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Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.
Proper citation: Community Structure-Activity Resource (RRID:SCR_002206) Copy
The primary climate-change data and information analysis center of the U.S. Department of Energy (DOE) and includes the World Data Center for Atmospheric Trace Gases, serving the climate change-related data and information needs of users worldwide. CDIAC''s data holdings include estimates of carbon dioxide emissions from fossil-fuel consumption and land-use changes; records of atmospheric concentrations of carbon dioxide and other radiatively active trace gases; carbon cycle and terrestrial carbon management datasets and analyses; and global/regional climate data and time series. CDIAC provides scientific and data management support for projects sponsored by a number of agencies, including the AmeriFlux Network, continuous observations of ecosystem level exchanges of CO2, water, energy and momentum at different time scales for sites in the Americas; the Ocean CO2 Data Program of CO2 measurements taken aboard ocean research vessels; DOE-supported FACE experiments, which evaluate plant and ecosystem response to elevated CO2 concentrations; and the HIPPO project, which is analyzing the atmospheric carbon cycle and greenhouse gas concentrations from pole to pole over the Pacific Ocean. For those wishing to contribute data to the CDIAC data collection, review the guide and then contact one of the CDIAC staff members to discuss further data submission plans. Data providers may submit data in a variety of ways including via email, direct deposit to a secure CDIAC File Transfer Protocol (FTP) server, on transfer media (e.g. CD-ROM), or by having CDIAC mirror a location at the investigator''s institution.
Proper citation: Carbon Dioxide Information Analysis Center (RRID:SCR_006999) Copy
A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.
Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Data sharing platform based on the ISA software suite - including an annotation tool and a database - that holds environmental omic data in standards-compliant format. It uses various approaches to provide new discovery, interoperability and integration opportunities for environmental scientists, including the development of tools, databases, standard and ontologies. The main tool for collecting environmental omics data from researchers is the EnvBase data catalogue. The NEBC Toolbox contains a range of tools developed by NEBC to support environmental researchers. The data include next generation sequencing, microarray and ABI sequencing technologies. ISAconfigurator and ISAcreator ensure that the extensive information relating to environmental sampling is consistently collected by the NERC experimentalists, according to the appropriate MIBBI checklist(s), and then reported centrally to NEBC. A local instance of the BII runs as an internal prototype database that will soon provide public and private access to NERC research projects outputs, as appropriate. In accordance with the NERC Data Policy, and when data sets are declared ready for public release, the NEBC team will use the ISAconverter to perform (combined) submissions to the appropriate public repositories (ENA, or SRA, ArrayExpress and PRIDE) to ensure long term stewardship.
Proper citation: NERC Environmental Bioinformatics Centre (RRID:SCR_000526) Copy
https://www.genome.wisc.edu/tools/asap.htm
Database and web interface developed to store, update and distribute genome sequence data and gene expression data. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments. Use of some of this preliminary data is conditional, and it is the users responsibility to read the data release policy and to verify that any use of specific data obtained through ASAP is consistent with this policy. There are four main routes to viewing the information in ASAP: # a summary page, # a form to query the genome annotations, # a form to query strain collections, and # a form to query the experimental data. Navigational buttons appear on every page allowing users to jump to any of these four points., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: ASAP (RRID:SCR_001849) Copy
Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.
Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy
http://bioinformatics.aecom.yu.edu/index.htm
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Primary informatics resource for joint research efforts of the Albert Einstein College of Medicine and Montefiore Medical Center to facilitate the study and understanding of biological processes, clinical disorders, pathologic abnormalities, and the relationships among them, using a wide variety of informatics techniques, applications, and user training. Their services include: * Collaboration on research design to enable effective data management throughout all phases of a project * Provision of management capability for large volumes of data generated by microarrays and related technologies * Provision and supports a software toolchest for data capture, retrieval, and analysis * Design and implementation of custom interfaces to incorporate existing or separately designed databases into the central data management architecture * Support for data management for the Biorepository, to enhance specimen storage, identification, and linkage with clinical data * Ensuring conformity of data elements and structures to national standards via participation in standards organizations, facilitating intramural and extramural collaboration * Providing individualized support to end-users with bioinformatics training needs * Serving as a bioinformatics liaison to other research institutes and organizations * Providing data management support for clinical research * Providing a common, secure repository for clinical, experimental, and biosample storage data
Proper citation: Einstein-Montefiore ICTR Research Informatics Core (RRID:SCR_003451) Copy
http://projects.tcag.ca/autism/
The Autism Chromosome Rearrangement Database is a collection of hand curated breakpoints and other genomic features, including phenotypes, organized by chromosome, related to autism, taken from publicly available literature: databases and unpublished data. The database welcomes submission of data and comments regarding the database from the research community. The database is continuously updated with information from in-house experimental data as well as data from published research studies.
