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https://bitbucket.org/dranew/defuse

Software package for gene fusion discovery using RNA-Seq data. It uses clusters of discordant paired end alignments to inform a split read alignment analysis for finding fusion boundaries.

Proper citation: deFuse (RRID:SCR_003279) Copy   

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http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

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http://vano.cellexplorer.org/

VANO is a Volume image object AnNOtation System for 3D multicolor image stacks, developed by Hanchuan Peng, Fuhui Long, and Gene Myers. VANO provides a well-coordinated way to annotate hundreds or thousands of 3D image objects. It combines 3D views of images and spread sheet neatly, and is just easy to manage 3D segmented image objects. It also lets you incorporate your segmentation priors, and lets you edit your segmentation results! This system has been used in building the first digital nuclei atlases of C. elegans at the post-embryonic stage (joint work with Stuart Kim lab, Stanford Univ), the single-neuron level fruit fly neuronal atlas of late embryos (with Chris Doe lab, Univ of Oregon, HHMI), and the compartment-level of digital map(s) of adult fruit fly brains (several labs at Janelia Farm, HHMI). VANO is cross-platform software. Currently the downloadable versions are for Windows (XP and Vista) and Mac (Intel-chip based, Leopard or Tiger OS). If you need VANO for different systems (such as 64bit or 32bit, Redhat Linux, Ubuntu, etc), you can either compile the software, or send an email to pengh (at) janelia.hhmi.org. VANO is Open-Source. You can download both the source code files and pre-complied versions at the Software Downloads page.

Proper citation: Volume image object AnNOtation System (RRID:SCR_003393) Copy   

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http://www.well.ox.ac.uk/

An international leader in genetics, genomics and structural biology, and research institute of the Nuffield Department of Medicine at the University of Oxford, whose objective is to extend our understanding on how genetic inheritance makes us who we are in order to gain a clearer insight into mechanisms of health and disease. Looking across all three billion letters of the human genetic code, they aim to pinpoint variant spellings and discover how they increase or decrease an individual's risk of falling ill. They collaborate with research teams across the world on a number of large-scale studies in these areas.

Proper citation: Wellcome Trust Centre for Human Genetics (RRID:SCR_003307) Copy   

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http://moma.dk/normfinder-software

Software for identifying the optimal normalization gene among a set of candidates. It ranks the set of candidate normalization genes according to their expression stability in a given sample set and given experimental design. It can analyze expression data obtained through any quantitative method e.g. real time RT-PCR and microarray based expression analysis. NormFinder.xla adds the NormFinder functionality directly to Excel. A version for R is also available.

Proper citation: NormFinder (RRID:SCR_003387) Copy   

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http://protege.stanford.edu

Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development.

Proper citation: Protege (RRID:SCR_003299) Copy   

•   Source: SciCrunch Registry

http://www.genedata.com/products/expressionist/genomic-profiling.html

Software that provides data processing, analysis, management, and reporting of metabolomics, proteomics and biotherapeutics characterization studies based on mass spectrometry. It can process raw data from various MS instruments, serve MS processing, analysis and reporting needs, and ensure reproducibility and traceability of results.

Proper citation: Genedata Expressionist (RRID:SCR_003298) Copy   

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http://edoctoring.ncl.ac.uk/Public_site/

Online educational tool that brings challenging clinical practice to your computer, providing medical education that is engaging, challenging and interactive. While there is no substitute for real-life direct contact with patients or colleagues, research has shown that interactive online education can be a highly effective and enjoyable method of learning many components of clinical medicine, including ethics, clinical management, epidemiology and communication skills. eDoctoring offers 25 simulated clinical cases, 15 interactive tutorials and a virtual library containing numerous articles, fast facts and video clips. Their learning material is arranged in the following content areas: * Ethical, Legal and Social Implications of Genetic Testing * Palliative and End-of-Life Care * Prostate Cancer Screening and Shared Decision-Making

Proper citation: eDoctoring (RRID:SCR_003336) Copy   

•   Source: SciCrunch Registry

http://www.decode.com/

A biopharmaceutical company applying its discoveries in human genetics to develop drugs and diagnostics for common diseases. They specialize in gene discovery - their population approach and resources have enabled them to isolate key genes contributing to major public health challenges from cardiovascular disease to cancer. The company's genotyping capacity is now one of the highest in the world. They have a large population-based biobank containing whole blood and DNA samples with extensive relevant phenotypic information from around 120.000 Icelanders. In the company's work in more than 50 disease projects, their statistical and informatics departments have established themselves in data processing and analysis. deCODE genetics is widely recognized as a center of excellence in genetic research.

Proper citation: deCODE genetics (RRID:SCR_003334) Copy   

•   Source: SciCrunch Registry

http://primerseq.sourceforge.net/

Software that designs RT-PCR primers that evaluate alternative splicing events by incorporating RNA-Seq data. It is particularly advantageous for designing a large number of primers for validating alternative splicing events found in RNA-Seq data. It incorporates RNA-Seq data in the design process to weight exons by their read counts. Essentially, the RNA-Seq data allows primers to be placed using actually expressed transcripts. This could be for a particular cell line or experimental condition, rather than using annotations that incorporate transcripts that are not expressed for the data. Alternatively, you can design primers that are always on constitutive exons. PrimerSeq does not limit the use of gene annotations and can be used for a wide array of species.

