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https://www.ncbi.nlm.nih.gov/genbank/dbest/

Database as a division of GenBank that contains sequence data and other information on single-pass cDNA sequences, or Expressed Sequence Tags, from a number of organisms.

Proper citation: dbEST (RRID:SCR_008132) Copy   

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http://www.cmbn.no/ottersen/

A laboratory that investigates the molecular mechanisms involved in the development of acute and chronic neurodegenerative disease, with a focus on the role of glutamate excitotoxicity. It aims at unraveling the molecular basis for cell death and edema development in stroke, and explores the pathophysiology of Alzheimer's disease and temporal lobe epilepsy. The main objective of the LMN is to advance understanding of the role of glutamate, as a transmitter substance in the normal brain and as a mediator of excitotoxicity in pathological conditions such as stroke. To this end the LMN employs several vital and nonvital imaging techniques. Model systems includes organotypic slice cultures and transgenic animals. An important focus of the LMN is to explore the role of DNA damage and repair in the pathogenesis of neurodegenerative disease. LMN is also engaged in research on molecular mechanism underlying brain edema, epilepsy, and Alzheimer's disease.

Proper citation: Laboratory of Molecular Neuroscience, University of Oslo (RRID:SCR_008097) Copy   

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http://www.usc.edu/

American private research university in Los Angeles, California. Founded in 1880, it is the oldest private research university in California. USC has historically educated a large number of the nation's business leaders and professionals.

Proper citation: University of Southern California; Los Angeles; USA (RRID:SCR_008093) Copy   

•   Source: SciCrunch Registry

http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/

Software that currently allows to process an amount of bisulfite sequencing reads obtained in one or several bisulfite sequencing experiments.

Proper citation: BiQAnalyzer HT (RRID:SCR_008045) Copy   

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http://tnprc.tulane.edu

Center focused on understanding human health problems, including infectious diseases that require the use of nonhuman primates to develop diagnostics, therapeutics and preventive strategies. Primary research interests include developing vaccines, treatments and diagnostic tools for infectious diseases such as AIDS, tuberculosis, CMV, COVID-19, Lyme disease, and malaria. TNPRC has both biosafety level 2 and biosafety level 3 laboratories facilities to accommodate various research needs, and is the only National Primate Research Center with Regional Biosafety Laboratory.

Proper citation: Tulane National Biomedical Research Center (RRID:SCR_008167) Copy   

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http://www.interaction-proteome.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 28, 2013. (URL is no longer valid) A platform for high-throughput proteomic analysis. Major objectives of IPP include the establishment of a broadly applicable platform of routine methods for the analysis of protein interaction networks in bio-medical research. A multidisciplinary approach will address; * their validation by cell biological, biochemical and biophysical methods. * their collection in a new type of public database. * their exploitation and use for in silico simulations of protein-interaction networks. The innovations generated in IPP will provide the basis for an efficient analysis and systems modeling of fundamental biological processes in health and disease. It will develop novel technology, including a high-end mass spectrometer with extremely large dynamic range, high-density peptide arrays, and improved visualization technology for light and electron microscopy. Additionally, the novel technologies will be validated with selected model systems of high relevance to medicine and biotechnology. Extensive bioinformatics support is a key element in the project to cope with the massive increase in experimental data on protein interactions obtained using the novel technologies. In particular, the efficient integration of disparate data sets represents a key challenge in proteomics and functional genomics. Therefore, the consortium includes the creator of the only European protein-interactions database, MINT. The multi-disciplinary efforts required in the scientific program of IPP are organized into four sub-projects (SP): * SP1: Tools for interaction analysis - SP1 is dedicated to the development of innovative proteomics technology to map protein-interaction networks and their cellular topology for the interaction analyses in SP2 and SP3. * SP2: Identification of interaction partners for protein domains - SP2 will generate (high throughput) data for important protein-protein interactions defined by bioinformatics and biomedical interest and by SP3, utilizing technology developed in SP1. * SP3: Functional analysis of interactions - SP3 focuses on the validation of technologies and tools developed in SP1. It will perform functional analyses of protein-interactions in medically and biochemically relevant prokaryotic and eukaryotic (mammalian) model systems. * SP4: Interactome database and modelling - SP4 provides the required bioinformatics infrastructure for the project, comprising the improvement of the public MINT database for the collection and dissemination of the interactome data; modelling and simulation of protein-interaction networks characterised in SP2 and SP3; and the dissemination of the technology developments to the scientific community.

