approaches for the comprehensive and quantitative mapping of brain structure and function. | human, mouse, brain, health, disease, brain structure, brain function | nlx_144582 | http://www.youtube.com/user/loniucla | SCR_005462 | LONI - YouTube | 2026-08-29 11:29:42 | 0 | ||||||||
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YanHuang Project Resource Report Resource Website 50+ mentions |
YanHuang Project (RRID:SCR_006077) | data or information resource, database | This database presents the entire DNA sequence of the first diploid genome sequence of a Han Chinese, a representative of Asian population. The genome, named as YH, represents the start of YanHuang Project, which aims to sequence 100 Chinese individuals in 3 years. It was assembled based on 3.3 billion reads (117.7Gbp raw data) generated by Illumina Genome Analyzer. In total of 102.9Gbp nucleotides were mapped onto the NCBI human reference genome (Build 36) by self-developed software SOAP (Short Oligonucleotide Alignment Program), and 3.07 million SNPs were identified. The personal genome data is illustrated in a MapView, which is powered by GBrowse. A new module was developed to browse large-scale short reads alignment. This module enabled users track detailed divergences between consensus and sequencing reads. In total of 53,643 HGMD recorders were used to screen YH SNPs to retrieve phenotype related information, to superficially explain the donor's genome. Blast service to align query sequences against YH genome consensus was also provided. | genome, genetic, adult, chromosome, clinical, control, genomic, human, normal, FASEB list | has parent organization: BGI; Shenzhen; China | nif-0000-03654 | SCR_006077 | YH1 | 2026-08-29 11:29:39 | 53 | |||||||||
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DBETH - Database for Bacterial ExoToxins for Humans Resource Report Resource Website 1+ mentions |
DBETH - Database for Bacterial ExoToxins for Humans (RRID:SCR_005908) | DBETH | data or information resource, database | Database of Bacterial ExoToxins for Human is a database of sequences, structures, interaction networks and analytical results for 229 exotoxins, from 26 different human pathogenic bacterial genus. All toxins are classified into 24 different Toxin classes. The aim of DBETH is to provide a comprehensive database for human pathogenic bacterial exotoxins. DBETH also provides a platform to its users to identify potential exotoxin like sequences through Homology based as well as Non-homology based methods. In homology based approach the users can identify potential exotoxin like sequences either running BLASTp against the toxin sequences or by running HMMER against toxin domains identified by DBETH from human pathogenic bacterial exotoxins. In Non-homology based part DBETH uses a machine learning approach to identify potential exotoxins (Toxin Prediction by Support Vector Machine based approach). | sequence, structure, interaction network, human, pathogen, bacterial genus, toxin, bacteria, exotoxin, homology, homolog, structure, sequence, domain, prediction, mechanism, activity, bio.tools |
is listed by: Debian is listed by: bio.tools has parent organization: CSIR - Indian Institute of Chemical Biology; Kolkata; India |
Council of Scientific and Industrial Research; New Delhi; India | PMID:22102573 | nlx_149481, biotools:dbeth | https://bio.tools/dbeth | SCR_005908 | Database for Bacterial ExoToxins for Humans | 2026-08-29 11:29:45 | 2 | |||||
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Kabat Database of Sequences of Proteins of Immunological Interest Resource Report Resource Website 1+ mentions |
Kabat Database of Sequences of Proteins of Immunological Interest (RRID:SCR_006465) | data or information resource, database | The Kabat Database determines the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. The Kabat Database searching and analysis tools package is an ASP.NET web-based portal containing lookup tools, sequence matching tools, alignment tools, length distribution tools, positional correlation tools and much more. The searching and analysis tools are custom made for the aligned data sets contained in both the SQL Server and ASCII text flat file formats. The searching and analysis tools may be run on a single PC workstation or in a distributed environment. The analysis tools are written in ASP.NET and C# and are available in Visual Studio .NET 2003/2005/2008 formats. The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences at that time. Bence Jones proteins, mostly from human, were aligned, using the now-known Kabat numbering system, and a quantitative measure, variability, was calculated for every position. Three peaks, at positions 24-34, 50-56 and 89-97, were identified and proposed to form the complementarity determining regions (CDR) of light chains. Subsequently, antibody heavy chain amino acid sequences were also aligned using a different numbering system, since the locations of their CDRs (31-35B, 50-65 and 95-102) are different from those of the light chains. CDRL1 starts right after the first invariant Cys 23 of light chains, while CDRH1 is eight amino acid residues away from the first invariant