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http://predictsite.com

Patient database that contains EEG data sets, executable tasks, and computational tools., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PREDiCT (RRID:SCR_015517) Copy   

•   Source: SciCrunch Registry

http://www.apa.org/pubs/databases/psycinfo/

Database for published, indexed resources pertaining to psychological, psychiatric and other behavioral and social science research. Users can search for resources by document type, research methodology, and funding source.

Proper citation: PsycINFO (RRID:SCR_014799) Copy   

•   Source: SciCrunch Registry

http://www.massbank.jp/?lang=en

Public repository of mass spectral data which allows users to search similar spectra on a peak-to-peak basis, on a neutral loss-to-neutral loss basis, or by the m/z value and molecular formula, search chemical compounds by substructures, and keyword search chemical compounds

Proper citation: MassBank (RRID:SCR_015535) Copy   

•   Source: SciCrunch Registry

http://www.lncrnadb.org/

Searchable database of comprehensive annotations of eukaryotic long non-coding RNAs. Entries are manually curated from referenced literature.

Proper citation: lncRNAdb (RRID:SCR_015491) Copy   

•   Source: SciCrunch Registry

http://www.novusbio.com/

Commercial antibody vendor which supplies antibodies and other products to life science researchers.

Proper citation: Novus Biologicals (RRID:SCR_004286) Copy   

•   Source: SciCrunch Registry

http://pipeline.lbl.gov/cgi-bin/gateway2

Software tools for comparative genomics.Comprehensive suite of programs and databases for comparative analysis of genomic sequences. There are two ways of using VISTA - you can submit your own sequences and alignments for analysis (VISTA servers) or examine pre-computed whole-genome alignments of different species.

Proper citation: VISTA Browser (RRID:SCR_011808) Copy   

•   Source: SciCrunch Registry

http://zork.wustl.edu/niaaa/

A multi-site, multi-disciplinary undertaking with the overall goals of characterizing the familial transmission of alcoholism and related phenotypes and identifying susceptibility genes using genetic linkage. The study is being coordinated by the SUNY Health Science Center at Brooklyn (HSCB) under the leadership of Henri Begleiter. The study was initially funded by the National Institute of Alcohol Abuse and Alcoholism (NIAAA) in 1989. Additional useful information at http://www.niaaa.nih.gov/ResearchInformation/ExtramuralResearch/SharedResources/projcoga.htm

Proper citation: Collaborative Study on the Genetics of Alcoholism (RRID:SCR_013395) Copy   

•   Source: SciCrunch Registry

https://github.com/ncbi/pgap

Software tool as NCBI prokaryotic genome annotation pipeline. Used to annotate both complete genomes and draft genomes comprising multiple contigs. Integrated into NCBI infrastructure and processes, and uses modular software framework, GPipe, developed at NCBI for execution of all annotation tasks, from fetching of raw and curated data from public repositories through sequence alignment and model based gene prediction, to submission of annotated genomic data to public NCBI databases.

Proper citation: Prokaryotic Genomes Automatic Annotation Pipeline (RRID:SCR_021329) Copy   

•   Source: SciCrunch Registry

http://www.hdbr.org/

Collection of human embryonic and fetal material (Tissue and RNA) ranging from 3 to 20 weeks of development available to the international scientific community. Material can either be sent to registered users or our In House Gene Expression Service (IHGES) can carry out projects on user''''s behalf, providing high quality images and interpretation of gene expression patterns. Gene expression data emerging from HDBR material is added to our gene expression database which is accessible via our HUDSEN (Human Developmental Studies Network) website. A significant proportion of the material has been cytogenetically karyotyped, and normal karyotyped material is provided for research.

Proper citation: Human Developmental Biology Resource (RRID:SCR_006326) Copy   

•   Source: SciCrunch Registry

http://www.ppmi-info.org/

An observational longitudinal clinical study partnership to identify and validate biomarkers of Parkinson disease (PD) progression and provide easy and open web-based access to the comprehensive set of correlated clinical data and biospecimens, information, and biosamples acquired from PD and age and gender matched healthy control subjects to the research community. The data and specimens have been collected in a standardized manner under strict protocols and includes clinical (demographic, motor and non-motor, cognitive and neurobehavioral), imaging (raw and processed MRI, SPECT and DAT), and blood chemistry and hematology subject assessments and biospecimen inventories (serum, plasma, whole blood, CSF, DNA, RNA and urine). All data are de-identified to protect patient privacy. PPMI will be carried out over five years at 21 clinical sites in the United States and Europe and requires the participation of 400 Parkinson's patients and 200 control participants. The PPMI database provides researchers with access to correlated clinical and imaging data, along with annotated biospecimens, all available within an open access system that encourages data sharing (http://www.ppmi-info.org/access-data-specimens/). The website hosts an Ongoing Analysis section to keep the scientific community apprised of analyses being completed, in hopes of stimulating collaborations between researchers who are using PPMI data and specimens.

