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http://www.nitrc.org/projects/tumorsim/

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

http://www.tc.umn.edu/~konox006/Code/SNPMeta/

A Python and BioPython-based tool to generate metadata for single nucleotide polymorphisms (SNPs) for easy filtering, or submission to SNP databases. Information reported includes gene name, whether the SNP is coding or noncoding, and whether the SNP is synonymous or nonsynonymous. SNPMeta outputs in either a dbSNP submission report format, or a tab-delimited format. There is a also Web-based version available that only annotates with default settings, and only annotates a maximum of 20 SNPs at one time. The script may be downloaded for full functionality.

Proper citation: SNPMeta (RRID:SCR_002005) Copy   

•   Source: SciCrunch Registry

http://seer.cancer.gov/resources/

Portal provides SEER research data and software SEER*Stat and SEER*Prep. SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas can be used to examine stage at diagnosis by race/ethnicity, calculate survival by stage at diagnosis, age at diagnosis, and tumor grade or size, determine trends and incidence rates for various cancer sites over time. SEER releases new research data every Spring based on the previous November’s submission of data.

Proper citation: SEER Datasets and Software (RRID:SCR_003293) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.nl/QualitySNPng/

Software for the detection and visualization of single nucleotide polymorphisms (SNPs) from next generation sequencing data that uses a haplotype-based strategy.

Proper citation: QualitySNPng (RRID:SCR_002479) Copy   

•   Source: SciCrunch Registry

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

Software that simulates PacBio reads by using either a model-based or sampling-based simulation.

Proper citation: PBSIM (RRID:SCR_002512) Copy   

•   Source: SciCrunch Registry

http://biologicstylus.sourceforge.net/

Biologic Stylus is Biologic Institute's Stylus simulation software suite. Programming Language: C++, Python

Proper citation: Biologic Stylus (RRID:SCR_002991) Copy   

•   Source: SciCrunch Registry

http://www.fda.gov/ScienceResearch/BioinformaticsTools/MicroarrayQualityControlProject/default.htm

Project to improve the microarray and next-generation sequencing technologies and foster their proper applications in discovery, development and review of FDA regulated products by developing standards and quality measures. Microarrays and next-generation sequencing represent core technologies in pharmacogenomics and toxicogenomics; however, before these technologies can successfully and reliably be used in clinical practice and regulatory decision-making, standards and quality measures need to be developed. Everyone is invited to participate in the MAQC project.

Proper citation: MAQC (RRID:SCR_002351) Copy   

•   Source: SciCrunch Registry

http://wiki.na-mic.org/Wiki/index.php/2010_Winter_Project_Week_Spine_Segmentation_Module_in_Slicer3

3D Slicer module for automated segmentation of the spine. This is an implementation of a novel model-based segmentation algorithm. This work was presented at the NA-MIC Week in Salt Lake City, Jan 2010.

Proper citation: SpineSegmentation module for 3DSlicer (RRID:SCR_002593) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/btorb/btmorph

Small Python library containing a data structure and tools to represent and analyze neuronal morphologies stored in the de facto standard SWC format.

Proper citation: BTMORPH (RRID:SCR_003566) Copy   

•   Source: SciCrunch Registry

https://github.com/

A web-based hosting service for software development projects that use the Git revision control system offering powerful collaboration, code review, and code management. It offers both paid plans for private repositories, and free accounts for open source projects. Large or small, every repository comes with the same powerful tools. These tools are open to the community for public projects and secure for private projects. Features include: * Integrated issue tracking * Collaborative code review * Easily manage teams within organizations * Text entry with understated power * A growing list of programming languages and data formats * On the desktop and in your pocket - Android app and mobile web views let you keep track of your projects on the go.

Proper citation: GitHub (RRID:SCR_002630) Copy   

•   Source: SciCrunch Registry

http://165.124.81.52/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 08, 2013. A consortium of three facilities whose purpose is to establish, characterize, and distribute novel mutant mouse models with neural and/or behavioral phenotypes, and distribute them to the worldwide research community. Interested scientists are able to obtain information about mouse lines at all three sites in a single unified database. GOALS * Increase genomic and genetic tools for functional gene identification * Provide mice with mutations that alter the nervous system or behavior * Build collaborations between geneticists and neuroscientists The consortium is made up of three mutagenesis and phenotypic screening facilities, focused on identifying alterations in nervous system function and behavior, and established by NIH. They are the Neurogenomics Project at Northwestern University, the Neuroscience Mutagenesis Facility at The Jackson Laboratory, and the Neuromutagenesis Project of the Tennessee Mouse Genome Consortium. The NIH Neurogenomics Project at Northwestern University is directed by Dr. Joseph S. Takahashi, who also acts as the Director of the Neuromice.org consortium. Chemical mutagenesis is used to induce mutations throughout the genome and combined with phenotypic screens to detect mice with mutations. In order to maximize the genomic coverage and recover both dominant and recessive mutations, a dominant G1 screen and a recessive G3 screen are utilized. Phenotypic screens focus on five primary domains: learning and memory, behavioral responses to stress, responses to psychostimulants, circadian rhythmicity, and vision. The Neuroscience Mutagenesis Facility at the Jackson Laboratory is directed by Dr. Wayne N. Frankel. The Neuroscience Mutagenesis Facility is using a three-generation backcross breeding scheme to produce homozygous mutants and will thus recover dominant, semidominant, and recessive mutations. In addition, some mutagenesis will be done in ES cells followed by two generations of breeding. Phenotypic screens focus on identifying mutations affecting: motor function, seizure threshold, hearing, vision, and neurodevelopment. The Neuromutagenesis Project of the Tennessee Mouse Genome Consortium (TMGC) involves researchers throughout the state of Tennessee, under the direction of Dr. Daniel Goldowitz, Ph.D., at the University of Tennessee Health Science Center, Memphis. TMGC also includes researchers at Oak Ridge National Laboratory, Vanderbilt University, Meharry Medical College, University of Tennessee-Knoxville, St. Jude Children's Research Hospital, and the University of Memphis. The Project is using regional mutagenesis, covering regions on chromosomes 10, 14, 15, 19, and X, thus including approximately 15 of the genome in the screened region. Phenotypic screens include: motor and sensory function, learning and memory, neurohistology, aging, alcohol response, abused drug response, visual function, and social behavior. Neuromice.org has stopped taking orders online but mutants are orderable please contact the originating center for availability and pricing details. Live targeted mutant Fragile X model mice are now available for distribution.