Cys 22 of heavy chains. During the past 30 years, the Kabat database has grown to include nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules and other proteins of immunological interest. It has been used extensively by immunologists to derive useful structural and functional information from the primary sequences of these proteins. | functional, align, alignment, amino acid, antibody, antigen, biological, cdr, chain, class i, class ii, combining, complementarity, complex, delineation, heavy, histocompatibility, human, immunological, immunological database, light, macromolecule, mhc, molecule, nucleotide, position, protein, receptor, region, sequence, structural, t cell | has parent organization: Northwestern University; Illinois; USA | nif-0000-21233 | SCR_006465 | Kabat Database | 2026-08-29 11:29:41 | 2 | |||||||||
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mitopred Resource Report Resource Website 1+ mentions |
mitopred (RRID:SCR_006135) | MITOPRED | analysis service resource, data analysis service, production service resource, service resource | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution. | yeast, c. elegans, drosophila, mouse, human, arabidopsis, bio.tools |
is listed by: Debian is listed by: bio.tools is listed by: SoftCite has parent organization: University at Albany; New York; USA |
THIS RESOURCE IS NO LONGER IN SERVICE | biotools:mitopred, nif-0000-03956, BioTools:mitopred | https://bio.tools/mitopred, https://bio.tools/mitopred, https://bio.tools/mitopred | SCR_006135 | A genome-scale method for predicting mitochondrial proteins | 2026-08-29 11:29:45 | 7 | ||||||
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Neurocritic Resource Report Resource Website 1+ mentions |
Neurocritic (RRID:SCR_006528) | Neurocritic | blog, data or information resource, narrative resource | The Neurocritic is a blog deconstructing the most sensationalistic recent findings in Human Brain Imaging, Cognitive Neuroscience, and Psychopharmacology. Born in West Virginia in 1980, The Neurocritic embarked upon a roadtrip across America at the age of thirteen with his mother. She abandoned him when they reached San Francisco and The Neurocritic descended into a spiral of drug abuse and prostitution. At fifteen, The Neurocritic''s psychiatrist encouraged him to start writing as a form of therapy. | human, brain imaging, cognitive neuroscience, psychopharmacology, brain, imaging, neuroimaging | nlx_144592 | SCR_006528 | The Neurocritic | 2026-08-29 11:29:47 | 2 | |||||||||
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Rickettsia Genome Database Resource Report Resource Website 1+ mentions |
Rickettsia Genome Database (RRID:SCR_007102) | data or information resource, database, image | THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams. | evolutionary, africae, alignment, arthropod, bacteria, bellii, conorii, dendrogram, disease, genome, genomic, human, intracellular, massiliae, mechanism, pathogenicity, physiology, prowazekii, rickettsia, sequence, specie, journal article, topical portal | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-20993 | SCR_007102 | RicBase | 2026-08-29 11:29:48 | 1 | |||||||||
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Biomolecular Object Network Databank Resource Report Resource Website 10+ mentions |
Biomolecular Object Network Databank (RRID:SCR_007433) | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus. | gene, genes, genome, annotation, binding specificity, biological process, complex, dna, genomes, genomic, human, interaction, interactome, ligand, metabolomic, molecular, molecular complex, molecular function, molecular interaction, mouse, ontoglyphs, ontology terms, pathway, photon, protein, protein-protein interactions, proteomic, rna, sequence, structure, sub-cellular localization, taxonomy, unclassified biological entity | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-00571 | SCR_007433 | BOND | 2026-08-29 11:29:59 | 17 | |||||||||
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MIPS Ustilago maydis Database Resource Report Resource Website 1+ mentions |
MIPS Ustilago maydis Database (RRID:SCR_007563) | data or information resource, database | The MIPS Ustilago maydis Genome Database aims to present information on the molecular structure and functional network of the entirely sequenced, filamentous fungus Ustilago maydis. The underlying sequence is the initial release of the high quality draft sequence of the Broad Institute. The goal of the MIPS database is to provide a comprehensive genome database in the Genome Research Environment in parallel with other fungal genomes to enable in depth fungal comparative analysis. The specific aims are to: 1. Generate and assemble Whole Genome Shotgun sequence reads yielding 10X coverage of the U. maydis genome 2. Integrate the genomic sequence assembly with physical maps generated by Bayer CropScience 3. Perform automated annotation of the sequence assembly 4. Align the strain 521 assembly with the FB1 assembly provided by Exelixis 5. Release the sequence assembly and results of our annotation and analysis to public Ustilago maydis is a basidiomycete fungal pathogen of maize and