Proper citation: Interaction Proteome Project (RRID:SCR_008043) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

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http://www.gene-regulation.com/pub/databases.html

In an effort to strongly support the collaborative nature of scientific research, BIOBASE offers academic and non-profit organizations free access to reduced functionality versions of their products. TRANSFAC Professional provides gene regulation analysis solutions, offering the most comprehensive collection of eukaryotic gene regulation data. The professional paid subscription gives customers access to up-to-date data and tools not available in the free version. The public databases currently available for academic and non-profit organizations are: * TRANSFAC: contains data on transcription factors, their experimentally-proven binding sites, and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. * TRANSPATH: provides data about molecules participating in signal transduction pathways and the reactions they are involved in, resulting in a complex network of interconnected signaling components.TRANSPATH focuses on signaling cascades that change the activities of transcription factors and thus alter the gene expression profile of a given cell. * PathoDB: is a database on pathologically relevant mutated forms of transcription factors and their binding sites. It comprises numerous cases of defective transcription factors or mutated transcription factor binding sites, which are known to cause pathological defects. * S/MARt DB: presents data on scaffold or matrix attached regions (S/MARs) of eukaryotic genomes, as well as about the proteins that bind to them. S/MARs organize the chromatin in the form of functionally independent loop domains gained increasing support. Scaffold or Matrix Attached Regions (S/MARs) are genomic DNA sequences through which the chromatin is tightly attached to the proteinaceous scaffold of the nucleus. * TRANSCompel: is a database on composite regulatory elements affecting gene transcription in eukaryotes. Composite regulatory elements consist of two closely situated binding sites for distinct transcription factors, and provide cross-coupling of different signaling pathways. * PathoSign Public: is a database which collects information about defective cell signaling molecules causing human diseases. While constituting a useful data repository in itself, PathoSign is also aimed at being a foundational part of a platform for modeling human disease processes.

Proper citation: Gene Regulation Databases (RRID:SCR_008033) Copy   

•   Source: SciCrunch Registry

http://ncv.unl.edu/Angelettilab/HPV/Database.html

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 August 23, 2016. The Human Papillomaviruses Database collects, curates, analyzes, and publishes genetic sequences of papillomaviruses and related cellular proteins. It includes molecular biologists, sequence analysts, computer technicians, post-docs and graduate research assistants. This Web site has two main branches. The first contains our four annual data books of papillomavirus information, called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. and the second contains papillomavirus genetic sequence data. There is also a New Items location where we store the latest changes to the database or any other current news of interest. Besides the compendium, we also provide genetic sequence information for papilloma viruses and related cellular proteins. Each year they publish a compendium of papillomavirus information called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. which can now be downloaded from this Web site.

