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https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

•   Source: SciCrunch Registry

https://software.broadinstitute.org/gatk/

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

Proper citation: GATK (RRID:SCR_001876) Copy   

•   Source: SciCrunch Registry

http://flybrain.stanford.edu/

Project content including raw image data, neuronal tracings, image registration tools and analysis scripts covering three manuscripts: Comprehensive Maps of DrosophilaHigher Olfactory Centres : Spatially Segregated Fruit and Pheromone Representation which uses single cell labeling and image registration to describe the organization of the higher olfactory centers of Drosophila; Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe which uses single cell labeling to describe the organization of the antennal lobe local interneurons; and Sexual Dimorphism in the Fly Brain which uses clonal analysis and image registration to identify a large number of sex differences in the brain and VNC of Drosophila. Data * Raw Data of Reference Brain (pic, amira) (both seed and average) * Label field of LH and MB calyx and surfaces for these structures * Label field of neuropil of Reference Brain * Traces (before and after registration). Neurolucida, SWC and AmiraMesh lineset. * MB and LH Density Data for different classes of neuron. In R format and as separate amira files. * Registration files for all brains used in the study * MBLH confocal images for all brains actually used in the study (Biorad pic format) * Sample confocal images for antennal lobe of every PN class * Confocal stacks of GABA stained ventral PNs Programs * ImageJ plugins (Biorad reader /writer/Amira reader/writer/IGS raw Reader) * Binary of registration, warp and gregxform (macosx only, others on request) * Simple GUI for registration tools (macosx only at present) * R analysis/visualization functions * Amira Script to show examples of neuronal classes The website is a collaboration between the labs of Greg Jefferis and Liqun Luo and has been built by Chris Potter and Greg Jefferis. The core Image Registration tools were created by Torsten Rohlfing and Calvin Maurer.

Proper citation: Flybrain at Stanford (RRID:SCR_001877) Copy   

•   Source: SciCrunch Registry

http://learn.genetics.utah.edu/

Educational resources that provide accurate and unbiased information about topics in genetics, bioscience and health for global and local audiences. They are jargon-free, target multiple learning styles, and often convey concepts through animation and interactivity. The Genetic Science Learning Center is a science and health education program located in the midst of the bioscience research being carried out at the University of Utah. Our mission is making science easy for everyone to understand. * Two websites, available free of charge to Internet users worldwide: ** Learn.Genetics delivers educational materials on genetics, bioscience and health topics. They are designed to be used by students, teachers and members of the public. The materials meet selected US education standards for science and health. ** Teach.Genetics provides resources for K-12 teachers, higher education faculty, and public educators. These include PDF-based Print-and-Go™ activities, unit plans and other supporting resources. The materials are designed to support and extend the materials on Learn.Genetics. *Professional development programs that update K-16 teachers' expertise in bioscience and health topics as well as prepare them to implement the materials on our websites. * Community programs that engage with diverse communities in discussions about genetics and health, and in developing culturally and linguistically-appropriate educational materials. Some topics in genetics and bioscience research are controversial. The Center does not take sides in political or ethical controversies. Rather, our goal is to provide comprehensive information that promotes a lively discussion of these topics, so that individuals can arrive at their own informed decisions.

Proper citation: University of Utah Genetic Science Learning Center - Learn Genetics (RRID:SCR_001910) Copy   

•   Source: SciCrunch Registry

http://www.agcol.arizona.edu/software/tcw/

Software package for assembling, annotating, querying, and comparing transcript and expression level data that consists of two parts: * singleTCW (sTCW): Single transcript sets or assemblies; annotation; differential expression (EdgeR, DEGSeq, DESeq, GoSeq) * multiTCW (mTCW): Comparison of multiple transcript sets; ortholog grouping (e.g., OrthoMCL) It has been tested on Linux and uses Java, mySQL and optionally R.

Proper citation: TCW (RRID:SCR_001875) Copy   

•   Source: SciCrunch Registry

http://victorian-bioinformatics-consortium.github.io/degust/

An interactive web tool for visualizing differential gene expression data.

Proper citation: Degust (RRID:SCR_001878) Copy   

•   Source: SciCrunch Registry

http://english.msip.go.kr/english/main/main.do

Division of the South Korea government responsible for formulating national science and technology policies and plans.

Proper citation: Korean Ministry of Science ICT and Future Planning (RRID:SCR_001911) Copy   

•   Source: SciCrunch Registry

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

Software that provides utilities for flow cytometry data.

Proper citation: flowUtils (RRID:SCR_001879) Copy   

•   Source: SciCrunch Registry

http://mousecyc.jax.org/

A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database.

