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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   

•   Source: SciCrunch Registry

http://www.genomatix.de/

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://www.biodas.org

The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.

Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy   

•   Source: SciCrunch Registry

https://www.stat.auckland.ac.nz/~paul/plaudits/Iobion.htm

GeneTraffic is a web-based microarray data analysis and management software developed by Iobion Informatics that allows users to log onto a server, upload their microarray data and perform analysis and project management remotely. GeneTraffic was made by Iobion Informatics (now under Stratagene) and can be accessed thorough Internet Explorer 6.0 or greater on Windows XP.

Proper citation: GeneTraffic (RRID:SCR_008651) Copy   

•   Source: SciCrunch Registry

http://apid.dep.usal.es

APID Interactomes (Agile Protein Interactomes DataServer) provides information on the protein interactomes of numerous organisms, based on the integration of known experimentally validated protein-protein physical interactions (PPIs). The interactome data includes a report on quality levels and coverage over the proteomes for each organism included. APID integrates PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. This collection references protein interactors, through a UniProt identifier.

Proper citation: Agile Protein Interactomes DataServer (RRID:SCR_008871) Copy   

•   Source: SciCrunch Registry

http://www.g-node.org/data

Platform for sharing data, with very large storage capability for electrophysiological data, EEG data is included. This service is provided for neuroscientists to facilitate data access, data storage, data analysis and data sharing. This service is developed and maintained by the German Node of the International Neuroinformatics Coordinating Facility. The global scale of neuroinformatics offers unprecedented opportunities for scientific collaborations between and among experimental and theoretical neuroscientists. To fully harvest these possibilities, coordinated activities are required to improve key ingredients of neuroscience: data access, data storage, and data analysis, together with supporting activities for teaching and training. Focusing on the development and free distribution of tools for handling and analyzing neurophysiological data, G-Node aims at addressing these aspects as part of the International Neuroinformatics Coordination Facility (INCF) and the German Bernstein Network for Computational Neuroscience (NNCN). G-Node also serves as an international forum for Computational Neuroscientists that are interested in sharing experimental data and tools for data analysis and modeling. G-Node is funded through the German Federal Ministry of Education and Research and hosted by Ludwig-Maximilians-Universit-Munchen.

Proper citation: G-node portal electrophysiology data sharing (RRID:SCR_008893) Copy   

•   Source: SciCrunch Registry

http://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

•   Source: SciCrunch Registry

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

Tool to assist site staff with curation of data dictionary, data item, and subject item files for preparation to uploading and sharing data with DbGaP resource.

Proper citation: DbGaP Cleaner (RRID:SCR_009462) Copy   

•   Source: SciCrunch Registry

http://databrary.org/

Project aims to promote data sharing, archiving, and reuse among researchers who study human development. Focuses on creating tools for scientists to store, manage, preserve, analyze and share video and related data.

Proper citation: Databrary (RRID:SCR_010471) Copy   

•   Source: SciCrunch Registry

http://www.arrayserver.com/wiki/index.php?title=ArrayStudio_Online_Help

Software package which provides statistics and visualization for analysis of high dimensional quantification data including microarray or RTPCR data or Taqman data, genotype data including SNP or Copy Number data and Next Generation Sequencing data. Provides integrated environment for analyzing and visualizing high dimensional data.

Proper citation: Array Studio (RRID:SCR_010970) Copy   

•   Source: SciCrunch Registry

http://bioinf.wehi.edu.au/limma/

Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

Proper citation: LIMMA (RRID:SCR_010943) Copy   

•   Source: SciCrunch Registry

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

Support and community integration for the enhanced NITRC services of the Image Repository (IR) and the Computational Environment (CE). The NITRC Computational Environment, an on-demand, cloud based computational virtual machine pre-installed with popular NITRC neuroimaging tools built using NeuroDebian. NITRC Image Repository is built upon XNAT and supports both NIfTI and DICOM images. The NITRC-IR offers 3,733 Subjects, and 3,743 Imaging Sessions searchable across seven projects to promote re-use and integration of valuable NIH-funded data.

Proper citation: NITRC Enhanced Services (RRID:SCR_002494) Copy   

•   Source: SciCrunch Registry

http://www.fmrib.ox.ac.uk/fsl/

Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.

Proper citation: FSL (RRID:SCR_002823) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/arrayexpress/

International functional genomics data collection generated from microarray or next-generation sequencing (NGS) platforms. Repository of functional genomics data supporting publications. Provides genes expression data for reuse to the research community where they can be queried and downloaded. Integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Contains a subset of curated and re-annotated Archive data which can be queried for individual gene expression under different biological conditions across experiments. Data collected to MIAME and MINSEQE standards. Data are submitted by users or are imported directly from the NCBI Gene Expression Omnibus.

Proper citation: ArrayExpress (RRID:SCR_002964) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/

Community portal for researchers and content management system for data and databases. Intended to provide common source of data to research community and data about Research Resource Identifiers (RRIDs), which can be used in scientific publications. Central service where RRIDs can be searched and created. Designed to help communities of researchers create their own portals to provide access to resources, databases and tools of relevance to their research areas. Adds value to existing scientific resources by increasing their discoverability, accessibility, visibility, utility and interoperability, regardless of their current design or capabilities and without need for extensive redesign of their components or information models. Resources can be searched and discovered at multiple levels of integration, from superficial discovery based on limited description of resource at SciCrunch Registry, to deep content query at SciCrunch Data Federation.

Proper citation: SciCrunch (RRID:SCR_003115) Copy   

•   Source: SciCrunch Registry

http://developingmouse.brain-map.org/

Map of gene expression in developing mouse brain revealing gene expression patterns from embryonic through postnatal stages. Provides information about spatial and temporal regulation of gene expression with database. Feature include seven sagittal reference atlases created with a developmental ontology. These anatomic atlases may be viewed alongside in situ hybridization (ISH) data as well as by itself.

Proper citation: Allen Developing Mouse Brain Atlas (RRID:SCR_002990) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/index.html

MIALAB, headed by Dr. Vince Calhoun, focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data. Much of our time is spent working on new methods for flexible analysis of brain imaging data. The use of data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. To this end, we draw heavily from the areas of image processing, adaptive signal processing, estimation theory, neural networks, statistical signal processing, and pattern recognition.

Proper citation: MIALAB - Medical Image Analysis Lab (RRID:SCR_006089) Copy   

•   Source: SciCrunch Registry

http://www.chemspider.com/

Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.

Proper citation: ChemSpider (RRID:SCR_006360) Copy   

•   Source: SciCrunch Registry

https://proteomecommons.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A public resource for sharing general proteomics information including data (Tranche repository), tools, and news. Joining or creating a group/project provides tools and standards for collaboration, project management, data annotation, permissions, permanent storage, and publication.

Proper citation: Proteome Commons (RRID:SCR_006234) Copy   

•   Source: SciCrunch Registry