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https://cab.spbu.ru/software/spades/
Software package for assembling single cell genomes and mini metagenomes. Uses short read sets as input. Used for genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. Works with Illumina or IonTorrent reads and can provide hybrid assemblies using PacBio, Oxford Nanopore and Sanger reads. Intended for small genomes like bacterial or fungal., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SPAdes (RRID:SCR_000131) Copy
This page contains the Influenza Surveillance Report during 2008-2009 Influenza Season Week 15, ending April 18, 2009.
Proper citation: FluView: A Weekly Influenza Surveillance Report (RRID:SCR_001118) Copy
http://www.ncbi.nlm.nih.gov/guide/sitemap/
The National Center for Biotechnology Information''s listing of resources. Sort by alphabetical character, Databases, Downloads, Submissions, Tools and How-To; or by Topic: Chemicals & Bioassays; Data & Software; DNA & RNA; Domains & Structures; Genes & Expression; Genetics & Medicine; Genomes & Maps; Homology; Literature; Proteins; Sequence Analysis; Taxonomy; Training & Tutorials; Variation.
Proper citation: NCBI Resource List (RRID:SCR_005628) Copy
http://www.nih.gov/science/brain/
Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.
Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy
XSEDE is a single virtual system that scientists can use to interactively share computing resources, data and expertise. People around the world use these resources and services things like supercomputers, collections of data and new tools to improve our planet. XSEDE resources may be broadly categorized as follows: High Performance Computing, High Throughput Computing, Visualization, Storage, and Data Services. Many resources provide overlapping functionality across categories. Scientists, engineers, social scientists, and humanists around the world - many of them at colleges and universities - use advanced digital resources and services every day. Things like supercomputers, collections of data, and new tools are critical to the success of those researchers, who use them to make our lives healthier, safer, and better. XSEDE integrates these resources and services, makes them easier to use, and helps more people use them. XSEDE supports 16 supercomputers and high-end visualization and data analysis resources across the country. Digital services, meanwhile, provide users with seamless integration to NSF''s high-performance computing and data resources. XSEDE''s integrated, comprehensive suite of advanced digital services will federate with other high-end facilities and with campus-based resources, serving as the foundation for a national cyberinfrastructure ecosystem. Common authentication and trust mechanisms, global namespace and filesystems, remote job submission and monitoring, and file transfer services are examples of XSEDE''s advanced digital services. XSEDE''s standards-based architecture allows open development for future digital services and enhancements. XSEDE also provides the expertise to ensure that researchers can make the most of the supercomputers and tools.
Proper citation: XSEDE - Extreme Science and Engineering Discovery Environment (RRID:SCR_006091) Copy
http://reproducibility.stanford.edu/
Center with the goal of harnessing high-performance computing to make neuroscience research more reliable.Provide researchers with tools to analyze their data in ways that focus on the reproducibility of the results through the OpenfMRI ( OpenNeuro ) and Neurovault projects.
Proper citation: Stanford Center for Reproducible Neuroscience (RRID:SCR_016684) Copy
Web portal for the administration of Norwegian e-Infrastructure for Life Sciences. Enables Norwegian life scientists and their international collaborators to store, share, archive, and analyse their genomics scale data. NeLS is one of the packages of the ELIXIR.NO project.
Proper citation: NeLS (RRID:SCR_016301) Copy
Portal for Twins Research Australia. Brings twins and researchers together for vital health research in twins.
Proper citation: Twins Research Australia (RRID:SCR_017485) Copy
Portal as central source of Australian open government data. Used to find, explore and reuse Australia public data. Anyone can access the anonymised public data published by federal, state and local government agencies, publicly funded research data and datasets from private institutions that are in public interest.
Proper citation: Australian Government Data Portal (RRID:SCR_019159) Copy
http://www.clcbio.com/products/clc-main-workbench/
A suite of software for DNA, RNA and protein sequence data analysis. The software allows for the analysis and visualization of Sanger sequencing data as well as gene expression analysis, molecular cloning, primer design, phylogenetic analyses, and sequence data management.