Proper citation: Autism Chromosome Rearrangement Database: A database of structural variants in autism spectrum disorder (RRID:SCR_006474) Copy
DDMoRe project to develop common standards and tools to allow scientists to share their models. Developed model repository which enables access to curated and shared knowledge for benefit of model informed drug discovery.
Proper citation: DDMoRe (RRID:SCR_003851) Copy
https://www.ebi.ac.uk/pdbe/emdb/empiar/
Public archive for raw electron microscopy image data. Resource for raw 2D electron microscopy images. Used to browse, upload and download raw images to build 3D structure. Provides access to raw data to facilitate methods development and validation. Complements Electron Microscopy Data Bank where 3D volumes are stored, and uses Aspera platform for data transfers.
Proper citation: Electron Microscopy Public Image Archive (RRID:SCR_019237) Copy
https://github.com/ledancs/hFigures
A Javascript library that aims to deliver a starting point for interactive health data visualization. Examples and demos are available on the site. hFigures was built with d3.js and a copy of the library is included in this repository. All rights and license terms apply to the d3.js library accordingly.
Proper citation: hFigures (RRID:SCR_014201) Copy
http://www.mitre.org/news/digest/archives/2002/neuroinformatics.html
This resource''s long-term goal is to develop informatics methodologies and tools that will increase the creativity and productivity of neuroscience investigators, as they work together to use shared human brain mapping data to generate and test ideas far beyond those pursued by the data''s originators. This resource currently has four major projects supporting this goal: * Database tools: The goal of the NeuroServ project is to provide neuroscience researchers with automated information management tools that reduce the effort required to manage, analyze, query, view, and share their imaging data. It currently manages both structural magnetic resonance image (MRI) datasets and diffusion tensor image (DTI) datasets. NeuroServ is fully web-enabled: data entry, query, processing, reporting, and administrative functions are performed by qualified users through a web browser. It can be used as a local laboratory repository, to share data on the web, or to support a large distributed consortium. NeuroServ is based on an industrial-quality query middleware engine MRALD. NeuroServ includes a specialized neuroimaging schema and over 40 custom Java Server Pages supporting data entry, query, and reporting to help manage and explore stored images. NeuroServ is written in Java for platform independence; it also utilizes several open source components * Data sharing: DataQuest is a collaborative forum to facilitate the sharing of neuroimaging data within the neuroscience community. By publishing summaries of existing datasets, DataQuest enables researchers to: # Discover what data is available for collaborative research # Advertise your data to other researchers for potential collaborations # Discover which researchers may have the data you need # Discover which researchers are interested in your data. * Image quality: The approach to assessing the inherent quality of an image is to measure how distorted the image is. Using what are referred to as no-reference or blind metrics, one can measure the degree to which an image is distorted. * Content-based image retrieval: NIRV (NeuroImagery Retrieval & Visualization) is a work environment for advanced querying over imagery. NIRV will have a Java-based front-end for users to issue queries, run processing algorithms, review results, visualize imagery and assess image quality. NIRV interacts with an image repository such as NeuroServ. Users can also register images and will soon be able to filter searches based on image quality.
Proper citation: MITRE Neuroinformatics (RRID:SCR_006508) Copy
Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.
Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy
Web server for macromolecular structure model optimisation and databank of optimised structure models. Focuses on automating final steps of crystallographic process: optimisation of structure model through refinement, rebuilding, and validation. Can automatically optimise most of crystallographic structure models based on input model and diffraction data. Web server works on user provided data, databank has updated versions of Protein Data Bank entries based on original experimental data that were deposited with atomic coordinates in PDB.
