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DCC DIFFUSE Standards Frameworks is a browsable database with information on both standards and the organizations which sponsor them. Entries can currently be browsed either by category, alphabetically by title or by sponsoring body. Although no further work on DIFFUSE is planned, frameworks that were created remain an accessible and relevant resource. These include frameworks developed from existing publications or specifications as well as those developed specifically for the DIFFUSE project. The DCC DIFFUSE Standards Frameworks were developed in partnership with a number of organizations with the aim of presenting searchable frameworks of standards relevant to digital curation and preservation. DCC DIFFUSE Standards Frameworks provides information about sets of standards, used by specific domains, which enable curation and preservation of, and access to, data across all stages of the DCC Curation Lifecycle Model. The project maintains information about current and emerging standards and specifications which are used. Entries for individual standards and specifications include: * Links to database entries concerning sponsoring bodies * Links to the official documentation * Links to additional documentation such as user guides, tutorials, implementation profiles and registers, XML DTD or Schema * A description of the scope of the standard or specification * A description of the development of the standard or specification * Practical examples of the standard or specification in use Entries for sponsoring bodies include: * Contact details * Organizational objectives * Areas of activity * Membership details DCC DIFFUSE includes published standards which are included in frameworks used for curation and preservation of access to digital material, for example: * Standards ratified by national or international standards organizations or bodies * Standards developed by, or ratified by, professional organizations * Publicly available specifications developed by, or ratified by, a consortia or fora

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• SciCrunch
• 15 years ago - by Anonymous

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

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• SciCrunch
• 15 years ago - by Anonymous

Recognized as the world authority on chemical nomenclature, terminology, standardized methods for measurement, atomic weights and many other critically evaluated data, this scientific, international, non-governmental and objective body addresses many global issues involving the chemical sciences. It serves to advance the worldwide aspects of the chemical sciences and to contribute to the application of chemistry in the service of Humankind. The Union sponsors major international meetings that range from specialized scientific symposia to CHEMRAWN meetings with societal impact. * Projects: IUPAC encourages the submission of projects in all areas of chemistry relevant to its work. * Publications: IUPAC publishes books, journals, electronic resources, and issues many reports in all areas of chemistry * Conferences: Each year IUPAC sponsors a large number of symposia that cover a wide range of specialized topics in chemistry. * Members and bodies: Chemists throughout the world are engaged on a voluntary basis in the scientific work of IUPAC.

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• SciCrunch
• 15 years ago - by Anonymous

Data files for a high resolution three dimensional (3D) structure of the rat hippocampus reconstructed from histological sections. The data files (supplementary data for Ropireddy et al., Neurosci., 2012 Mar 15;205:91-111) are being shared on the Windows Live cloud space provided by Microsoft. Downloadable data files include the Nissl histological images, the hippocampus layer tracings that can be visualized alone or superimposed to the corresponding Nissl images, the voxel database coordinates, and the surface rendering VRML files. * Hippocampus Nissl Images: The high resolution histological Nissl images obtained at 16 micrometer inter-slice distance for the Long-Evans rat hippocampus can be downloaded or directly viewed in a browser. This dataset consists of 230 jpeg images that cover the hippocampus from rostral to caudal poles. This image dataset is uploaded in seven parts as rar files. * Hippocampus Layer Tracings: The seven hippocampus layers ''ML, ''GC'', ''HILUS'' in DG and ''LM'', ''RAD'', ''PC'', ''OR'' in CA were segmented (traced) using the Reconstruct tool which can be downloaded from Synapse web. This tool outputs all the tracings for each image in XML format. The XML tracing files for all these seven layers for each of the above Nissl images are zipped into one file and can be downloaded. * Hippocampus VoxelDB: The 3D hippocampus reconstructed is volumetrically transformed into 16 micrometer sized voxels for all the seven layers. Each voxel is reported according to multiple coordinate systems, namely in Cartesian, along the natural hippocampal dimensions, and in reference to the canonical brain planes. The voxel database file is created in ascii format. The single voxel database file was split into three rar archive files. Please note that the three rar archive files should be downloaded and decompressed in a single directory in order to obtain the single voxel data file (Hippocampus-VoxelDB.txt). * 3D Surface Renderings: This is a rar archive file with a single VRML file containing the surface rendering of DG and CA layers. This VRML file can be opened and visualized in any VRML viewer, e.g. the open source software view3dscene. * 3D Hippocampus Movie: This movie contains visualization of the 3D surface renderings of CA (blue) and DG (red) inner and outer boundaries; neuronal embeddings of DG granule and CA pyramidal dendritic arbors; potential synapses between CA3b interneuron axon and pyramidal dendrite, and between CA2 pyramidal axon and CA pyramidal dendrites.