Proper citation: HPV Sequence Database (RRID:SCR_008154) Copy   

•   Source: SciCrunch Registry

http://www.genomatix.de/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 13,2026. Genomatix is a privately held company that offers software, databases, and services aimed at understanding gene regulation at the molecular level representing a central part of systems biology. Its multilayer integrative approach is a working implementation of systems biology principles. Genomatix combines sequence analysis, functional promoter analysis, proprietary genome annotation, promoter sequence databases, comparative genomics, scientific literature data mining, pathway databases, biological network databases, pathway analysis, network analysis, and expression profiling into working solutions and pipelines. It also enables better understanding of biological mechanisms under different conditions and stimuli in the biological context of your data. Some of Genomatix'' most valuable assets are the strong scientific background and the years of experience in research & discovery as well as in development & application of scientific software. Their firsthand knowledge of all the complexities involved in the in-silico analysis of biological data makes them a first-rate partner for all scientific projects involving the evaluation of gene regulatory mechanisms. The Genomatix team has more than a decade of scientific expertise in the successful application of computer aided analysis of gene regulatory networks, which is reflected by more than 150 peer reviewed scientific publications from Genomatix'' scientists More than 35,000 researchers in industry and academia around the world use this technology. The software available in Genomatix are: - GenomatixSuite: GenomatixSuite is our comprehensive software bundle including ElDorado, Gene2Promoter, GEMS Launcher, MatInspector and MatBase. GenomatixSuite PE also includes BiblioSphere Pathway Edition. Chromatin IP Software - RegionMiner: Fast, extensive analysis of genomic regions. - ChipInspector: Discover the real power of your microarray data. Genome Annotation Software - ElDorado: Extended Genome Annotation. - Gene2Promoter: Retrieve & analyze promoters - GPD: The Genomatix Promoter Database, which is now included with Gene2Promoter. Knowledge Mining Software - BiblioSpere : The next level of pathway/genomics analysis. - LitInspector: Literature and pathway analysis for free. Sequence Analysis Software - GEMS Launcher: Our integrated collection of sequence analysis tools. - MalInspector: Search transcription factor binding sites - MatBase: The transcription factor knowledge base. Other (no registration required) Software - DiAlign: Multiple alignment of DNA/protein sequence. - Genomatix tools: Various small tools for sequence statistics, extraction, formatting, etc.

Proper citation: Genomatix Software: Understanding Gene Regulation (RRID:SCR_008036) Copy   

•   Source: SciCrunch Registry

http://erlichlab.wi.mit.edu/lobSTR/

A software tool for profiling Short Tandem Repeats (STRs) from high throughput sequencing data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: lobSTR (RRID:SCR_008030) Copy   

•   Source: SciCrunch Registry

https://plantcyc.org/databases/aracyc/15.0

Curated species-specific database present at the Plant Metabolic Network. It has a large number of experimentally supported enzymes and metabolic pathways, but it also houses a substantial number of computationally predicted enzymes and pathways.

Proper citation: AraCyc (RRID:SCR_008109) Copy   

•   Source: SciCrunch Registry

http://www.baderlab.org/Software/ActiveDriver

A statistical method for interpreting variations in protein sequence (e.g. coding SNPs in the population, SNVs in cancer genomes) in the context of protein post-translational signaling modifications.

Proper citation: ActiveDriver (RRID:SCR_008104) Copy   

•   Source: SciCrunch Registry

http://edge.oncology.wisc.edu/edge.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. EDGE is a scientific resource for toxicology-related gene expression information. The site contains databases and analyses of gene expression studies following exposure to a variety of chemicals or physiological changes. The ultimate goal of the EDGE is to map transcriptional changes from chemical exposure that will someday be used as a diagnostic fingerprint to predict toxicity as well as provide valuable insights into the basic molecular changes responsible. EDGE gives you the ability to easily answer the following fundamental questions about your data 1. Can I compare transcriptional profiles across treatments? 2. What genes respond to my treatment? 3. What influences my favorite gene(s)? One of the major objectives of toxicology is to understand the adverse health effects that result from exposure to foreign chemicals. The traditional method for assessing the toxicity of a test chemical is very resource intensive; requiring the commitment of large amounts of money, time, and animals. According to the National Toxicology Program (NTP), each chemical study requires between 2 and 4 million dollars and several years to complete. Due to the cost and labor intensive nature of these studies, the number of chemicals currently tested by the NTP stands at less than 500. Given these statistics and the fact that there are approximately 70,000 chemicals in commerce today, it is increasingly apparent that alternative methods for assessing toxic potential must be explored if a significant portion of the remaining chemicals is to be tested. One potential solution is to develop a comprehensive database that describes alterations in gene expression resulting from chemical exposure. The pattern of transcriptional activity will not only be highly sensitive indicator of chemical exposure, but that this pattern will be diagnostic for mechanistically linked toxicants. In our laboratory, we have chosen to address this problem through a combination of high throughput sequencing of expressed sequence tags (ESTs) and construction of custom toxicology-related cDNA microarrays derived from the unique ESTs identified in the sequencing effort. By using this approach, we can simultaneously develop a quantitative gene expression profile using ESTs and the reagents for further analyzing these changes in a rapid, highly parallel manner. In addition, the expression profiles are not biased for preselected favorite genes. The resulting gene expression pattern can then be used as diagnostic fingerprint to predict toxicity and/or carcinogenicity as well as provide valuable insight into the basic biochemical and molecular changes responsible for toxicity. Submission of total RNA for Bradfield Lab Microarray Microarray comparisons are made between untreated, control animals and animals treated with ONE treatment. Please make sure the RNA submitted adheres to this experimental design. Necessary information is available on the site.