Proper citation: Parkinson's Progression Markers Initiative (RRID:SCR_006431) Copy   

•   Source: SciCrunch Registry

http://www.framinghamheartstudy.org/

A longitudinal, epidemiologic study to identify the common risk factors or characteristics that contribute to cardiovascular disease by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms or suffered a heart attack or stroke. Since that time the FHS has studied three generations of participants resulting in biological specimens and data from nearly 15,000 participants. Since 1994, two groups from minority populations, including related individuals have been added to the FHS. FHS welcomes proposals from outside investigators for data and biospecimens. The researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have continued to return to the study every two years for a detailed medical history, physical examination, and laboratory tests, and in 1971, the Study enrolled a second generation - 5,124 of the original participants'''' adult children and their spouses - to participate in similar examinations. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study was enrolled. In April 2002 the Study entered a new phase, the enrollment of a third generation of participants, the grandchildren of the Original Cohort. In 2003, a second group of Omni participants was enrolled. Over the years, careful monitoring of the Framingham Study population has led to the identification of major CVD risk factors, as well as valuable information on the effects of these factors such as blood pressure, blood triglyceride and cholesterol levels, age, gender, and psychosocial issues. Risk factors for other physiological conditions such as dementia have been and continue to be investigated. In addition, the relationships between physical traits and genetic patterns are being studied. FHS clinical and research data is stored in the dbGaP and NHLBI Repository repositories and may be accessed by application. Please check the following repositories before applying for data through FHS. Investigators seeking data that is not available through dbGaP or BioLINCC or seeking biological specimens may submit a proposal through the FHS web-based research application. The FHS data repository may be accessed through this FHS website, under the For Researchers link, then Description of Data, in order to determine if and how the desired data is stored. Proposals may involve the use of existing data, the collection of new data, either directly from participants or from previously collected samples, images, or other materials (e.g., medical records). The FHS Repository also has biological specimens available for genetic and non-genetic research proposals. Specimens include urine, blood and blood products, as well as DNA.

Proper citation: Framingham Heart Study (RRID:SCR_008963) Copy   

•   Source: SciCrunch Registry

http://promedmail.org/

Program for Monitoring Emerging Diseases - is an Internet-based reporting system dedicated to rapid global dissemination of information on outbreaks of infectious diseases and acute exposures to toxins that affect human health, including those in animals and in plants grown for food or animal feed. Electronic communications enable ProMED-mail to provide up-to-date and reliable news about threats to human, animal, and food plant health around the world, seven days a week. By providing early warning of outbreaks of emerging and re-emerging diseases, public health precautions at all levels can be taken in a timely manner to prevent epidemic transmission and to save lives. ProMED-mail is open to all sources and free of political constraints. Sources of information include media reports, official reports, online summaries, local observers, and others. Reports are often contributed by ProMED-mail subscribers. A team of expert human, plant, and animal disease moderators screen, review, and investigate reports before posting to the network. Reports are distributed by email to direct subscribers and posted immediately on the ProMED-mail web site. ProMED-mail currently reaches over 60,000 subscribers in at least 185 countries. ProMED collaborates closely with HealthMap at Children''s Hospital Boston. We also gratefully acknowledge HealthMap for providing Website and hosting services to ProMED.

Proper citation: ProMed-Mail (RRID:SCR_010260) Copy   

•   Source: SciCrunch Registry

http://pyro.cme.msu.edu/

Software to simplify the processing of large rRNA sequence libraries (including single-strand and paired-end reads) obtained through high-throughput sequencing technology. Tools for assembly, quality filtering, taxonomy based analysis and taxonomy independent analysis tools, and tools to convert the data to formats suitable for common ecological and statistical packages are available. For extremely large datasets, command line tools are available.

Proper citation: RDPipeline (RRID:SCR_001192) Copy   

•   Source: SciCrunch Registry

http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/strap/

Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed. Platform: Windows compatible

Proper citation: STRAP (RRID:SCR_005675) Copy   

•   Source: SciCrunch Registry

http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   

•   Source: SciCrunch Registry

http://www.hgsc.bcm.tmc.edu/

Center for high-throughput DNA sequence generation and the accompanying analysis. The sequence data generated by the center's machines are analyzed in a complex bioinformatics pipeline, and the data are deposited regularly in the public databases at the National Center for Biotechnology Information (NCBI).

Proper citation: Baylor College of Medicine Human Genome Sequencing Center (RRID:SCR_013605) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/ExaML

Source code for large-scale phylogenetic analyses on whole-transcriptome and whole-genome alignments using supercomputers.

Proper citation: Examl (RRID:SCR_016087) Copy   

•   Source: SciCrunch Registry

http://gmod.org/wiki/Apollo

A standalone Java application with a GUI (graphical user interface) for editing genome annotations. Like GBrowse, it allows users to scroll and zoom in on areas of interest in a sequence; authorized users can edit annotations and write the changes back to the underlying database. Apollo can run off GFF3 or a Chado database, and it can also integrate with remote services, such as BLAST and Primer BLAST analyses.

Proper citation: Apollo (RRID:SCR_001936) Copy   

•   Source: SciCrunch Registry

http://genapha.icapture.ubc.ca/PathTutorial/

Web application to investigate gene-gene interactions in genetic association studies designed to: 1. Interface your SNP data with biological information from several online bioinformatics databases. 2. Generate biologically plausible hypotheses for testing gene-gene interactions. 3. Select a subset of SNPs and conduct SNP-SNP interaction tests. 4. Store analysis results. 5. Explore analysis results through interactive plots and summary tables. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PATH (RRID:SCR_009042) Copy   

•   Source: SciCrunch Registry