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https://github.com/ElementoLab/ChIPseeqer

Software that provides a comprehensive framework for the analysis of ChIP-seq data.

Proper citation: ChIPseeqer (RRID:SCR_001545) Copy   

•   Source: SciCrunch Registry

http://mobile.ebiocenter.com/ebionews/

eBioNews specializes in online information services and resource exchanges in the fields of life sciences and biotechnology. By applying its knowledge database and content management system (CMS), eBioNews offers readers and customers the organized and comprehensive information. eBioNews also provides a membership-based service to assist our customers in information and data search, processing, storage, and sharing. Generally, eBioNews covers the following areas: - life science frontiers - news and discussions - features and specials - resources and sourcing - career development - academic and industry - training and education Additionally, eBioNews information is organized into the following two clusters: - News Center: 1. Headlights 2. Research Frontiers 3. General Research 4. Clinical Development 5. Enterprise & Industry 6. Products & Services 7. Investment & Financials 8. Features 9. Newsletter The News Center consists of the elements and mechanisms that enable collecting, organizing, displaying, and delivering life science related information, data, and knowledge. - Resource Center: 1. eBioResources 2. Cooperation 3. Events 4. Human Resources 5. Intellectual Property 6. Finance & Legal 7. Operations 8. Organization 9. Publication The Resource Center is a system that hosts and facilitates the resource-related information between and among multiple parties, especially for promoting cooperation, collaboration, consortium, partnering, joint venture, licensing, out-sourcing, and trading. Sponsors: This resource is supported by eBioCenter Corporation.

Proper citation: eBioNews - A Subsidiary of eBioCenter (RRID:SCR_001717) Copy   

•   Source: SciCrunch Registry

http://neuroimage.usc.edu/brainstorm/

Software as collaborative, open source application dedicated to analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. User-Friendly Application for MEG/EEG Analysis.

Proper citation: Brainstorm (RRID:SCR_001761) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/itk-snap/

Open source interactive software application for three dimentional medical images, manual delineation of anatomical regions of interest, and performing automatic image segmentation. Used for delineating anatomical structures and regions in MRI, CT and other 3D biomedical imaging data.WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non axis-aligned) cross-sectional views of volumetric data, as well as 3-D meshes and line-segment based models (skeletons).

Proper citation: ITK-SNAP (RRID:SCR_002010) Copy   

•   Source: SciCrunch Registry

https://datashare.nida.nih.gov

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

Proper citation: NIDA Data Share (RRID:SCR_002002) Copy   

•   Source: SciCrunch Registry

http://connectomics.org/viewer

Extensible, scriptable, pythonic software tool for visualization and analysis in structural neuroimaging research on many spatial scales. Employing the Connectome File Format, diverse data such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The field of Connectomics research benefits from recent advances in structural neuroimaging technologies on all spatial scales. The need for software tools to visualize and analyze the emerging data is urgent. The ConnectomeViewer application was developed to meet the needs of basic and clinical neuroscientists, as well as complex network scientists, providing an integrative, extensible platform to visualize and analyze Connectomics data. With the Connectome File Format, interlinking different datatypes such as hierarchical networks, surface data, volumetric data is easy and might provide new ways of analyzing and interacting with data. Furthermore, ConnectomeViewer readily integrates with: * ConnectomeWiki: a semantic knowledge base representing connectomics data at a mesoscale level across various species, allowing easy access to relevant literature and databases. * ConnectomeDatabase: a repository to store and disseminate Connectome files.

Proper citation: ConnectomeViewer: Multi-Modal Multi-Level Network Visualization and Analysis (RRID:SCR_008312) Copy   

•   Source: SciCrunch Registry

http://www.biobankcentral.org/resource/wwibb.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 27, 2013. Web-based portal to connect all the constituencies in the global biobank community. The project seeks to increase the transparency and accessibility of the scientific research process by connecting researchers with an additional source of funding - microinvestments received from the broader online community. In exchange for these public investments, researchers will maintain research logs detailing the play-by-play progress made in their project, as well as publishing all of their data in a public database under a science commons license. These research projects, in turn, will serve to continually update a research-based neuroscience-based human brain & body curriculum. Biobanks are the meeting point of two major information trends in biomedical research: the generation of huge amounts of genomic and other laboratory data, and the electronic capture and integration of patient clinical records. They are comprised of large numbers of human biospecimens supplemented with clinical data. Biobanks when implemented effectively can harness the power of both genomic and clinical data and serve as a critical bridge between basic and applied research, linking laboratory to patient and getting to cures faster. As science and technology leaders work to address the many challenges facing U.S. biobanks logistical, technical, ethical, financial, intellectual property, and IT BioBank Central will serve as an accurate and timely source of knowledge and news about biorepositories and their role in research and drug development. The Web site also provides a working group venue, patient and public education programs, and a forum for international collaboration and harmonization of best practices.

Proper citation: BioBank Central (RRID:SCR_008645) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/cancer/software/genecluster2/gc2.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding supervised classification, gene selection, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting (WV) and k-nearest neighbor (KNN) algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. It enhances the clustering capabilities of GeneCluster 1.0 by adding a module for batch SOM clustering, and also includes a marker gene finder based on a KNN analysis and a visualization module. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.