Proper citation: EDGE: Environment, Drugs and Gene Expression (RRID:SCR_008187) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/fm/FME/index.html

The Foundational Model Explorer (FME) is an internet based software application developed for viewing the content and organization of the Foundational Model of Anatomy Ontology (FMA). The initial purpose of the FME was to provide a simple and intuitive interface to the FMA for domain experts, in the field of anatomy, participating in the evaluation of the FMA. The FME also provides an easily available method of exploring the FMA to individuals or groups considering the adoption of the Foundational Model of Anatomy knowledge base. The FME display consists of two panes: a hierarchical tree may be opened up in the pane on the left side; if a class is selected in the hierarchical tree, the pane on the right side displays the information that has been entered in the FMA for that class. The information associated with a given class is organized in so-called slots. Each slot has a name (e.g., Definition, Parts) and some content, which is that particular slots value (e.g., the English definition and the names of parts of the selected class, respectively). For an explanation of the interactive features of the FME, see the Knowledge Navigation Section. For a guided tutorial check out the Conducted Tour. In the left pane, the default tree is a subclass hierarchy, based on the -is a- or -kind of- relationship; it is the instantiation of the Anatomy taxonomy (At) component in the high level scheme of the Foundational Model of Anatomy. Apart from the slots Preferred Name and Synonyms, other slots relate to the Anatomical Structural Abstraction (ASA) component in the FMAs high level scheme. Hierarchies based on various part-whole relationships can also be opened up in the left pane. Once a class has been highlighted in the subclass hierarchy, you can choose a relationship from a drop down list labeled Select navigation tree type. Some other transitive relationships (e.g., -branch of- and -tributary of-) are also available. The Search facility matches a search term to the preferred name, as well as to the Latin name, or synonym of an FMA class (if such exist). The tree is expanded to reveal the matching class and the information about this class is displayed. The wildcard * is allowed in the search term and will match to any sequence of characters. For example the search term h*d matches the class names Head and Hepatic cord (amongst others). The search function is not case sensitive. If more than one class name matches with the search term, a list of matching terms is presented for the user to choose between.

Proper citation: Foundational Model Explorer (RRID:SCR_008189) Copy   

•   Source: SciCrunch Registry

http://genewindow.nci.nih.gov/

Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible

Proper citation: GeneWindow (RRID:SCR_008183) Copy   

•   Source: SciCrunch Registry

http://www.utsa.edu/claibornelab/

The long-term goals of my research are to understand the relationship between neuronal structure and function, and to elucidate the factors that affect neuronal morphology and function over the lifespan of the mammal. Currently we are examining 1) the effects of synaptic activity on neuronal development; 2) the effects of estrogen on neuronal morphology and on learning and memory; and, 3) the effects of aging on neuronal structure and function. We have focused our efforts on single neurons in the hippocampal formation, a region that is critical for certain forms of learning and memory in rodents and humans. From the portal, you may click on a cell in your region of interest to see the complete database of cells from that region. You may also explore the Neuron Database: * Comparative Electrotonic Analysis of Three Classes of Rat Hippocampal Neurons. (Raw data available) * Quantitative, three-dimensional analysis of granule cell dendrites in the rat dentate gyrus. * Dendritic Growth and Regression in Rat Dentate Granule Cells During Late Postnatal Development.(Raw data available) * A light and electron microscopic analysis of the mossy fibers of the rat dentate gyrus.

