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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://hollywood.mit.edu/burgelab/rescue-ese/

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing (ESE References). A hybrid computational/experimental method, RESCUE-ESE, was recently developed for identifying sequences with ESE activity. In this approach, specific hexanucleotide sequences are identified as candidate ESEs on the basis that they have both significantly higher frequency of occurrence in exons than in introns and also significantly higher frequency in exons with weak (non-consensus) splice sites than in exons with strong (consensus) splice sites. Representative hexamers from ten different classes of candidate ESEs, together with 6 or 7 bases of flanking sequence context on each side, were introduced into a weak (poorly spliced) exon in a splicing reporter construct. These reporter minigenes were then transfected into cultured cells, where they are transcribed and spliced, and the relative level of inclusion of the test exon was assayed by quantitative (radio-labeled) RT-PCR. Point mutants of these sequences were also analyzed to confirm the precise motifs responsible for ESE activity. The RESCUE-ESE approach identified 238 hexamers as candidate ESEs using a large database of human genes of known exon-intron structure containing over 30,000 nonredudant exons. In more recent analyses by Yeo et al., the RESCUE-ESE approach was utilized to predict hexamers as candidate ESEs in other vertebrate genes, namely, Fugu rubipes, Zebrafish and Mouse. This allows the identification of motifs that are conserved in vertebrates. This web server allows a sequence to be checked for presence of these candidate ESE hexamers.

Proper citation: RESCUE-ESE (RRID:SCR_008496) Copy   

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https://compumedicsneuroscan.com/products/by-name/curry/

Processing software for multimodal neuroimaging centered on combining functional data such as EEG and MEG with imaging data from MRI and CT to optimize source reconstruction. They are now combining Curry's strength with the acquisition and signal processing features of the SCAN software for a comprehensive EEG acquisition, data analysis, source localization and source imaging package.

Proper citation: CURRY (RRID:SCR_009546) Copy   

•   Source: SciCrunch Registry

http://oncokb.org

Precision oncology knowledge base which contains information about the effects and treatment implications of specific cancer gene alterations. OncoKB contains detailed information about specific alterations in 418 cancer genes. Each variant entry contains biological effect, prevalence, prognostic information, and treatment implications. Information is curated from various sources, such as guidelines from the FDA, ClinicalTrials.gov, and scientific literature by a network of clinical fellows, research fellows, and faculty members at Memorial Sloan Kettering Cancer Center.

Proper citation: OncoKB (RRID:SCR_014782) Copy   

•   Source: SciCrunch Registry

http://humanproteomemap.org

Web-based resource that reorganizes mass spectrometry-based proteomics data to explore expressed proteins in fetal tissues/adult tissues/hematopoietic cells obtained from human. All samples used to generate these data were obtained from histologically normal samples.

Proper citation: Human Proteome Map (RRID:SCR_015560) Copy   

•   Source: SciCrunch Registry

http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&type=1

Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible

Proper citation: EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) Copy   

•   Source: SciCrunch Registry

http://www.cbioportal.org/

A portal that provides visualization, analysis and download of large-scale cancer genomics data sets.

Proper citation: cBioPortal (RRID:SCR_014555) Copy   

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http://www.functionalnet.org/humannet/about.html

Database of human protein-encoding genes that is constructed by a modified Bayesian integration of 'omics' data from multiple organisms. Each data type is weighted according to how well it links genes that are known to function together in humans, and each interaction has an associated log-likelihood score (LLS) that measures the probability of an interaction representing a true functional linkage between two genes.

Proper citation: HumanNet (RRID:SCR_016146) Copy   

•   Source: SciCrunch Registry

http://www.lincsproject.org/

Project to create network based understanding of biology by cataloging changes in gene expression and other cellular processes when cells are exposed to genetic and environmental stressors. Program to develop therapies that might restore pathways and networks to their normal states. Has LINCS Data Coordination and Integration Center and six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.

Proper citation: LINCS Project (RRID:SCR_016486) Copy   

•   Source: SciCrunch Registry

http://ftp://ftp.ebi.ac.uk/pub/databases/taxonomy

The taxonomy database of the International Sequence Database Collaboration contains the names of all organisms that are represented in the sequence databases with at least one nucleotide or protein sequence. The database is available via the EBI SRS server of ftp.