Proper citation: MouseCyc (RRID:SCR_001791) Copy   

•   Source: SciCrunch Registry

http://ahd.cbi.pku.edu.cn

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Proper citation: Arabidopsis Hormone Database (RRID:SCR_001792) Copy   

•   Source: SciCrunch Registry

https://github.com/hms-dbmi/spp

R analysis and processing package for Illumina platform Chip-Seq data.

Proper citation: SPP (RRID:SCR_001790) Copy   

•   Source: SciCrunch Registry

http://www.myexperiment.org/

Community repository and virtual research environment where scientists can safely publish their workflows and experiment plans, share them with groups and find and use those of others. Workflows, other digital objects and collections (called Packs) can be swapped, sorted and searched. It supports Linked data, has a SPARQL Endpoint and REST API and is based on an open source Ruby on Rails codebase. Scientific workflows in various formats can be uploaded. Specific support is provided for Taverna workflows for which the system displays relevant metadata, components and visual previews, that are retrieved directly from workflow files. Version history for workflows is collected. This feature allows the contributor to keep previous versions of the workflow available, when the latest one is uploaded. This brings additional benefit for the users by allowing them to view the development stages of the workflow towards its latest implementation.

Proper citation: myExperiment (RRID:SCR_001795) Copy   

•   Source: SciCrunch Registry

https://openprovenance.org/opm/

A model of provenance that is designed to meet the following requirements: (1) To allow provenance information to be exchanged between systems, by means of a compatibility layer based on a shared provenance model. (2) To allow developers to build and share tools that operate on such a provenance model. (3) To define provenance in a precise, technology-agnostic manner. (4) To support a digital representation of provenance for any "thing", whether produced by computer systems or not. (5) To allow multiple levels of description to coexist. (6) To define a core set of rules that identify the valid inferences that can be made on provenance representation.

Proper citation: Open Provenance Model (RRID:SCR_001829) Copy   

•   Source: SciCrunch Registry

http://www.pdc.kth.se/

PDC operates leading-edge, high-performance computers on a national level. PDC offers easily accessible computational resources that primarily cater to the needs of Swedish academic research and education. PDC also takes part in major international projects to develop high-performance computing for the future and stay a leading national resource in parallel computing.

Proper citation: Royal Institute of Technology: PDC (RRID:SCR_001828) Copy   

•   Source: SciCrunch Registry

https://github.com/JialiUMassWengLab/TEMP

Software package for detecting transposable elements (TEs) insertions and excisions from pooled high-throughput sequencing data.

Proper citation: TEMP (RRID:SCR_001788) Copy   

•   Source: SciCrunch Registry

https://github.com/uci-cbcl/EXTREME

A motif discovery algorithm designed to find DNA-binding motifs in ChIP-Seq and DNase-Seq data.

Proper citation: EXTREME (RRID:SCR_001821) Copy   

•   Source: SciCrunch Registry

http://www.mimg.ucla.edu/faculty/xing/glimmps/

Software to characterize the genetic variation of alternative splicing using a robust statistical method for detecting splicing quantitative trait loci (sQTLs) from RNA-seq data. It takes into account the individual variation in sequencing coverage and the noise prevalent in RNA-seq data.

Proper citation: GLiMMPS (RRID:SCR_001787) Copy   

•   Source: SciCrunch Registry

http://consc.net/online

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. This is a directory of 5311 free online papers on consciousness in philosophy and in science, and of related topics in the philosophy of mind. The papers in this directory are drawn from PhilPapers, a database of both online and offline works in philosophy. Sponsors: Sponsored by the Joint Information Systems Committee as part of the Information Environment Programme.

Proper citation: Online Papers on Consciousness (RRID:SCR_001826) Copy   

•   Source: SciCrunch Registry

http://www.wikicancer.org/

A place where people connected to cancer can share real-life experiences -- fears, insights, stories, and advice. Adding perspectives is easy, and every contribution builds the site into a more valuable and unique community resource. Content, resources, and support on wikiCancer: * Just been diagnosed with cancer? * Living with cancer * For cancer survivors * How to support someone with cancer * Connect with other cancer patients, survivors, family and caregivers

Proper citation: wikiCancer (RRID:SCR_001824) Copy   

•   Source: SciCrunch Registry

https://github.com/shka/R-SAMstrt

Software package that provides the significance analysis of sequencing data with spike-in normalization. The statistical backgrounds and the benefits depend on SAMseq of the samr package.

Proper citation: SAMstrt (RRID:SCR_001780) Copy   

•   Source: SciCrunch Registry