Proper citation: neuromice (RRID:SCR_002993) Copy   

•   Source: SciCrunch Registry

http://burgundy.cmmt.ubc.ca/cgi-bin/RAVEN/a?rm=home

Tool to search for putative regulatory genetic variation in your favorite gene. Single nucleotide polymorphisms (SNPs) (from dbSNP and user defined) are analyzed for overlap with potential transcription factor binding sites (TFBS) and phylogenetic footprinting using UCSC phastCons scores from multiple alignments of 8 vertebrate genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RAVEN (RRID:SCR_001937) Copy   

•   Source: SciCrunch Registry

http://nipy.org/nitime/

Software library for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code.

Proper citation: Nitime (RRID:SCR_002504) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/OPE

Ontology that provides a reference for describing an exercise in terms of functional movements, engaged musculoskeletal system parts, related equipment or monitoring devices, intended health outcomes, as well as target ailments for which the exercise might be employed as a treatment or preventative measure.

Proper citation: Ontology of Physical Exercises (RRID:SCR_003836) Copy   

•   Source: SciCrunch Registry

http://pennadc.org

A national Alzhiemer's disease research center funded by the National Institute on Aging, and the research arm of the Penn Memory Center.

Proper citation: Penn Alzheimer's Disease Center (RRID:SCR_004444) Copy   

•   Source: SciCrunch Registry

http://f1000.com/posters

An open access repository of conference posters from across the life sciences and medicine. It provides a permanent, structured environment for the deposition of posters as well as a trustworthy venue for ongoing discussion and development of the information being presented. You can browse posters by Topic or Section or by conference. Please note that most posters on this site present work that is preliminary in nature and has not been peer reviewed. The most interesting posters are selected for evaluation by our expert Faculty and you will receive ideas and feedback. Widen your audience ����?? top performing posters receive 800+ views in a month!

Proper citation: F1000 Posters (RRID:SCR_006503) Copy   

•   Source: SciCrunch Registry

http://crdd.osdd.net/servers/virsirnadb/

VIRsiRNAdb is a curated database of experimentally validated viral siRNA / shRNA targeting diverse genes of 42 important human viruses including influenza, SARS and Hepatitis viruses. Submissions are welcome. Currently, the database provides detailed experimental information of 1358 siRNA/shRNA which includes siRNA sequence, virus subtype, target gene, GenBank accession, design algorithm, cell type, test object, test method and efficacy (mostly quantitative efficacies). Further, wherever available, information regarding alternative efficacies of above 300 siRNAs derived from different assays has also been incorporated. The database has facilities like search, advance search (using Boolean operators AND, OR) browsing (with data sorting option), internal linking and external linking to other databases (Pubmed, Genbank, ICTV). Additionally useful siRNA analysis tools are also provided e.g. siTarAlign for aligning the siRNA sequence with reference viral genomes or user defined sequences. virsiRNAdb would prove useful for RNAi researchers especially in siRNA based antiviral therapeutics development.

Proper citation: VIRsiRNAdb (RRID:SCR_006108) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/2.8/bioc/html/qrqc.html

Software R package to quickly scan reads and gather statistics on base and quality frequencies, read length, k-mers by position, and frequent sequences. Produces graphical output of statistics for use in quality control pipelines, and an optional HTML quality report. S4 SequenceSummary objects allow specific tests and functionality to be written around the data collected.

Proper citation: qrqc (RRID:SCR_006867) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/geo/

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

Proper citation: Gene Expression Omnibus (GEO) (RRID:SCR_005012) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/hPATM/

A web tool, based on a heuristic transformation of the original global pairwise and local pairwise alignment algorithms, offers objective alignments for transmembrane protein sequences. hPATM takes advantage of the information offered by the knowledge of the position of transmembrane segmets, by experiment or prediction. The heuristic approach may reveal similarities between diverge sequences with low percentages of identity and similarity. The produced alignments, based on common structural scaffolds derived by the transmembrane segments of the sequence, can be used to spot conserved non-transmembrane segments or as a basis for the production of 3-D models via homology modelling. The hPAFAG algorithm is based on the heuristic transformation of the Needleman & Wunsch and Smith & Waterman algorithms, featuring affine gap penalties. The heuristic transformation is based on two extra features: * a heuristic bonus, added to the score when two amino acids that belong to transmembrane segmens are aligned. * a heuristic gap penalty, substracted from the score when a gap is opened in a transmembrane segment. This way transmembrane segments are anchored (not by force, but by more strict alignment) together, allowing the pairwise alignment to focus on non-transmembrane segments. This web server offers a friendly interface for the hPATM command line version. The algorithm was implemented in PERL and the source code of the command line version is available on request by the authors.

Proper citation: hPATM (RRID:SCR_006224) Copy   

•   Source: SciCrunch Registry