Proper citation: CLC Main Workbench (RRID:SCR_000354) Copy
http://www.neuroconstruct.org/
Software for simulating complex networks of biologically realistic neurons, i.e. models incorporating dendritic morphologies and realistic cell membrane conductance, implemented in Java and generates script files for the NEURON and GENESIS simulators, with support for other simulation platforms (including PSICS and PyNN) in development. neuroConstruct is being developed in the Silver Lab in the Department of Neuroscience, Physiology and Pharmacology at UCL and uses the latest NeuroML specifications, including MorphML, ChannelML and NetworkML. Some of the key features of neuroConstruct are: Creation of networks of biologically realistic neurons, positioned in 3D space. Complex connectivity patterns between cell groups can be specified for the networks. Can import morphology files in GENESIS, NEURON, Neurolucida, SWC and MorphML format for inclusion in network models. Simulations can be run on the NEURON or GENESIS platforms. Cellular processes (synapses/channel mechanisms) can be imported from native script files or created in ChannelML. Recording of simulation data generated by the simulation and visualization/analysis of data. Stored simulation runs can be viewed and managed through the Simulation Browser interface.
Proper citation: neuroConstruct (RRID:SCR_007197) Copy
http://www.fmrib.ox.ac.uk/fsl/
Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.
Proper citation: FSL (RRID:SCR_002823) Copy
http://abacus.gene.ucl.ac.uk/software/indelible/
Software that generates nucleotide, amino acid and codon sequence data by simulating insertions and deletions (indels) as well as substitutions. It is used for biological sequence simulation of multi-partitioned nucleotide, amino-acid, or codon data sets through the processes of insertion, deletion, and substitution in continuous time.
Proper citation: Indelible (RRID:SCR_016163) Copy
https://picrust.github.io/picrust/
Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.
Proper citation: PICRUSt (RRID:SCR_016855) Copy
The Center develops conceptual models, computational infrastructure, an integrated knowledge repository, and query and analysis tools that enable scientists to effectively access and integrate the wealth of biological data. The National Center for Integrative Biomedical Informatics (NCIBI) was founded in October 2005 and is one of seven National Centers for Biomedical Computing (NCBC) in the NIH Roadmap. NCIBI is based at the University of Michigan as a part of the Center for Computational Medicine and Biology (CCMB). NCIBI is composed of biomedical researchers, computational biologists, computer scientists, developers and human-computer interaction specialists organized into seven major core functions. They work in interdisciplinary teams to collectively develop tools that are not only computationally powerful but also biologically relevant and meaningful. The four initial Driving Biological Projects (prostate cancer progression, Type 1 and type 2 diabetes and bipolar disorder) provide the nucleation point from which tool development is informed, launched, and tested. In addition to testing tools for function, a separate team is dedicated to testing usability and user interaction that is a unique feature of this Center. Once tools are developed and validated the goal of the Center is to share and disseminate data and software throughout the research community both internally and externally. This is achieved through various mechanisms such as training videos, tutorials, and demonstrations and presentations at national and international scientific conferences. NCIBI is supported by NIH Grant # U54-DA021519.
Proper citation: National Center for Integrative Biomedical Informatics (RRID:SCR_001538) Copy
http://www.cs.cmu.edu/~schneide/tut5/node42.html
A model evaluation method for training someone to read data. There are three methods: the holdout method, K-fold cross validation, and leave-one-out cross validation.
Proper citation: Cross Validation (RRID:SCR_000702) Copy
Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.
Proper citation: Bioconductor (RRID:SCR_006442) Copy
https://github.com/EpistasisLab/ReBATE
Open source software Python package to compare relief based feature selection algorithms used in data mining. Used for feature selection in any bioinformatics problem with potentially predictive features and target outcome variable, to detect feature interactions without examination of all feature combinations, to detect features involved in heterogeneous patterns of association such as genetic heterogeneity .
Proper citation: ReBATE (RRID:SCR_017139) Copy
https://edspace.american.edu/openbehavior/
Repository of open source tools for behavioral neuroscience research. OpenBehavior features hardware (tools, devices, apparatuses), as well as software for data acquisition and analysis and for the investigation of animal behavior and cognition. Dedicated to accelerating research through promotion of collaboration and open source projects.
Proper citation: OpenBehavior (RRID:SCR_015938) Copy
https://www.thermofisher.com/order/catalog/product/CHROMELEON7
Software system to support chromatography operations, to ensure data quality and manage all the analytical processes from instrument control, to raw data storage and processing, through to generating the final results.
Proper citation: Chromeleon Chromatography Data System (CDS) Software (RRID:SCR_016874) Copy
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