Proper citation: PrimerSeq (RRID:SCR_003295) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/OmicCircos.html

An R software application and package used to generate high-quality circular plots for visualizing genomic variations, including mutation patterns, copy number variations (CNVs), expression patterns, and methylation patterns.

Proper citation: OmicCircos (RRID:SCR_003292) Copy   

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https://github.com/rsc-ontologies/rsc-cmo

An ontology that describes methods used to collect data in chemical experiments, such as mass spectrometry and electron microscopy; preparing and separating material for further analysis, such as sample ionization, chromatography, and electrophoresis; and synthesizing materials, such as epitaxy and continuous vapor deposition. It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns. It is intended to be complementary to the Ontology for Biomedical Investigations (OBI).

Proper citation: Chemical Methods Ontology (RRID:SCR_003286) Copy   

•   Source: SciCrunch Registry

http://shendurelab.github.io/MIPGEN/

Software for a fast, simple way to generate designs for MIP assays targeting hundreds or thousands of genomic loci in parallel. Packaged with MIPgen are scripts that aid in visualization of MIP designs and processing of MIP sequence reads to SAM files that can then be passed through any standard variant calling pipeline.

Proper citation: MIPgen (RRID:SCR_003325) Copy   

•   Source: SciCrunch Registry

https://www.msu.edu/~brains/index.html

The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. Atlases and brain sections are available for a variety of mammals, and we are also developing a series of labeled atlases of stained sections for educators, students, and researchers. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan. What we are doing currently at Michigan State is a series of demonstration projects for publicizing the contents of the collections and ways in which they can be used. For example, the images from the collection can be used for comparative brain study. We have prepared databases of the contents of the collections for presentation and use on this site, as well as for downloading by users in several formats. We are also developing a series of labeled atlases of stained sections for educators, students, and researchers. This internet site is associated with the Comparative Mammalian Brain Collections site. All of the images are in JPEG or GIF format.

Proper citation: Michigan State University Brain Biodiversity Bank (RRID:SCR_003289) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/popoolation2/

Software to compare allele frequencies for SNPs between two or more populations and to identify significant differences. PoPoolation2 requires next generation sequencing data of pooled genomic DNA (Pool-Seq). It may be used for measuring differentiation between populations, for genome wide association studies and for experimental evolution., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PoPoolation2 (RRID:SCR_003284) Copy   

•   Source: SciCrunch Registry

http://www.yaleruddcenter.org/

A non-profit research and public policy organization devoted to improving the worlds diet, preventing obesity, and reducing weight stigma.

Proper citation: Yale Rudd Center for Food Policy and Obesity (RRID:SCR_003283) Copy   

•   Source: SciCrunch Registry

http://www.brainbank.mclean.org/

Biomaterial supply resource that acquires, processes, stores, and distributes postmortem brain specimens for brain research. Various types of brain tissue are collected, including those with neurological and psychiatric disorders, along with their parents, siblings and offspring. The HBTRC maintains an extensive collection of postmortem human brains from individuals with Huntington's chorea, Alzheimer's disease, Parkinson's disease, and other neurological disorders. In addition, the HBTRC also has a collection of normal-control specimens.

Proper citation: Harvard Brain Tissue Resource Center (RRID:SCR_003316) Copy   

•   Source: SciCrunch Registry

https://github.com/outbig/DAFGA

A python script package which estimates the evolutionary rate of a particular functional gene in a standardized manner by relating its sequence divergence to that of the 16S rRNA gene. It provides gene-specific parameter sets for OTU clustering and taxonomic assignment at desired rank, and it can be implemented into the diversity measurements offered by QIIME or Mothur.

Proper citation: DAFGA (RRID:SCR_003319) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/johanneskoester/snakemake/wiki/

A Python based language and execution environment for make-like workflows. The system supports the use of automatically inferred multiple named wildcards (or variables) in input and output filenames.

Proper citation: Snakemake (RRID:SCR_003475) Copy   

•   Source: SciCrunch Registry

http://bbid.irp.nia.nih.gov/

Database of images of putative biological pathways, macromolecular structures, gene families, and cellular relationships. It is of use to those who are working with large sets of genes or proteins using cDNA arrays, functional genomics, or proteomics. The rationale for this collection is that: # Except in a few cases, information on most biological pathways in higher eukaryotes is non-existent, incomplete, or conflicting. # Similar biological pathways differ by tissue context, developmental stages, stimulatory events, or for other complex reasons. This database allows comparisons of different variations of pathways that can be tested empirically. # The goal of this database is to use images created directly by biomedical scientists who are specialists in a particular biological system. It is specifically designed to NOT use average, idealized or redrawn pathways. It does NOT use pathways defined by computer algorithm or information search approaches. # Information on biological pathways in higher eukaryotes generally resides in the images and text of review papers. Much of this information is not easily accessible by current medical reference search engines. # All images are attributable to the original authors. All pathways or other biological systems described are graphic representations of natural systems. Each pathway is to be considered a work in progress. Each carries some degree of error or incompleteness. The end user has the ultimate responsibility to determine the scientific correctness and validity in their particular biological system. Image/pathway submissions are welcome.

Proper citation: Biological Biochemical Image Database (RRID:SCR_003474) Copy   

•   Source: SciCrunch Registry