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http://www.bioontology.org

Organization that provides biomedical researchers with online tools and a web portal enabling them to access, review, and integrate disparate ontological resources in all aspects of biomedical investigation and clinical practice. A major focus of the work involves the use of biomedical ontologies to aid in the management and analysis of data derived from complex experiments.

Proper citation: National Center for Biomedical Ontology (RRID:SCR_003304) Copy   

•   Source: SciCrunch Registry

http://sagebase.org/

Non-profit biomedical research organization developing predictors of disease and accelerating health research through creation of open systems, incentives, and standards. Formed to coordinate and link academic and commercial biomedical researchers through Commons that represents new paradigm for genomics intellectual property, researcher cooperation, and contributor evolved resources.

Proper citation: Sage Bionetworks (RRID:SCR_003384) Copy   

•   Source: SciCrunch Registry

http://neuroscience.aecom.yu.edu/index.html

University department that oversees neuroscience research and graduate education.

Proper citation: Albert Einstein College of Medicine of Yeshiva University Department of Neuroscience (RRID:SCR_003303) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/NormqPCR.html

Software package providing functions for the selection of optimal reference genes and the normalization of real-time quantitative PCR data.

Proper citation: NormqPCR (RRID:SCR_003388) Copy   

•   Source: SciCrunch Registry

http://signalml.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.An XML-based language designed for metadescription of formats, used for digital storage of biomedical time series. Using SignalML, information on the structure of binary data files can be simply and efficiently coded. Once written, this information can be used by any software, which - owing to this metadescription - can read data files in the original format. This eliminates the need for conversions and duplication of data. signalml.org provides the following resources for interchange of relevant information and ideas: * SignalML wiki * Newsgroup / mailing list The main current software project is Svarog - a SignalML-compliant signal viewer, annotator, analyzer and (future) recorder. Svarog is written in Java and is currently best fitted for display of EEG and MEG signals. Also open platform for implementing advanced signal processing methods in user-friendly environment, at the moment interfacs for Java code, standalone executables and Matlab code via Matlab Builder for Java.

Proper citation: signalml.org (RRID:SCR_003383) Copy   

•   Source: SciCrunch Registry

http://www.exbio.cz/

An Antibody supplier

Proper citation: EXBIO Praha (RRID:SCR_003381) Copy   

•   Source: SciCrunch Registry

http://www.gene-quantification.de/bestkeeper.html

Excel-based tool using pair-wise correlations for determination of stable housekeeping genes, differentially regulated target genes and sample integrity. It determines the best suited standards, out of ten candidates, and combines them into an index. The index can be compared with further ten target genes to decide, whether they are differentially expressed under an applied treatment. All data processing is based on crossing points.

Proper citation: BestKeeper (RRID:SCR_003380) Copy   

•   Source: SciCrunch Registry

http://phosphat.uni-hohenheim.de/

Database containing information on Arabidopsis phosphorylation sites which were identified by mass spectrometry in large scale experiments from different research groups. Specific information on the peptide properties as well as on the experimental and analytical context is given. The PhosPhAt service has a built-in plant specific phosphorylation site predictor trained on the experimental dataset for Serine, threonine and tyrosine phosphorylation (pSer, pThr, pTyr). Protein sequences or Arabidopsis AGI gene identifier can be submitted to the predictor. Users and researchers are encouraged to assist in keeping the database current by submitting either published data or unpublished data (MS/MS data required).

Proper citation: PhosPhAt (RRID:SCR_003332) Copy   

•   Source: SciCrunch Registry

http://bio3d.colorado.edu/imod

A free, cross-platform set of image processing, modeling and display programs used for tomographic reconstruction and for 3D reconstruction of EM serial sections and optical sections. The package contains tools for assembling and aligning data within multiple types and sizes of image stacks, viewing 3-D data from any orientation, and modeling and display of the image files. IMOD 4.1.8 Is Now Available for Linux, Windows, and Mac OS X

Proper citation: IMOD (RRID:SCR_003297) Copy   

•   Source: SciCrunch Registry

https://github.com/egonw/semanticchemistry

An ontology that aims to establish a standard in representing chemical information including chemical structure and the ability to richly describe chemical properties, whether intrinsic or computed. It includes terms for the descriptors commonly used in cheminformatics software applications and the algorithms which generate them.

