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http://vamps.mbl.edu/overview.php

A publicly-accessible website to measure and visualize similarities and differences between molecular profiles of complex microbial communities. The project includes visualization tools such as heat maps that simultaneously compare the taxonomic distributions of multiple datasets and 3-D charts of the frequency distributions of 16S rRNA tags. Analytical tools include Chao diversity estimates and rarefaction curves. As a service to the community, researchers have the opportunity to upload their own data to the site for private viewing with the full range of data and analysis tools. Public data can be downloaded for further analysis locally.

Proper citation: VAMPS (RRID:SCR_004483) Copy   

•   Source: SciCrunch Registry

http://www.arabidopsis.org

Database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana. Data available includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from data pages to other Arabidopsis resources. The data can be searched, viewed and analyzed. Datasets can also be downloaded. Pages on news, job postings, conference announcements, Arabidopsis lab protocols, and useful links are provided.

Proper citation: TAIR (RRID:SCR_004618) Copy   

•   Source: SciCrunch Registry

http://www.aftol.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented Jan 13, 2022; To enhance the understanding of the evolution of the Kingdom Fungi, 1500+ species were sampled for eight gene loci across all major fungal clades, plus a subset of taxa for a suite of morphological and ultrastructural characters with resulting data: AFTOL Molecular Database (generated by WASABI - Web Accessible Sequence Analysis for Biological Inference), Blast search the AFTOL Database (generated by WASABI), AFTOL primers (generated by WASABI), AFTOL primers by species (generated by WASABI), AFTOL alignments, and the AFTOL Structural and Biochemical Database. Users may submit samples to the AFTOL project. AFTOL is a collaboration centered around four universities in the United States: Duke University (Francois Lutzoni and Rytas Vilgalys), Clark University (David Hibbett), Oregon State University (Joey Spatafora), and University of Minnesota (David McLaughlin). Participants throughout the world have donated vouchers, taxon samples, and gene sequences. The aim of the project is to reconstruct the fungal tree of life using all available data for eight loci (nuclear ribosomal DNA: LSU, SSU, ITS (including 5.8s, ITS1 and ITS2); RNA polymerase II: RPB1, RPB2; elongation factor 1-alpha; mitochondrial SSU rDNA, and mitochondrial ATP synthase protein subunit 6). A further objective of this study is to summarize and integrate current knowledge regarding fungal subcellular features within this new phylogenetic framework. The name of the bioinformatic package developed for AFTOL is WASABI which provides an efficient communication platform to facilitate the collection and dissemination of molecular data to (and from) the laboratories and participants. All molecular data can be viewed, downloaded, verified, and corrected by the participants of AFTOL. A central goal of the WASABI interface is to establish an automated analysis framework that includes basecalling of newly generated chromatograms, contig assembly, quality verification of sequences (including a local BLAST), sequence alignment, and congruence test. Gene sequences that pass all tests and are finally verified by their authors will undergo automated phylogenetic analysis on a regular schedule. Although all steps are initially carried out noninteractively, the users can verify and correct the results at any step and thus initiate the reanalysis of dependent data.

Proper citation: AFTOL (RRID:SCR_004650) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/brainsinsilicon/neurogrid.html

A specialized hardware platform that will perform cortex-scale emulations while offering software-like flexibility. With sixteen 12x14 sq-mm chips (Neurocores) assembled on a 6.5x7.5 sq-in circuit board that can model a slab of cortex with up to 16x256x256 neurons - over a million! The chips are interconnected in a binary tree by 80M spike/sec links. An on-chip RAM (in each Neurocore) and an off-chip RAM (on a daughterboard, not shown) softwire vertical and horizontcal cortical connections, respectively. It provides an affordable option for brain simulations that uses analog computation to emulate ion-channel activity and uses digital communication to softwire synaptic connections. These technologies impose different constraints, because they operate in parallel and in serial, respectively. Analog computation constrains the number of distinct ion-channel populations that can be simulatedunlike digital computation, which simply takes longer to run bigger simulations. Digital communication constrains the number of synaptic connections that can be activated per secondunlike analog communication, which simply sums additional inputs onto the same wire. Working within these constraints, Neurogrid achieves its goal of simulating multiple cortical areas in real-time by making judicious choices.