teosinte. The genome size is approximately 20 Mb. The fungus induces tumors on host plants and forms masses of diploid teliospores. These spores germinate and form haploid meiotic products that can be propagated in culture as yeast-like cells. Haploid strains of opposite mating type fuse and form a filamentous, dikaryotic cell type that invades plant tissue to reinitiate infection. Ustilago maydis is an important model system for studying pathogen-host interactions and has been studied for more than 100 years by plant pathologists. Molecular genetic research with U. maydis focuses on recombination, the role of mating in pathogenesis, and signaling pathways that influence virulence. Recently, the fungus has emerged as an excellent experimental model for the molecular genetic analysis of phytopathogenesis, particularly in the characterization of infection-specific morphogenesis in response to signals from host plants. Ustilago maydis also serves as an important model for other basidiomycete plant pathogens that are more difficult to work with in the laboratory, such as the rust and bunt fungi. Genomic sequence of U. maydis will also be valuable for comparative analysis of other fungal genomes, especially with respect to understanding the host range of fungal phytopathogens. The analysis of U. maydis would provide a framework for studying the hundreds of other Ustilago species that attack important crops, such as barley, wheat, sorghum, and sugarcane. Comparisons would also be possible with other basidiomycete fungi, such as the important human pathogen C. neoformans. Commercially, U. maydis is an excellent model for the discovery of antifungal drugs. In addition, maize tumors caused by U. maydis are prized in Hispanic cuisine and there is interest in improving commercial production. The complete putative gene set of the Broad Institute''s second release is loaded into the database and in addition all deviating putative genes from a putative gene set produced by MIPS with different gene prediction parameters are also loaded. The complete dataset will then be analysed, gene predictions will be manually corrected due to combined information derived from different gene prediction algorithms and, more important, protein and EST comparisons. Gene prediction will be restricted to ORFs larger than 50 codons; smaller ORFs will be included only if similarities to other proteins or EST matches confirm their existence or if a coding region was postulated by all prediction programs used. The resulting proteins will be annotated. They will be classified according to the MIPS classification catalogue receiving appropriate descriptions. All proteins with a known, characterized homolog will be automatically assigned to functional categories using the MIPS functional catalog. All extracted proteins are in addition automatically analysed and annotated by the PEDANT suite. | drug, environment, filamentous, functional, fungal, fungal genome databases, fungus, gene, genetic, basidiomycete, cell, codon, culture, dikaryotic, diploid, genome, genomic, germinate, haploid, host, human, infection, maize, mating, meiotic, model, molecular, morphogenesis, network, orf, pathogen, pathologist, phytopathogen, phytopathogenesis, plant, protein, recombination, sequence, signal, spore, strain, structure, teliospore, teosinte, tissue, tumor, ustilago maydis, virulence, yeast | nif-0000-21276 | SCR_007563 | MUMDB | 2026-08-29 11:29:53 | 9 | ||||||||||
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WHO Collaborating Centre for Drug Statistics Methodology Resource Report Resource Website 10+ mentions |
WHO Collaborating Centre for Drug Statistics Methodology (RRID:SCR_000677) | data or information resource, database | The official compendium for the Anatomical Therapeutic Chemical Classification System (ATC)-code descriptions. The Centre's main tasks are development and maintenance of the ATC/DDD system, including: * To classify drugs according to the ATC system. * Priority will be given to the classification of single substances, while combination products available internationally (i.e. important fixed combinations) will be dealt with as far as possible. * To establish DDDs for drugs which have been assigned an ATC code. * To review and revise as necessary the ATC classification system and DDDs. * To stimulate and influence the practical use of the ATC system by co-operating with researchers in the drug utilization field. Support: The WHO Collaborating Centre for Drug Statistics Methodology was established in 1982. The Centre is situated in Oslo at the Norwegian Institute of Public Health. The Centre is funded by the Norwegian government. | drug, clinical, human, people, FASEB list | nif-0000-10553 | SCR_000677 | WHOCC | 2026-08-29 11:29:15 | 39 | ||||||||||
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Collecting Duct Database Resource Report Resource Website |