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• SciCrunch
• 15 years ago - by Anonymous

An International Union of Pure and Applied Chemistry (IUPAC) subcommittee that deals with individual projects related to technique-specific data standards as well as generic issues. There are worrying gaps in the coverage of known chemistry by reference spectroscopic databases, which are unlikely to be filled by the activities of the commercial sector alone. The IS-DB offers the scientific community the opportunity to share their spectra and develop a vital resource for future generations. Such a collection of spectra will help to provide significant improvements in human health, new materials, environmental protection, sustainable development and educational progress. XML in Chemistry is a new IUPAC initiative to bring a degree of regulation to this important and rapidly expanding field. They aim to facilitate the validation of data dictionaries for various groups developing ontologies expressed in XML in the broad field of Chemistry. This will help to reduce duplication of effort around the world and allow development projects to build on the work previous groups concentrating on their own innovative goals rather than wasting time and effort re-inventing wheels. IUPAC encourages the submission of projects in all areas of chemistry relevant to its work. If you believe there is a need for a new scientific data standard in your field and wish to know more about how to form a limited term task group to get the standard developed please contact the subcommittee.

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• SciCrunch
• 15 years ago - by Anonymous

A tool for genome assembly and variation analysis from sequence data. You can use it to discover and genotype variants on single or multiple haploid or diploid samples. If you have multiple samples, you can use Cortex to look specifically for variants that distinguish one set of samples (eg phenotype=X, cases, parents, tumour) from another set of samples (eg phenotype=Y, controls, child, normal). cortex_var features * Variant discovery by de novo assembly - no reference genome required * Supports multicoloured de Bruijn graphs - have multiple samples loaded into the same graph in different colours, and find variants that distinguish them. * Capable of calling SNPs, indels, inversions, complex variants, small haplotypes * Extremely accurate variant calling - see our paper for base-pair-resolution validation of entire alleles (rather than just breakpoints) of SNPs, indels and complex variants by comparison with fully sequenced (and finished) fosmids - a level of validation beyond that demanded of any other variant caller we are aware of - currently cortex_var is the most accurate variant caller for indels and complex variants. * Capable of aligning a reference genome to a graph and using that to call variants * Support for comparing cases/controls or phenotyped strains * Typical memory use: 1 high coverage human in under 80Gb of RAM, 1000 yeasts in under 64Gb RAM, 10 humans in under 256 Gb RAM

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• SciCrunch
• 13 years ago - by Anonymous

NASA leads the nation on a great journey of discovery, seeking new knowledge and understanding of our planet Earth, our Sun and solar system, and the universe out to its farthest reaches and back to its earliest moments of existence. NASA's Science Mission Directorate (SMD) and the nation's science community use space observatories to conduct scientific studies of the Earth from space to visit and return samples from other bodies in the solar system, and to peer out into our Galaxy and beyond. NASA's science program seeks answers to profound questions that touch us all: * How and why are Earth's climate and the environment changing? * How and why does the Sun vary and affect Earth and the rest of the solar system? * How do planets and life originate? * How does the universe work, and what are its origin and destiny? * Are we alone? This is NASA's science vision: using the vantage point of space to achieve with the science community and our partners a deep scientific understanding of our planet, other planets and solar system bodies, the interplanetary environment, the Sun and its effects on the solar system, and the universe beyond. In so doing, we lay the intellectual foundation for the robotic and human expeditions of the future while meeting today's needs for scientific information to address national concerns, such as climate change and space weather. At every step we share the journey of scientific exploration with the public and partner with others to substantially improve science, technology, engineering and mathematics (STEM) education nationwide.

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• SciCrunch
• 15 years ago - by Anonymous

Software to cluster genes based on Poisson or Negative-Binomial model for RNA-Seq or other digital gene expression (DGE) data.

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• SciCrunch
• 13 years ago - by Anonymous

The Earth Observing System Data and Information System (EOSDIS) is a major core capability within NASA''s Earth Science Data Systems Program. EOSDIS ingests, processes, archives and distributes data from a large number of Earth observing satellites. EOSDIS consists of a set of processing facilities and Earth Science Data Centers distributed across the United States and serves hundreds of thousands of users around the world, providing hundreds of millions of data files each year covering many Earth science disciplines. In order to serve the needs of a broad and diverse community of users, NASA''s Earth Science Data Systems Program is comprised of both Core and Community data system elements. Core data system elements reflect NASA''s responsibility for managing Earth science satellite mission data characterized by the continuity of research, access, and usability. The core comprises all the hardware, software, physical infrastructure, and intellectual capital NASA recognizes as necessary for performing its tasks in Earth science data system management. Community data system elements are those pieces or capabilities developed and deployed largely outside of NASA core elements and are characterized by their evolvability and innovation. Successful applicable elements can be infused into the core, thereby creating a vibrant and flexible, continuously evolving infrastructure. NASA''s Earth Science program was established to use the advanced technology of NASA to understand and protect our home planet by using our view from space to study the Earth system and improve prediction of Earth system change. To meet this challenge, NASA promotes the full and open sharing of all data with the research and applications communities, private industry, academia, and the general public. NASA was the first agency in the US, and the first space agency in the world, to couple policy and adequate system functionality to provide full and open access in a timely manner - that is, with no period of exclusive access to mission scientists - and at no cost. NASA made this decision after listening to the user community, and with the background of the then newly-formed US Global Change Research Program, and the International Earth Observing System partnerships. Other US agencies and international space agencies have since adopted similar open-access policies and practices. Since the adoption of the Earth Science Data Policy adoption in 1991, NASA''s Earth Science Division has developed policy implementation, practices, and nomenclature that mission science teams use to comply with policy tenets. Data System Standards NASA''s Earth Science Data Systems Groups anticipate that effective adoption of standards will play an increasingly vital role in the success of future science data systems. The Earth Science Data Systems Standards Process Group (SPG), a board composed of Earth Science Data Systems stakeholders, directs the process for both identification of appropriate standards and subsequent adoption for use by the Earth Science Data Systems stakeholders.