Proper citation: Neurogrid (RRID:SCR_005024) Copy   

•   Source: SciCrunch Registry

http://songbirdtranscriptome.net/

Database containing cDNA clone information of the brains of songbirds. These clones are annotated with behavioral information, as well as links to information of homologous genes of other species. The database includes over 91,000 zebra finch brain cDNAs (2009) sequenced by Duke, ESTIMA, and Rockefeller research groups. The project is a collaborative effort of the Jarvis Laboratory of Duke University, Duke Bioinformatics, and The Genomics group of RIKEN, with Erich D. Jarvis as P.I. and Kazuhiro Wada as Co-P.I. Microarrays with the cDNAs in this database are available at Duke http://mgm.duke.edu/genome/dna_micro/core/spotted.htm and through the NIH Neurosciences Microarray Consortium http://arrayconsortium.tgen.org/np2/public/overview.jsp

Proper citation: Songbird Brain Transcriptome Database (RRID:SCR_006182) Copy   

•   Source: SciCrunch Registry

http://galaxyproject.org/

Open, web-based platform providing bioinformatics tools and services for data intensive genomic research. Platform may be used as a service or installed locally to perform, reproduce, and share complete analyses. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Community has created Galaxy instances in many different forms and for many different applications including Galaxy servers, cloud services that support Galaxy instances, and virtual machines and containers that can be easily deployed for your own server.The Galaxy team is a part of BX at Penn State, and the Biology and Mathematics and Computer Science departments at Emory University.Training Infrastructure as a Service (TIaaS) is a service offered by some UseGalaxy servers to specifically support training use cases.

Proper citation: Galaxy (RRID:SCR_006281) Copy   

•   Source: SciCrunch Registry

http://divvy.ucsd.edu/

Software application for performing unsupervised machine learning and visualization with a focus on the clustering (separating data into groups) and dimensionality reduction (finding low dimensional structure in high dimensional data) subfields of machine learning. For visualization we provide support for both the whole dataset (e.g. a scatter plot) and points (e.g. transforming a particular point into an image). * Endlessly extensible. Every clusterer, reducer, point visualizer and dataset visualizer in Divvy is a plugin. We''ve provided a few big ones (K-means, PCA, scatter plot, &c.) and we''re hoping the community will use our plugin protocol to build many more. Each plugin defines its own UI, so your algorithm can look and behave the way that you want it to without top-down constraints. * Have lots of cores? Divvy is both task and data parallel. No longer will you be waiting for one algorithm to complete before you start another. Start as many as you want and keep using the UI. Only started one? With data parallelism we''ll still push your new MacBook Pro to 800% CPU utilization. * Part of your workflow: Export your clusterings and reductions to .csv and your visualizations to .png. Use your Matlab or R data with our Matlab/R to Divvy export tools available at http://github.com/jmlewis/divvy.

Proper citation: Divvy (RRID:SCR_006336) Copy   

•   Source: SciCrunch Registry

http://datastar.mannlib.cornell.edu/

A single library software prototype transitioning to a to an open-source platform ready for adoption and extension at other institutions wishing to provide research data sharing and discovery services. Datastar''''s ability to expose metadata about research datasets in a standard semantic format called Linked Data will be enhanced to support selective interchange of related information with VIVO, an open-source semantic researcher networking tool gaining prominence through adoption at multiple U.S. universities, in the federal government, and internationally.

Proper citation: DataStaR (RRID:SCR_006381) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/functionalconnectivitytoolbox/

MATLAB toolbox for performing functional connectivity analyses includes many of the most commonly-used approaches researchers have utilized to date for the identification of condition-dependent functional interactions between fMRI time-series obtained from two or more brain regions. The approaches are either bivariate or multivariate methods defined in time or frequency domains that emphasize distinct features of relationships among the time-series.

Proper citation: Functional Connectivity Toolbox (RRID:SCR_006394) Copy   

•   Source: SciCrunch Registry

http://www.mitre.org/news/digest/archives/2002/neuroinformatics.html

This resource''s long-term goal is to develop informatics methodologies and tools that will increase the creativity and productivity of neuroscience investigators, as they work together to use shared human brain mapping data to generate and test ideas far beyond those pursued by the data''s originators. This resource currently has four major projects supporting this goal: * Database tools: The goal of the NeuroServ project is to provide neuroscience researchers with automated information management tools that reduce the effort required to manage, analyze, query, view, and share their imaging data. It currently manages both structural magnetic resonance image (MRI) datasets and diffusion tensor image (DTI) datasets. NeuroServ is fully web-enabled: data entry, query, processing, reporting, and administrative functions are performed by qualified users through a web browser. It can be used as a local laboratory repository, to share data on the web, or to support a large distributed consortium. NeuroServ is based on an industrial-quality query middleware engine MRALD. NeuroServ includes a specialized neuroimaging schema and over 40 custom Java Server Pages supporting data entry, query, and reporting to help manage and explore stored images. NeuroServ is written in Java for platform independence; it also utilizes several open source components * Data sharing: DataQuest is a collaborative forum to facilitate the sharing of neuroimaging data within the neuroscience community. By publishing summaries of existing datasets, DataQuest enables researchers to: # Discover what data is available for collaborative research # Advertise your data to other researchers for potential collaborations # Discover which researchers may have the data you need # Discover which researchers are interested in your data. * Image quality: The approach to assessing the inherent quality of an image is to measure how distorted the image is. Using what are referred to as no-reference or blind metrics, one can measure the degree to which an image is distorted. * Content-based image retrieval: NIRV (NeuroImagery Retrieval & Visualization) is a work environment for advanced querying over imagery. NIRV will have a Java-based front-end for users to issue queries, run processing algorithms, review results, visualize imagery and assess image quality. NIRV interacts with an image repository such as NeuroServ. Users can also register images and will soon be able to filter searches based on image quality.

