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http://www.suba.bcs.uwa.edu.au/

SUBA provides a powerful tool to investigate subcellular localization in Arabidopsis. SUBA houses large scale proteomic and GFP localization sets from cellular compartments of Arabidopsis, and also contains pre-compiled bioinformatic predictions for protein subcellular localizations. The Database functions through the unification of disparate datasets and through the provision of a web accessible interface for the construction of user based queries resulting in a one-stop-shop for protein localization in this model plant. Subcellular localization information can contribute towards our understanding of protein function, protein redundancy and of biological inter-relationships. In an attempt to get a clearer picture of our experimental data and to more generally understand subcellular partitioning we have brought together various data sources to build SUBA.

Proper citation: SUB-cellular location database for Arabidopsis proteins II (RRID:SCR_006668) Copy   

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http://www.mc.vanderbilt.edu/root/vumc.php?site=chtn%20western%20division

The Cooperative Human Tissue Network- Western Division at Vanderbilt University Medical Center is one of six institutions throughout the country funded by the National Cancer Institutes to procure and distribute remnant human tissues to biomedical researchers throughout the United States and Canada. CHTN operates through a shared networking system which allows investigators greater access to available research specimens. CHTN offers a variety of preparation and preservation techniques to ensure investigators are receiving the quality specimens needed for research. Remnant tissues are obtained from surgical resections and autopsies and are procured to the specifications of the investigator.

Proper citation: Cooperative Human Tissue Network Western Division at Vanderbilt University Medical Center (RRID:SCR_006661) Copy   

•   Source: SciCrunch Registry

http://www.re3data.org/

Global registry of research data repositories from all academic disciplines that allows the easy identification of appropriate research data repositories, both for data producers and users. Information icons display principal attributes of a repository that can be used for multi-faceted searches. Repository operators can suggest their infrastructures to be listed via a simple application form. A repository is indexed when the minimum requirements are met, i.e. mode of access to the data and repository, as well as the terms of use.

Proper citation: re3data.org (RRID:SCR_006782) Copy   

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http://prodoric.tu-bs.de/

Database about gene regulation and gene expression in prokaryotes. It includes a manually curated and unique collection of transcription factor binding sites. A variety of bioinformatics tools for the prediction, analysis and visualization of regulons and gene reglulatory networks is included. The integrated approach provides information about molecular networks in prokaryotes with focus on pathogenic organisms. In detail this concerns: * transcriptional regulation (transcription factors and their DNA binding sites * signal transduction (two-component systems, phosphylation cascades) * protein interactions (complex formation, oligomerization) * biochemical pathways (chemical reactions) * other regulation events (e.g. codon usage, etc. ...) It aims to be a resource to model protein-host interactions and to be a suitable platform to analyze high-throughput data from proteomis and transcriptomics experiments (systems biology). Currently it mainly contains detailed information about operon and promoter structures including huge collections of transcription factor binding sites. If an appropriate number of regulatory binding sites is available, a position weight matrix (PWM) and a sequence logo is provided, which can be used to predict new binding sites. This data is collected manually by screening the original scientific literature. PRODORIC also handles protein-protein interactions and signal-transduction cascades that commonly occur in form of two-component systems in prokaryotes. Furthermore it contains metabolic network data imported from the KEGG database., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRODORIC (RRID:SCR_007074) Copy   

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http://www.bioinfo.no/tools/TAED

A database of sequence alignments and phylogenetic trees for chordates and embryophytes. The Adaptive Evolution Database (TAED) was first presented as a collection of branches from chordate and embryophyte gene families with fast evolutionary rates mapped onto the NCBI taxonomy (1,2). The original gene families were from the Master Catalog and are proprietary (3). A new version of TAED is now presented as a taxonomic shell together with a gene family database. In addition to multiple sequence alignments and phylogenetic trees for all families of chordate and embryophyte sequences, the ratio of non-synonymous to synonymous nucleotide substitution rates (Ka/Ks) is provided for each branch of every phylogenetic tree. This ratio, when significantly greater than 1, is an indicator of positive selection and potentially a change of function of the encoded protein. With a gene tree to species tree mapping, the branches significantly greater than 1 are collated together in a phylogenetic context. The framework is expandable to incorporate other genomic-scale information in a phylogenetic context. Ultimately, the database is designed both to provide high-quality gene families with multiple sequence alignments and phylogenetic trees for chordates and embryophytes, and to enable asking the question, What makes each species unique at the molecular genomic level?

Proper citation: TAED - The Adaptive Evolution Database (RRID:SCR_006930) Copy   

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http://www.dddc.ac.cn/pdtd/

It is a dual function database that associates an informatics database to a structural database of known and potential drug targets. PDTD is a comprehensive, web-accessible database of drug targets, and focuses on those drug targets with known 3D-structures. PDTD contains 1207 entries covering 841 known and potential drug targets with structures from the Protein Data Bank (PDB). Drug targets of PDTD were categorized into 15 and 13 types according to two criteria: therapeutic areas and biochemical criteria. The database supports extensive searching function using PDB ID, target name and category, related disease.