Proper citation: Chemical Information Ontology (RRID:SCR_003290) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/amplicon/

Software tool for designing PCR primers on aligned groups of DNA sequences. The most important application is the design of "group-specific" PCR primer sets that amplify a DNA region from a given taxonomic group but do not amplify orthologous regions from other taxonomic groups. It is written in Python 2.3 and Tkinter 8.4. The current script was created for Windows and an executable is available. Future versions of the script should be able to run on Linux and Mac

Proper citation: Amplicon (RRID:SCR_003294) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. An initiative to develop a molecular classification schema that is both clinically and biologically meaningful, based on gene expression and genomic data from tumors (Gliomas) of patients who will be prospectively followed through natural history and treatment phase of their illness. The study will also explore gene expression profiles to determine the responsiveness of the patients and correlate with discrete chromosomal abnormalities. The initiative was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. The sample collection is accompanied by careful and prospective clinical data acquisition, allowing a variety of matched molecular and clinical data permitting a wide variety of analyses. GMDI has accrued fresh frozen tumors in the retrospective phase (all from the Henry Ford Hospital, without germline DNA) and fresh frozen tumors in the prospective phase (from a variety of institutions). In addition to characterizing the samples from patients enrolled in GMDI, the microarray group has generated genomic-scale analyses of the many human and canine glioma initiating cells/glioma stem cells (GIC/GSC) lines, as well as many canine and murine normal neural stem cell (NSC) lines produced in laboratory.

Proper citation: Glioma Molecular Dignostic Initiatives (RRID:SCR_003329) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/datasets/OglycBase/

Revised database of O- and C-glycosylated proteins. The criteria for inclusion are at least one experimentally verified O- or C-glycosylation site. Each entry contains information about the glycan involved, the species, sequence, a literature reference and http-linked cross-references to other databases. Version 6.00 has 242 glycoprotein entries. The terminal sugar linked to serine or threonine is cited when known. The database is non-redundant in the sense that it contains no identical sequences, unless there is conflicting glycosylation data. Mucins have tandem repeat sequences, which are O-glycosylated. This result in some redundancy of the O-glycosylation sites. For prediction purposes they have also included a version of the database which contains no identical O-glycosylation sites (window=9) called O-Unique.seq. Data can no longer be retrieved by anonymous ftp. Only http is supported. New data, comments and suggestions are welcome.

Proper citation: O-GLYCBASE (RRID:SCR_003288) Copy   

•   Source: SciCrunch Registry

http://nrresource.org

Collection of individual databases on members of the steroid and thyroid hormone receptor superfamily. Although the databases are located on different servers and are managed individually, they each form a node of the NRR. The NRR itself integrates the separate databases and allows an interactive forum for the dissemination of information about the superfamily. NRR Components: Androgen receptor, Estrogen receptor, Glucocorticoid receptor, Peroxisome proliferator, Steroid receptor protein, Thyroid receptor, Vitamin D receptor.

Proper citation: Nuclear Receptor Resource (RRID:SCR_003285) Copy   

•   Source: SciCrunch Registry

http://www.xenbase.org/

Data collection for Xenopus laevis and Xenopus tropicalis biology and genomics.