Proper citation: GeneCluster 2: An Advanced Toolset for Bioarray Analysis (RRID:SCR_008446) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

•   Source: SciCrunch Registry

http://www.blogmydata.org/

Software tool for data sharing, incorporating blogs and spatial registration of data. Mainly used in geological data sets. A Virtual Research Environment (VRE) aims to combine the capabilities of two existing technologies that have already seen wide adoption among scientists: - The Godiva2 data visualization system provides a means for scientists to browse interactively in a ''Google Maps-like'' fashion through large environmental datasets, including numerical model outputs and high-resolution satellite imagery, using only a web browser. - The LabBlog is a web-based blogging tool specifically designed for the practising scientist to record, disseminate and evaluate their research. The Blog can also be used as a collaboration tool that allows secure discussion between colleagues. Although initially designed for the use of laboratory chemists, the LabBlog is being adapted in this project to meet the needs of environmental scientists. The BlogMyData VRE will allow scientists to explore data visually using Godiva2, then make comments about features in the data on a blog. Colleagues will discover these blog entries and offer further information, providing answers to research questions through comments. Through RSS and GeoRSS feeds, colleagues, investigators and other interested parties can be notified of research activity, and scientists can discover hitherto-unknown colleagues working with similar data in similar geographic regions. Sponsors: BlogMyData is a collaboration between the Reading e-Science Centre and the University of Southampton and is one of the JISC VRERI projects.

Proper citation: BlogMyData (RRID:SCR_008697) Copy   

•   Source: SciCrunch Registry

http://neuro-information.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The International Observatory on Neuro-Information is the central source of knowledge, research and data on all skills and issues for Neuroscience applied in Information Sciences. It is an initiative of the Documentation Sciences Foundation, from Spain, which aims to gather information, express opinions, prepare documents, make comparative research, support and promote policy-making, evaluate trends, and take other appropriate action relating to the Neuroscience and its application to the Information Sciences (Libraries, Archives, Documentation centers), and how the traditional knowledge of Information Sciences can bring expertise in data visualization and retrieval techniques, records management, quality assurance and usability in Neuroscience. The Observatory may work together, or in agreement with other national or international organizations pursuing similar or compatible aims.

Proper citation: International Observatory on Neuro-Information (RRID:SCR_008690) Copy   

•   Source: SciCrunch Registry

https://www.brainproducts.com/

Commercial organization for hardware and software for neurophysiological research. Provides EEG and ERP amplifier systems, EEG recording caps, Data recording and analysis software, TMS Stimulator for combined EEG/TMS coregistrations and more.

Proper citation: Brain Products (RRID:SCR_009443) Copy   

•   Source: SciCrunch Registry

http://wbiomed.curtin.edu.au/genepop/

Population genetic data analysis software package. Used to perform exact Hardy Weinberg Equilibrium test. Used for population differentiation and for genotypic disequilibrium among pairs of loci. Computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc. and performs analyses of isolation by distance from pairwise comparisons of individuals or population samples., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GENEPOP (RRID:SCR_009194) Copy   

•   Source: SciCrunch Registry

https://www.mdc-berlin.de/8551903/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep

Software tool to identify known and novel miRNA genes in seven animal clades by analyzing sequenced RNAs. Used for discovering known and novel miRNAs from small RNA sequencing data.

Proper citation: miRDeep (RRID:SCR_010829) Copy   

•   Source: SciCrunch Registry

http://eupathdb.org/eupathdb/

EuPathDB integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises veterinary and medically important parasitic protozoa including human pathogenic species of genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as database but unifies access to three major existing individual organism databases, PlasmoDB.org, ToxoDB.org and CryptoDB.org, and integrates these databases with data available from additional sources. Through ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases. EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with eukaryotic pathogens.

Proper citation: Eukaryotic Pathogen Database Resources (RRID:SCR_004512) Copy   

•   Source: SciCrunch Registry

http://alt.kompetenznetz-parkinson.de/englisch/englisch.html

A medical network comprised of university clinics, special clinics, and special practices working together to collect data, gene samples, and execute clinical trials in order to bring about diagnoses and therapy methods. Research projects are done in cure research, diagnostic and therapeutic research. The care network includes university clinics, town clinics, special clinics for Parkinson's disease, specialists, and general practitioners.

Proper citation: Competence Network on Parkinson's Disease (RRID:SCR_005013) Copy   

•   Source: SciCrunch Registry

https://www.fieldtriptoolbox.org

Software toolbox for analysis of MEG, EEG, and other electrophysiological data. Used by experimental neuroscientists.

Proper citation: FieldTrip (RRID:SCR_004849) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

•   Source: SciCrunch Registry

https://www.immport.org/home

Data sharing repository of clinical trials, associated mechanistic studies, and other basic and applied immunology research programs. Platform to store, analyze, and exchange datasets for immune mediated diseases. Data supplied by NIAID/DAIT funded investigators and genomic, proteomic, and other data relevant to research of these programs extracted from public databases. Provides data analysis tools and immunology focused ontology to advance research in basic and clinical immunology.

Proper citation: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804) Copy   

•   Source: SciCrunch Registry

http://web.bioinformatics.ic.ac.uk/eqtlexplorer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. eQTL Explorer was developed as a computational resource to visualize and explore data from combined genome-wide expression and linkage studies is essential for the development of testable hypotheses. This visualization tool stores expression profiles, linkage data and information from external sources in a relational database and enables simultaneous visualization and intuitive interpretation of the combined data via a Java graphical interface. eQTL Explorer also provides a new and powerful tool to interrogate these very large and complex datasets. eQTLexplorer allows users to mine and understand data from a repository of genetical genomics experiments. It will graphically display eQTL information based on a certain number of selection criteria, including: tissue type, p-value, cis/trans, probeset Affymetrix id and PQTL type. Sponsors: This work was funded by the MRC Clinical Sciences Centre and the Wellcome Trust programme for Cardiovascular Functional Genomics.

Proper citation: eQTL Visualization Tool (RRID:SCR_013413) Copy   

•   Source: SciCrunch Registry