Proper citation: Potential Drug Target Database (RRID:SCR_007069) Copy   

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http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

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.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

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http://www.physionet.org/physiobank/database/gaitpdb/

Database that contains measures of gait from 93 patients with idiopathic PD (mean age: 66.3 years; 63% men), and 73 healthy controls (mean age: 66.3 years; 55% men). The database includes the vertical ground reaction force records of subjects as they walked at their usual, self-selected pace for approximately 2 minutes on level ground. Underneath each foot were 8 sensors (Ultraflex Computer Dyno Graphy, Infotronic Inc.) that measure force (in Newtons) as a function of time. The output of each of these 16 sensors has been digitized and recorded at 100 samples per second, and the records also include two signals that reflect the sum of the 8 sensor outputs for each foot. This database also includes demographic information, measures of disease severity (i.e., using the Hoehn & Yahr staging and/or the Unified Parkinson's Disease Rating Scale) and other related measures (available in HTML or xls spreadsheet format). A subset of the database includes measures recorded as subjects performed a second task (serial 7 subtractions) while walking, which shows excerpts of swing time series from a patient with PD and a control subject, under usual walking conditions and when performing serial 7 subtractions. Under usual walking conditions, variability is larger in the patient with PD (Coefficient of Variation = 2.7%), compared to the control subject (CV = 1.3%). Variability increases during dual tasking in the subject with PD (CV = 6.5%), but not in the control subject (CV = 1.2%).

Proper citation: Gait in Parkinson's Disease (RRID:SCR_006891) Copy   

•   Source: SciCrunch Registry

http://arabidopsis.med.ohio-state.edu

An information resource of Arabidopsis promoter sequences, transcription factors and their target genes that contains three databases. *AtcisDB consists of approximately 33,000 upstream regions of annotated Arabidopsis genes (TAIR9 release) with a description of experimentally validated and predicted cis-regulatory elements. *AtTFDB contains information on approximately 1,770 transcription factors (TFs). These TFs are grouped into 50 families, based on the presence of conserved domains. *AtRegNet contains 11,355 direct interactions between TFs and target genes. They provide free download of Arabidopsis thaliana cis-regulatory database (AtcisDB) and transcription factor database (AtTFDB).

Proper citation: Arabidopsis Gene Regulatory Information Server (RRID:SCR_006928) Copy   

•   Source: SciCrunch Registry

https://www.embrys.jp/embrys/html/About.html

Data collection of gene expression patterns mapped in whole-mount mouse embryo (ICR strain) of mid-gestational stages (Embryonic Day 9.5, 10.5, 11.5), in which most striking dynamics in pattern formation and organogenesis is observed. Collection of gene expression patterns of transcription factors (TFs) and TF-related factors such as transcription cofactors. Genes were extracted from databases including RIKEN Transcription Factor Database and Panther Classification System.

Proper citation: EMBRYS (RRID:SCR_006689) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database of sequence tagged sites (STSs) derived from STS-based maps and other experiments. STSs are defined by PCR primer pairs and are associated with additional information such as genomic position, genes, and sequences. Chromosome maps are labeled by name of the originating organism, the map title, total markers, total UniSTSs and links to view maps as well as research documents available through PubMed, another NCBI database. The search functions within UniSTS allow the user to search by gene marker, chromosome, gene symbol and gene description terms to locate markers on specified genes. A representation of the UniSTS datasets is available by ftp. NOTE: All data from this resource have been moved to the Probe database, http://www.ncbi.nlm.nih.gov/probe. You can retrieve all UniSTS records by searching the probe database using the search term unists(properties). (use brackets insead of parenthesis). Additionally, legacy data remain on the NCBI FTP Site in the UniSTS Repository (ftp://ftp.ncbi.nih.gov/pub/ProbeDB/legacy_unists).

Proper citation: UniSTS (RRID:SCR_006843) Copy   

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

A database for phylogenetic classification for proteins encoded in complete genomes. Clusters of Orthologous Groups of proteins (COGs) were delineated by comparing protein sequences encoded in complete genomes, representing major phylogenetic lineages. Each COG consists of individual proteins or groups of paralogs from at least 3 lineages and thus corresponds to an ancient conserved domain. Please be aware that COGs hasn't been updated in many years and will not be.