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• SciCrunch
• 15 years ago - by Anonymous

EPA data standards are a means to promote the efficient sharing of environmental information among US EPA, states, Tribes, local governments, the private sector, and other information trading partners. EPA''s Data Standards are managed by the Data Standards Branch (DSB) within the Office of Environmental Information (OEI). DSB works closely with Federal agencies, states, tribes, and other information trading partners to develop data standards. By its nature the program is a part of EPA''s Enterprise-wide Data Architecture and EPA''s Quality Systems. The use of data standards across EPA''s multiple program offices provides consistently defined and formatted data elements and sets of data values which provide the public access to more meaningful data. The benefits of EPA''s data standards are those as are applicable to any standard: * They are developed by subject matter experts coming to common consensus on how to solve business problems so represents the best solution * They are harder to develop than non-standards, but are more economical in the long term because you can use the same code or presentation and publishing mechanisms to provide access to information * They enable transparency and understanding use of standards promotes common, clear meanings for data that is often reused * They enable access - the same well understood terms, codes, and data structures can be used for data retrieval * They encourage and enable reuse of data and software for multiple purposes * Mappings to standards allow comparisons even when data isn''t standardized solves the environmental interest problem between programs and states * They provide consistent results during data retrieval Standards also promote quality EPA''s goal is high quality information delivered in an efficient way to the people who need it.

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• SciCrunch
• 15 years ago - by Anonymous

This website provides several different RNA databases for researchers. The first, the Non-canonical Base Pair Database, provides access to all the RNA structures in which a particular rare base pair has been found. Another, the Prokaryotic 16S rRNA Signature Database, offers local sequence segments that are highly characteristic of particular organisms or groups of organisms. The third, the Prokaryotic 16S rRNA Signature Database II, provides generalized ribosomal RNA data.

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• SciCrunch
• 17 years ago - by Anonymous

Public research university with its main campus in Lawrence, Kansas, and several satellite campuses, research and educational centers, medical centers, and classes across the state of Kansas.

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• SciCrunch
• 17 years ago - submitted by Stephen Larson

A university in Germany.

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• SciCrunch
• 17 years ago - submitted by Stephen Larson

A stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data.

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• SciCrunch
• 13 years ago - by Anonymous

A software program for scaffolding contigs produced by fragment assemblers using mate pair data such as those generated by ABI SOLiD or Illumina Genome Analyzer.

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• SciCrunch
• 13 years ago - by Anonymous

A generic algorithm for scaffolding next-generation sequencing assemblies.

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• SciCrunch
• 13 years ago - by Anonymous

An algorithm to use optical map information directly within the de Bruijn graph framework to help produce an accurate assembly of a genome that is consistent with the optical map information provided. AGORA takes as input two data structures: OpMap ? an ordered list of fragment sizes representing the optical map; and Edges ? a list of de Bruijn graph edges with their corresponding sequences.

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• SciCrunch
• 13 years ago - by Anonymous

Web-accessible digital brain atlas of the common marmoset (Callithrix jacchus), prepared from histological sections of the marmoset brain using various staining techniques.

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• SciCrunch
• 15 years ago - by Anonymous

Software for scaffolding to address some of the challenges encountered when analyzing metagenomes. Scaffolding represents the task of ordering and orienting contigs by incorporating additional information about their relative placement along the genome. While most other scaffolders are closely tied to a specific assembly program, Bambus accepts the output from most current assemblers and provides the user with great flexibility in choosing the scaffolding parameters. In particular, Bambus is able to accept contig linking data other than specified by mate-pairs. Such sources of information include alignment to a reference genome (Bambus can directly use the output of MUMmer), physical mapping data, or information about gene synteny.

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• SciCrunch
• 13 years ago - by Anonymous

Service to align and optionally taxonomically classify your rRNA gene sequences. The results can be combined with any other sequences aligned by SINA or taken from the SILVA databases by concatenation of FASTA files or using the ARB MERGE tool. Note: Submission is currently limited to at most 1000 sequences of at most 6000 bases each. If your requirements exceed this limitation, get Opens internal link in current windowSINA for local installation.

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• SciCrunch
• 13 years ago - by Anonymous