Proper citation: University of Texas at San Antonio Laboratory of Professor Brenda Claiborne (RRID:SCR_008064) Copy   

•   Source: SciCrunch Registry

http://www.cambridgesoft.com/databases/login/?serviceid=128

THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. ChemBioFinder.com is an online chemistry and biology reference database. With more than 500,000 compounds indexed and linked to other web sites, it provides a wealth of chemical information for professional chemists and students alike. ChemBioFinder.com is the gateway to all databases available from CambridgeSoft.
At ChemBioFinder.com, a subscriber can search for compounds by name, CAS Registry Number, molecular formula or weight, or by structure (exact and substructure). Successful searches return a basic profile of molecules indexed by this site. The profile contains the name, molecular formula and weight, CAS Registry Number, SMILES and InChI strings for each located compound, and lists the databases which contain entries for the located compound(s). Free trials to any of these databases are available, as are annual subscriptions for continuous use of the contents.
Users of ChemBioFinder.com are allowed 5 free searches before we request them to register with us as a cambridgesoft.com website user. The CambridgeSoft user account is free and will give you access to a growing list of products and services which includes, our quarterly print publication Chem & Bio News, frequent webinars, white papers and articles on all our offerings. Set up is fast & easy.
For ChemFinder.com users:
ChemFinder.Com has become ChemBioFinder.Com and has a whole new look and layout. This is part of a gradual redesign of the entire CambridgeSoft website. Here are some of the changes that were made to improve the vital information presented here to the scientific community:
1. Search results show the ChemBioFinder databases which have entries for the compound(s), and indicate the databases to which the logged in user has active subscriptions.
2. There are hyperlinks to the detailed records in the databases with active subscriptions.
3. Search results provide the name, molecular formula and weight, CAS Registry Number, SMILES and InChI strings for the compound.
4. Physical properties are no longer provided unless the user has a subscription to ChemIndex or other CambridgeSoft online databases that provide this information. Many of our products come with one year subscriptions to ChemIndex as part of the package. So you may actually be entitled to a subscription and dont realize it.

Proper citation: ChemBioFinder (RRID:SCR_008180) Copy   

•   Source: SciCrunch Registry

http://www.hopkins-abxguide.org/

Concise, clinically useful information for diagnosing, managing and treating infectious diseases in adults; however it does cover some pediatric topics including vaccines. It is designed for primary care providers and other non-infectious disease specialists as a tool that can be used at the point of care to assist in prescribing antibiotics.

Proper citation: ABX Guide (RRID:SCR_008214) Copy   

•   Source: SciCrunch Registry

http://nsdl.org/

NSDL is a digital library of exemplary resource collections and services, organized in support of science education at all levels. Starting with a partnership of NSDL-funded projects, NSDL is emerging as a center of innovation in digital libraries as applied to education, and a community center for groups focused on digital-library-enabled science education. The National Science Digital Library (NSDL) was created by the National Science Foundation to provide organized access to high quality resources and tools that support innovations in teaching and learning at all levels of science, technology, engineering, and mathematics (STEM) education. As a national network of learning environments, resources, and partnerships, NSDL seeks to serve a vital role as STEM educational cyberlearning for the nation, meeting the informational and technological needs of educators and learners at all levels. Educators need efficient and reliable methods to discover and use science and math materials that help them meet the demands of instruction, assessment, and professional development in an increasingly complex technology-based world. NSDL provides an organized point of access to: -High-quality STEM content aggregated from a variety of other digital libraries, NSF-funded projects, and NSDL-reviewed web sites. -Services and tools that enhance the use of this content in a variety of contexts. NSDL is designed primarily for K-16 educators, but anyone can access NSDL.org and search the library at no cost. Access to most resources discovered through NSDL is free; however, some content providers may require a login, or a nominal fee or subscription to retrieve their specific resources. NSDL serves as a nexus for educators, researchers, policy makers and the public by building bridges: -Between private sector and public interests by providing access to resources such as publisher'' journal articles, teacher-created lesson plans and real-time data sets from scientists -Between the scientific, research and educational communities by applying advanced technologies to stimulate new ways for educators and learners to access and use scientific information -Between teachers and learners at all levels, in all locations by supplying content and tools in open-access, non-proprietary formats in an easily accessible online environment. Sponsors: This work supported by the National Science Foundation under Grant No. 0733600, Grant No. 0424671, Grant No. 0227648, Grant No. 0227656, and Grant No. 0227888.

Proper citation: NSDL: The National Science Digital Library (RRID:SCR_008215) Copy   

•   Source: SciCrunch Registry