Proper citation: MITRE Neuroinformatics (RRID:SCR_006508) Copy   

•   Source: SciCrunch Registry

http://wiki.chasmsoftware.org/index.php/Main_Page

CHASM is a method that predicts the functional significance of somatic missense mutations observed in the genomes of cancer cells, allowing mutations to be prioritized in subsequent functional studies, based on the probability that they give the cells a selective survival advantage. SNV-Box is a database of pre-computed features of all possible amino acid substitutions at every position of the annotated human exome. Users can rapidly retrieve features for a given protein amino acid substitution for use in machine learning.

Proper citation: CHASM/SNV-Box (RRID:SCR_006445) Copy   

•   Source: SciCrunch Registry

http://flybase.org/

Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.

Proper citation: FlyBase (RRID:SCR_006549) Copy   

•   Source: SciCrunch Registry

http://bmcmicrobiol.biomedcentral.com/articles/10.1186/1471-2180-9-S1-S1

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 10, 2016. A consortium that created universal descriptors to describe functionally similar gene products and their attributes across all organisms. In 2004, the PAMGO interest group joined the GO consortium to extend the GO to include terms describing various processes related to microbe-host interactions. The organization uses a controlled vocabulary to set a process in place to describe plant associated microbes and their interactions with their plant-hosts. These higher order terms can describe gene products of all types of symbionts (e.g. parasites, commensals, and mutualists), including prokaryotes and eukaryotes that associate with plant or animal hosts. This initiative is a multi-institutional collaborative effort to pool information and research in: the bacteria Dickeya dadantii, Pseudomonas syringae pv tomato and Agrobacterium tumefaciens, the fungus Magnaporthe grisea, the oomycetes Phytophthora sojae and Phytophthora ramorum, and the nematode Meloidogyne hapla.

Proper citation: PAMGO (RRID:SCR_000022) Copy   

•   Source: SciCrunch Registry

http://www.uwyo.edu/buerkle/software/bamova/

Software that implements a Bayesian Analysis of Molecular Variance and different likelihood models for three different types of molecular data (including two models for high throughput sequence data).

Proper citation: bamova (RRID:SCR_000510) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/Urchin/contents.html

Laboratory modules designed for high school students covering sea urchin embryology including fertilization and development.

Proper citation: Sea Urchin Embryology (RRID:SCR_000460) Copy   

•   Source: SciCrunch Registry

http://www.gramene.org

Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.

Proper citation: Gramene (RRID:SCR_002829) Copy   

•   Source: SciCrunch Registry

http://sobekrepository.org/

Digital repository software written in C# / ASP.net for powering digital libraries in a Windows server environment. Standards-based repository keeps all files in METS/MODS packages. Several related applications are available as well and the libraries can work independently as great digital library resources. SobekCM allows users to discover online resources via semantic and full-text searches, as well as a variety of different browse mechanisms. For each digital resource in the repository there are a plethora of display options, which may be selected by an appropriately authenticated use. This repository includes online metadata editing and online submissions in support of institutional repositories.

Proper citation: SobekCM (RRID:SCR_003225) Copy   

•   Source: SciCrunch Registry

http://www.qgene.org/

A free, open-source, computationally efficient Java program for comparative analyses of QTL mapping data and population simulation that runs on any computer operating system. (entry from Genetic Analysis Software) It is written with a plug-in architecture for ready extensibility. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. Source code is available on request.

Proper citation: QGene (RRID:SCR_003209) Copy   

•   Source: SciCrunch Registry

http://compgen.bscb.cornell.edu/phast/

A freely available software package for comparative and evolutionary genomics that consists of about half a dozen major programs, plus more than a dozen utilities for manipulating sequence alignments, phylogenetic trees, and genomic annotations. For the most part, PHAST focuses on two kinds of applications: the identification of novel functional elements, including protein-coding exons and evolutionarily conserved sequences; and statistical phylogenetic modeling, including estimation of model parameters, detection of signatures of selection, and reconstruction of ancestral sequences. It consists of over 60,000 lines of C code.

Proper citation: PHAST (RRID:SCR_003204) Copy   

•   Source: SciCrunch Registry

http://datasharing.net

The U.S. National Institutes of Health Final NIH Statement on Sharing Research Data (NIH-OD-03-032) is now in effect. It specifies that all high-direct-cost NIH grant applications include plans for sharing of research data. To support and encourage collegial, enabling, and rewarding data sharing for neuroscience and beyond, the Laboratory of Neuroinformatics at Weill Medical College of Cornell University has established this site. A source of, and portal to, tools and proposals supporting the informed exchange of neuroscience data.

Proper citation: Datasharing.net (RRID:SCR_003312) Copy   

•   Source: SciCrunch Registry