Proper citation: PDB-REDO (RRID:SCR_018936) Copy
Clearinghouse and exchange portal for gene variant (mutation) data produced by diagnostics laboratories, offering users a portal through which to announce, discover and acquire a comprehensive listing of observed neutral and disease-causing gene variants in patients and unaffected individuals. Cafe Variome is not a ''''database'''' for the hosting/display/release of data, but a shop window for finding data. As such, it holds only core info for each record, and uses this merely to enable holistic searching across resources. Diagnostics laboratories routinely assess DNA samples from patients with various inherited disorders, and so produce a great wealth of data on the genetic basis of disease. Unfortunately, those data are not usually shared with others. To address this gross deficiency, a novel system has been developed that aims to facilitate the automated transfer of diagnostic laboratory data to the wider community, via an internet based Cafe for routinely exchanging genetic variation data. The flow of research data concerning the genetic basis of health and disease is critical to understanding and developing treatments for a range of genetic diseases. Overall, the project aims to lower the barriers and provide incentives for a willing community to share data, and thereby facilitate the broader exploitation of diagnostic laboratory data. Cafe Variome aims to address the above data flow problems by: # Minimizing the effort required to publish variant data # Ensuring attribution for data creators working in diagnostic laboratories Key elements of the project strategy are: * Data publication will be automated by endowing standard analysis tools used by laboratories with an online data submission function. Submissions will be received by a central Internet depot, which will serve as a place where published datasets are advertised, and subsequently discovered by diverse 3rd parties. * Each dataset will be unambiguously linked with the data submitter''''s identity, and systems devised to facilitate citation of published variant datasets so they can be cited in the literature. Data creators will thus be credited for their contributions. Data submitters can use Cafe Variome to simply announce or publicize their data to the world. To enable this, only core, non-identifiable data is submitted to the central repository, enabling users to search and discover records of interest in the source repository. The data are not automatically handed on to the user (unless intended by the submitters). Hence, the concept is used to deal with the challenge of maximally sharing data whilst fully respecting ethico-legal considerations.
Proper citation: cafe variome (RRID:SCR_006162) Copy
A center that works with the Oregon Alzheimer's Disease Center's Data Core, and collects and stores tissue samples, family history and genotype data of various populations. These include samples and data from subjects from the following sources: OADC clinical studies, the Oregon Brain Aging Study, the Community Brain Donor Program, the Preventing Cognitive Decline with Alternative Therapies program (informally called the Dementia Prevention Study or DPS), the African American Dementia and Aging Project, and the Klamath Exceptional Aging Project. The collected data samples include genomic DNA, lymphoblast cell lines, genome-wide and candidate region SNP marker data, APOE, AD candidate gene markers.
Proper citation: Layton Center Biomarkers and Genetics (RRID:SCR_008824) Copy
http://fgcz-bfabric.uzh.ch/bfabric/
An open infrastructure for managing projects and data in life sciences that allows to store and access experimental data together with its scientific context. The platform connects the data from scientific instruments with data analysis tools, including workflow, annotation, and data visualization support. All public data can be searched and used to carry out inter-experiment analyses. For a fee, B-Fabric Order allows you to order the following analytical services at the FGCZ independent of a User Lab research project: Mass spectrometry, Protein sequencing, peptide sequencing, Amino acid analysis, Chromatography, Electrophoresis.
Proper citation: B-Fabric (RRID:SCR_011827) Copy
Accepts and makes available geochemical, geochronlogical, and petrological data (analytical and synthesis) through this community-driven effort to facilitate the preservation, discovery, access and visualization of data generated. * PetDB holds geochemical data from sub-oceanic igneous and metamorphic rocks generated at mid-ocean ridges including back-arc basins, young seamounts, and old oceanic crust. Data are compiled primarily from the published literature. * SedDB integrates marine and terrestrial sediment geochemical data compiled primarily from the published literature. * Deep Lithosphere Data Set contains geochemical and petrological data from lower crust and upper mantle xenoliths. (more info) * VentDB contains hydrothermal spring geochemistry that hosts and serves the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. * NAVDAT - The Western North American Volcanic and Intrusive Rock Database * Geochron is an application that helps with the onerous task of data management for geochronological and thermochronological studies. * EarthChemPortal is the one-stop-shop for geochemical data that gives users the ability to search federated databases PetDB, NAVDAT, and GEOROC simultaneously, integrated into a common output format. (more info) * The EarthChem Library is a repository for geochemical datasets (analytical data, experimental data, synthesis databases) and other digital resources relevant to the field of geochemistry, contributed by the geochemistry community. * SESAR - System for Earth SAmple Registration
Proper citation: EarthChem (RRID:SCR_002207) Copy
Paleoecology database for plio-pleistocene to holocene fossil data with a centralized structure for interdisciplinary, multiproxy analyses and common tool development; discipline-specific data can also be easily accessed. Data currently include North American Pollen (NAPD) and fossil mammals (FAUNMAP). Other proxies (plant macrofossils, beetles, ostracodes, diatoms, etc.) and geographic areas (Europe, Latin America, etc.) will be added in the near future. Data are derived from sites from the last 5 million years.
Proper citation: Neotoma Paleoecology Database (RRID:SCR_002190) Copy
Accepts and provides access to biogeographic data collected throughout the global oceans. The datasets are integrated so you can search them all seamlessly by species name, higher taxonomic level, geographic area, depth, and time; and then map and find environmental data related to the locations. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
Proper citation: OBIS (RRID:SCR_006933) Copy
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