Proper citation: Xenbase (RRID:SCR_003280) Copy   

•   Source: SciCrunch Registry

http://pdsp.med.unc.edu/pdsp.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. Database of information on the abilities of drugs to interact with an expanding number of molecular targets. It serves as a data warehouse for published and internally-derived Ki, or affinity, values for a large number of drugs and drug candidates at an expanding number of G-protein coupled receptors, ion channels, transporters and enzymes. The query interface is designed to let you search by any field, or combination of them to refine your search criteria. The flexible user interface also provides for customized data mining. The database is regularly updated. If you know of Ki data you would like to add, you can select Direct Ki Entry at the grey panel. If you would like, however, your own data (published or not) added, Send them a Reference at the grey panel, or send an email to Dr. Bryan Roth or Estela Lopez. Most common targets: 5-HT2A, DOPAMINE D1, DOPAMINE D2, 5-HT2C, 5-HT1A, Cholinergic, muscarinic M1, 5-HT Transporter, HISTAMINE H1, 5-HT2B, OPIOID Mu, 5-HT6, adrenergic Beta2, 5-HT7, OPIATE Delta, adrenergic Alpha1A, OPIOID Kappa, 5-HT3, m-AChR, adrenergic Beta1, adrenergic Alpha2A, 5-HT1, Acetylcholinesterase, AChE, Thromboxane A2, n-AChR, Opiate non-selective, CANNABINOID CB1, HERG, Dopamine, cocaine site, adrenergic Alpha2C, M3, Norepinephrine Uptake, Monoamine Oxidase A, Monoamine Oxidase B, 5-HT4, adrenergic Alpha1, 5-HT1E, B1 BRADYKININ, 5-HT2, 5-HT2C-INI, DOPAMINE D4, ANGIOTENSIN AT1, Neurokinin NK1, HISTAMINE H3, Sigma-1, VIP, Dopamine2-like, metabotropic glutamate 5, 5-HT2c VGI, Carbonic Anhydrase Isozymes, CA I, DOPAMINE D2 Long, adrenergic Alpha2, adrenergic Alpha2B, adrenergic Alpha2D, GABA A alpha1, CANNABINOID CB2, adrenergic Alpha1B, 5-HT5a, Melatonin, HISTAMINE H4, NMDA, 5-HT4a, Glucocorticoid, Interleukin 1-beta, Sodium Channel, Benzodiazepine central, Cholinergic, muscarinic M5, Neuropeptide Y1, GABA A alpha5, Galanin R2, Neurokinin NK3, 5-HT1B, M2, DOPAMINE D3, Angiotensin, Dopamine1-like, Neurokinin NK2, adrenergic Beta, Dopamine D1 high, Dopamine D1A, MAP kinase, ADENOSINE A2a, 5-HT7b, Nitrogen oxide synthase - neuronal, Sigma-2, CDK2, Neurotensin 2, DOPAMINE D2 Short, Multidrug Resistance Transporter MDR 1, GABA A Benzodiazepine, VEGF-R2, OPIATE Mu 2, Angiotensin II AT1, HISTAMINE H2, Angiotensin-converting enzyme, ACE, Sigma, beta-amyloid, ADENOSINE, ADENOSINE A2B, Adrenaline, Neurotensin 1

Proper citation: Psychoactive Drug Screening Program Ki Database (RRID:SCR_003281) Copy   

•   Source: SciCrunch Registry

http://genecloud.org/

Gene Cloud is a novel tool presenting gene-gene associations based on the scientific literature. It was developed by the Knockout Mouse Repository (www.komp.org) to help our customers find products related to other products they chose. We have built a detailed graph model of gene-gene associations based on how many times two genes are cited in the same article. If two genes are cited in many papers together, they are considered strongly connected. Each instance of Gene Cloud is centered around a specific gene. A list of the top most related genes is plotted as a branching structure from the center. A secondary branch can occur if a gene in the graph is more related a non-central gene than it is to the center gene. The font size of a branched gene indicates the relative strength of connection--always to the center gene. The distribution of genes in space is randomized each time Gene Cloud is run so a different picture will result for the same central gene. Color is used to indicate the availability of Knockout Mouse products at the KOMP Repository. If a gene is colored green in the graph there are products (mutant ES cells, sperm, embryos, or mice) ready to be ordered. Blue colored genes do not yet have products available, but you can follow the links back to the KOMP Repository and register interest to be alerted when products do become available. Gene Cloud is driven by a database of gene-gene associations that currently contains 82,000 genes and other biotypes, 113,000 annotated publications, and 467 million connections. The latest gene symbols, names and gene-publication annotation information is updated daily from the Mouse Genome Informatics database. The graphing is accomplished through the use of a modified version of jsViz.

Proper citation: Gene Cloud: Exploring Connections in the Mouse Genome (RRID:SCR_003503) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/popoolation/

A collection of tools to facilitate population genetic studies of next generation sequencing data from pooled individuals. It builds upon open source tools (bwa, samtools) and uses standard file formats (gtf, sam, pileup) to ensure a wide compatibility. PoPoolation allows to calculate Tajima's Pi, Watterson's Theta and Tajima's D for reference sequences using a sliding window approach. Alternatively these population genetic estimators may be calculated for a set of genes (provided as gtf). One of the main challenges in population genomics is to identify regions of intererest on a genome wide scale. PoPoolation will greatly aid this task by allowing a fast and user friendly analysis of NGS data from DNA pools.

Proper citation: PoPoolation (RRID:SCR_003495) Copy   

•   Source: SciCrunch Registry

https://github.com/delt0r/msms

A coalescent simulation software program for a structured population including recombination, demographic structure and selection at a single diploid locus.

Proper citation: MSMS (RRID:SCR_003532) Copy   

•   Source: SciCrunch Registry