Proper citation: COG (RRID:SCR_007139) Copy   

•   Source: SciCrunch Registry

http://murphylab.web.cmu.edu/services/SLIF/

SLIF finds fluorescence microscope images in on-line journal articles, and indexes them according to cell line, proteins visualized, and resolution. Images can be accessed via the SLIF Web database. SLIF takes on-line papers and scans them for figures that contain fluorescence microscope images (FMIs). Figures typically contain multiple FMIs, to SLIF must segment these images into individual FMIs. When the FMI images are extracted, annotations for the images (for instance, names of proteins and cell-lines) are also extracted from the accompanying caption text. Protein annotation are also used to link to external databases, such as the Gene Ontology DB. The more detailed process includes: segmentation of images into panels; panel classification, to find FMIs; segmentation of the caption, to find which portions of the caption apply to which panels; text-based entity extraction; matching of extracted entities to database entries; extraction of panel labels from text and figures; and alignment of the text segments to the panels. Extracted FMIs are processed to find subcellular location features (SLFs), and the resulting analyzed, annotated figures are stored in a database, which is accessible via SQL queries.

Proper citation: Subcellular Location Image Finder (RRID:SCR_006723) Copy   

•   Source: SciCrunch Registry

http://www.mtf.org

The Musculoskeletal Transplant Foundation is a non-profit service organization dedicated to providing quality allograft tissue through a commitment to excellence in education, research, recovery and care for recipients, donors and their families. We are a national consortium comprised of academic medical institutions, organ procurement organizations and tissue recovery organizations. MTF was created as a charitable organization with a mission that is dedicated to the needs of donors, donor families, patients and surgeons. We focus on respectful stewardship of the donated gift while advancing the science and practice of bone, ligament, cartilage and skin transplantation. Since our inception in 1987, MTF has recovered more than 60,000 donors and distributed more than 3 million grafts for transplantation. We also support research to expand the science of transplantation, and we encourage the efforts of our members and non-member clients to improve the understanding of donation and transplantation among the medical community and the public at large. Our policies are developed and implemented by MTF''''s Medical Board of Trustees, Donation Board of Trustees and Board of Directors, composed of physicians and recovery agency representatives who are dedicated to the mission of the Foundation. This fundamental commitment enables us to set and maintain the highest levels of safety assurance and quality control in all phases of our operations.

Proper citation: Musculoskeletal Transplant Foundation - MTF (RRID:SCR_006684) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1347366/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. It provides a common access point to interaction resources at MIPS. It is designed to support the PSI-MI standard, for both downloading and uploading data. It provides the user with intuitive query forms to quickly retrieve the interactions of interest. Graphical representations allow an easy navigation through the protein interaction networks.

Proper citation: MPact: Representation of Interaction Data at MIPS (RRID:SCR_006687) Copy   

•   Source: SciCrunch Registry

http://www.mbio.ncsu.edu/RNaseP/home.html

Ribonuclease P is responsible for the 5''-maturation of tRNA precursors. Ribonuclease P is a ribonucleoprotein, and in bacteria (and some Archaea) the RNA subunit alone is catalytically active in vitro, i.e. it is a ribozyme. The Ribonuclease P Database is a compilation of ribonuclease P sequences, sequence alignments, secondary structures, three-dimensional models and accessory information. The database contains information on bacterial, archaeal, and eukaryotic RNase P. The RNase P and protein sequences are available from phylogentically-arranged lists, individual sequences, or aligned in GenBank format. The database also provides secondary structures and 3D models, as well as movies, still images, and other accessory information.

Proper citation: RNase P Database (RRID:SCR_006680) Copy   

•   Source: SciCrunch Registry

http://www.disprot.org/

The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Users can BLAST sequences, browse by protein name, or view by protein function and functional subclass.

Proper citation: DisProt - Database of Protein Disorder (RRID:SCR_007097) Copy   

•   Source: SciCrunch Registry

http://www.biologie.ens.fr/diatomics/EST3

A searchable databases of diatom ESTs (expressed sequence tags) that can be used to explore diatom biology. Research has generated approximately 90,000 ESTs from P. tricornutum cells grown in a range of conditions. Here we present a database of these sequences, that can be used for digital gene expression studies to explore this organisms responses to a range of environmental conditions. Such studies should provide a foundation for interpreting the ecological success of diatoms.

Proper citation: The Diatom EST Database (RRID:SCR_007090) Copy   

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http://blogs.nature.com/actionpotential

Action Potential is a forum operated by neuroscience editors at Nature for the entire neuroscience community. We''ll discuss what''s new and exciting in science, be it in our journals or elsewhere, as well as science policy and publishing and provide updates from major meetings. Although we provide the opportunity to comment as a service to the community, we do not endorse all viewpoints represented here. To contact the contributors directly with confidential questions or suggestions for future entries, please e-mail n.gray (at) us.nature.com.

Proper citation: Action Potential (RRID:SCR_006836) Copy   

•   Source: SciCrunch Registry

http://www.athamap.de/

Genome wide map of putative transcription factor binding sites in Arabidopsis thaliana genome.Data in AthaMap is based on published transcription factor (TF) binding specificities available as alignment matrices or experimentally determined single binding sites.Integrated transcriptional and post transcriptional data.Provides web tools for analysis and identification of co-regulated genes. Provides web tools for database assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana.

Proper citation: AthaMap (RRID:SCR_006717) Copy   

•   Source: SciCrunch Registry