Proper citation: Taxonomy (RRID:SCR_004299) Copy   

•   Source: SciCrunch Registry

http://www.ndexbio.org/

Repository where scientists and organizations can share, store, manipulate, and publish biological network data. Users can also run their own copies of NDEx Server software in cases where stored networks must be kept in highly secure environment (such as for HIPAA compliance) or where high application load is incompatible with shared public resource. Open source software system that is part of Cytoscape family. Project of Cytoscape Consortium in conjunction with Ideker lab at UCSD School of Medicine. Public forum where biologists can exchange and publish computable network models in many types and formats. NDEx is based on REST web API which can be accessed by any application, including NDEx website and NDEx Cytoscape App. NDEx networks are assigned stable, globally unique URIs and so can be referenced by publications, by other networks, and by analytic applications.

Proper citation: Network Data Exchange (NDEx) (RRID:SCR_003943) Copy   

•   Source: SciCrunch Registry

http://diyhpl.us/~bryan/irc/protocol-online/protocol-cache/TFSEARCH.html

The TFSEARCH searches highly correlated sequence fragments against TFMATRIX transcription factor binding site profile database in the "TRANSFAC" databases developed at GBF-Braunschweig, Germany. The TFSEARCH program was written by Yutaka Akiyama (Kyoto University, currently at RWCP) in 1995.

Proper citation: TFSEARCH: Searching Transcription Factor Binding Sites (RRID:SCR_004262) Copy   

•   Source: SciCrunch Registry

http://www.mycancergenome.org/

A freely available online personalized cancer medicine knowledge resource for physicians, patients, caregivers and researchers that gives up-to-date information on what mutations make cancers grow and related therapeutic implications, including available clinical trials. It is a one-stop tool that matches tumor mutations to therapies, making information accessible and convenient for busy clinicians.

Proper citation: My Cancer Genome (RRID:SCR_004140) Copy   

•   Source: SciCrunch Registry

http://tools.niehs.nih.gov/polg/

Database that lists all known mutations in the coding region of the POLG gene and describes the associated disease. Human DNA polymerase is composed of two subunits, a 140 kDa catalytic subunit encoded by the POLG on chromosome 15q25, and a 55kDa accessory subunit encoded by the POLG2 gene on chromosome 17q23-24. A number of mutations have been mapped to the gene for the catalytic subunit of DNA polymerase, POLG, and found to be associated with mitochondrial diseases. The nucleotide changes are numbered from the initiation Methionine codon and are based on the cDNA (accession U60325.1) and gene sequence (accession AF497906.1).

Proper citation: Human DNA Polymerase Gamma Mutation Database (RRID:SCR_004722) Copy   

•   Source: SciCrunch Registry

http://salilab.org/modbase

A database of three-dimensional protein models calculated by comparative modeling. ModBase is organized into datasets, which are either available to the public, to the academic community, or to specific users. 20 unique amidohydrolase and 41 unique enolase structures have been determined have been included in the database.

Proper citation: ModBase (RRID:SCR_004642) Copy   

•   Source: SciCrunch Registry

https://www.stanleygenomics.org/

The Stanley Online Genomics Database uses samples from the Stanley Medical Research Institute (SMRI) Brain Bank. These samples were processed and run on gene expression arrays by a variety of researchers in collaboration with the SMRI. These researchers have performed analyses on their respective studies using a range of analytic approaches. All of the genomic data have been aggregated in this online database, and a consistent set of analyses have been applied to each study. Additionally, a comprehensive set of cross-study analyses have been performed. A thorough collection of gene expression summaries are provided, inclusive of patient demographics, disease subclasses, regulated biological pathways, and functional classifications. Raw data is also available to download. The database is derived from two sets of brain samples, the Stanley Array collection and the Stanley Consortium collection. The Stanley Array collection contains 105 patients, and the Stanley Consortium collection contains 60 patients. Multiple genomic studies have been conducted using these brain samples. From these studies, twelve were selected for inclusion in the database on the basis of number of patients studied, genomic platform used, and data quality. The Consortium collection studies have fewer patients but more diversity in brain regions and array platforms, while the Array collection studies are more homogenous. There are tradeoffs, the Consortium results will be more variable, but findings may be more broadly representative. The collections contain brain samples from subjects in four main groups: Bipolar Schizophrenia, Depression, and Controls Brain regions used in the studies include: Broadman Area 6, Broadman Area 8/9, Broadman Area 10, Broadman Area 46, Cerebellum The 12 studies encompass a range of microarray platforms: Affymetrix HG-U95Av2, Affymetrix HG-U133A, Affymetrix HG-U133 2.0+, Codelink Human 20K, Agilent Human I, Custom cDNA Publications based on any of the clinical or genomic data should credit the Stanley Medical Research Institute, as well as any individual SMRI collaborators whose data is being used. Publications which make use of analytic results/methods in the database should additionally cite Dr. Michael Elashoff. Registration is required to access the data.