Collecting Duct Database (RRID:SCR_000759) | CDDB | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This database is intended to serve as a learning tool to obtain curated information for the design of microarray targets to scan collecting duct tissues (human, rat, mouse). The database focuses on regulatory and transporter proteins expressed in the collecting duct, but when collecting duct proteins are a member of a larger family of proteins, common additional members of the family are included even if they have not been demonstrated to be expressed in the collecting duct. An Internet-accessible database has been devised for major collecting duct proteins involved in transport and regulation of cellular processes. The individual proteins included in this database are those culled from literature searches and from previously published studies involving cDNA arrays and serial analysis of gene expression (SAGE). Design of microarray targets for the study of kidney collecting duct tissues is facilitated by the database, which includes links to curated base pair and amino acid sequence data, relevant literature, and related databases. Use of the database is illustrated by a search for water channel proteins, aquaporins, and by a subsequent search for vasopressin receptors. Links are shown to the literature and to sequence data for human, rat, and mouse, as well as to relevant web-based resources. Extension of the database is dynamic and is done through a maintenance interface. This permits creation of new categories, updating of existing entries, and addition of new ones. CDDB is a database that organizes lists of genes found in collecting duct tissues from three mammalian species: human, rat, and mouse. Proteins are divided into categories by family relationships and functional classification, and each category is assigned a section in the database. Each section includes links to the literature and to sequence information for genes, proteins, expressed sequence tags, and related information. The user can peruse a section or use a search engine at the bottom of the web page to search the database for a name or abbreviation or for a link to a sequence. Each entry in the database includes links to relevant papers in the kidney and collecting duct literature. It uses links to PubMed to generate MEDLINE searches for retrieval of references. In addition, each entry includes links to curated sequence data available in LocusLink. Individual links are made to sequence and protein data for human, rat, and mouse. Links are then added as curated sequences become available for proteins identified in the renal collecting duct and for proteins identified in kidney and similar in function or homologous to proteins identified in the collecting duct. | expressed sequence tag, expression, family, functional, gene, aquaporin, array, cdna, classification, collecting duct, homologous, human, kidney, literature, mammal, mammalian, microarray, mouse, protein, protein localization and targeting databases, rat, receptor, regulatory, relationship, scan, serial analysis, specie, target, tissue, transporter, vasopressin, water channel protein | has parent organization: National Institutes of Health | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21078 | SCR_000759 | Collecting Duct Database | 2026-08-29 11:29:07 | 0 | |||||||
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National Science Foundation Graduate Research Fellowship Program Resource Report Resource Website 100+ mentions |
National Science Foundation Graduate Research Fellowship Program (RRID:SCR_001487) | funding resource, graduate program resource | The National Science Foundation's Graduate Research Fellowship Program (GRFP) helps ensure the vitality of the human resource base of science and engineering in the United States and reinforces its diversity. The program recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based master's and doctoral degrees in the U.S. and abroad. The NSF welcomes applications from all qualified students and strongly encourages under-represented populations, including women, under-represented racial and ethnic minorities, and persons with disabilities, to apply for this fellowship. Fellows share in the prestige and opportunities that become available when they are selected. Fellows benefit from a three-year annual stipend of $30,000 along with a $10,500 cost of education allowance for tuition and fees, a one-time $1,000 international travel allowance and the freedom to conduct their own research at any accredited U.S., or foreign institution of graduate education they choose. NSF Fellows are anticipated to become knowledge experts who can contribute significantly to research, teaching, and innovations in science and engineering. So that the nation can build fully upon the strength and creativity of a diverse society, the Foundation welcomes applications from all qualified individuals. Women, under-represented minorites and people with disabilities are encouraged to apply. Those with disabilities are additionally accommodated by the Foundation to provide for the most successful graduate experience possible. Sponsors: This program is supported by the National Science Foundation (NSF). | engineering, fellowship, graduate, human, mathematics, research, science, technology | Free, Freely available | nif-0000-10366 | SCR_001487 | NSF GRFP | 2026-08-29 11:29:18 | 169 |
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