Proper citation: Stanley Medical Research Institute Online Genomics Database (RRID:SCR_004859) Copy   

•   Source: SciCrunch Registry

http://www.unos.org/

United Network for Organ Sharing (UNOS) is the private, non-profit organization that manages the nation''s organ transplant system under contract with the federal government. UNOS is involved in many aspects of the organ transplant and donation process: * Managing the national transplant waiting list, matching donors to recipients 24 hours a day, 365 days a year. * Maintaining the database that contains all organ transplant data for every transplant event that occurs in the U.S. * Bring together members to develop policies that make the best use of the limited supply of organs and give all patients a fair chance at receiving the organ they need, regardless of age, sex, ethnicity, religion, lifestyle or financial/social status. * Monitoring every organ match to ensure organ allocation policies are followed. * Provides assistance to patients, family members and friends. * Educates transplant professionals about their important role in the donation and transplant processes. * Educating the public about the importance of organ donation. UNOS was first awarded the national Organ Procurement and Transplantation Network (OPTN) contract in 1986 by the U.S. Department of Health and Human Services. UNOS continues as the only organization ever to operate the OPTN. As part of the OPTN contract, UNOS has: * established an organ sharing system that maximizes the efficient use of deceased organs through equitable and timely allocation * established a system to collect, store, analyze and publish data pertaining to the patient waiting list, organ matching, and transplants * informed, consulted and guided persons and organizations concerned with human organ transplantation in order to increase the number of organs available for transplantation

Proper citation: UNOS - United Network for Organ Sharing (RRID:SCR_004976) Copy   

•   Source: SciCrunch Registry

http://spot.cgsmd.isi.edu

A web-based tool for using biological databases to prioritize single nucleotide polymorphisms (SNPs) after a genome-wide association study (GWAS). The site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the genomic information network (GIN) method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution.

Proper citation: SPOT - Biological prioritization after a SNP association study (RRID:SCR_005193) Copy   

•   Source: SciCrunch Registry

http://autosome.ru/HOCOMOCO/

A comprehensive collection of human transcription factor binding sites models. DNA sequences of TF binding regions obtained by both pregenomic and high-throughput methods were collected from existing databases and other public data. The ChIPMunk software was used to construct positional weight matrices. Four motif discovery strategies were tested based on different motif shape priors including flat and periodic priors associated with DNA helix pitch. A quality rating was manually assigned to each model based on known binding preferences. An appropriate TFBS model was selected for each TF, with similar models selected for related TFs. In any case only one model per TF was selected unless there was additional evidence for two distinct binding models or different stable modes of dimerization. All TFBS models and initial binding segments data used for motif discovery were mapped to UniPROT IDs.

Proper citation: HOCOMOCO (RRID:SCR_005409) Copy   

•   Source: SciCrunch Registry

http://www.membranetransport.org

TransportDB is a relational database describing the predicted cytoplasmic membrane transport protein complement for organisms whose complete genome sequence are available. For each organism, its complete membrane transport complement was identified, classified into protein families according to the TC classification system, and functional predictions are provided.For each organism, a summary page is available, overviewing the whole transporter system, including transporter types and individual transporter families. For individual transporter types, a detailed list of transporters with their possible substrates is shown with links to individual protein page which contains protein sequence and annotation information. You can also compare the transporter system from two or more different organisms. A search engine is set up for easy search in our transporter database for transporter type, family, individual proteins and their substrates. You can also blast search your protein sequence against our transporter database.With the rapid development of genomic sequencing both in TIGR and in other institutes, more and more genomes are available for the analysis of their transporter system. We will keep updating this site with the newly published genomes. If you have any suggestions, corrections, or comments on our site, please contact us. We are currently working on providing additional functionality for this database.

Proper citation: TransportDB (RRID:SCR_005643) Copy   

•   Source: SciCrunch Registry