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>>>!!!<<< SMD has been retired. After approximately fifteen years of microarray-centric research service, the Stanford Microarray Database has been retired. We apologize for any inconvenience; please read below for possible resolutions to your queries. If you are looking for any raw data that was directly linked to SMD from a manuscript, please search one of the public repositories. NCBI Gene Expression Omnibus EBI ArrayExpress All published data were previously communicated to one (or both) of the public repositories. Alternatively, data for publications between 1997 and 2004 were likely migrated to the Princeton University MicroArray Database, and are accessible there. If you are looking for a manuscript supplement (i.e. from a domain other than smd.stanford.edu), perhaps try searching the Internet Archive: Wayback Machine https://archive.org/web/ . >>>!!!<<< The Stanford Microarray Database (SMD) is a DNA microarray research database that provides a large amount of data for public use.
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All observations obtained with the Parkes radio telescope are made available to the general community after an embargo period. Usually this embargo period is set to 18 months after the observation. The catalogue includes all published rotation-powered pulsars, including those detected only at high energies. It also includes Anomalous X-ray Pulsars (AXPs) and Soft Gamma-ray Repeaters (SGRs) for which coherent pulsations have been detected. However, it excludes accretion-powered pulsars such as Her X-1 and the recently discovered X-ray millisecond pulsars. ATNF Pulsar catalogue contains information on all published pulsars, with complete bibliographic information. For professional astronomers, a more detailed "Expert" web interface is available allowing access to parameters of specialist interest. The catalogue can also be accessed using a command-line interface on unix or linux systems.
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. OMIM is authored and edited at the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, under the direction of Dr. Ada Hamosh. Its official home is omim.org.
BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
<<<!!!<<< Efforts to obtain renewed funding after 2008 were unfortunately not successful. PANDIT has therefore been frozen since November 2008, and its data are not updated since September 2005 when version 17.0 was released (corresponding to Pfam 17.0). The existing data and website remain available from these pages, and should remain stable and, we hope, useful. >>>!!!>>> PANDIT is a collection of multiple sequence alignments and phylogenetic trees. It contains corresponding amino acid and nucleotide sequence alignments, with trees inferred from each alignment. PANDIT is based on the Pfam database (Protein families database of alignments and HMMs), and includes the seed amino acid alignments of most families in the Pfam-A database. DNA sequences for as many members of each family as possible are extracted from the EMBL Nucleotide Sequence Database and aligned according to the amino acid alignment. PANDIT also contains a further copy of the amino acid alignments, restricted to the sequences for which DNA sequences were found.
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<<<!!!<<< The repository is no longer available. >>>!!!>>>The information is accessible through PubChem:https://pubchem.ncbi.nlm.nih.gov/. Help for HSDB Users in PubChem PDF: https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.pdf Help for HSDB Users in PubChem Web Page: https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.html <<<!!!>>>
The CERN Open Data portal is the access point to a growing range of data produced through the research performed at CERN. It disseminates the preserved output from various research activities, including accompanying software and documentation which is needed to understand and analyze the data being shared.
>>>!!!<<<The repository is offline >>>!!!<<< The Space Physics Interactive Data Resource from NOAA's National Geophysical Data Center allows solar terrestrial physics customers to intelligently access and manage historical space physics data for integration with environment models and space weather forecasts.
<<<!!!<<<The repository is no longer available. The printversion see: https://www.taylorfrancis.com/books/mono/10.1201/9781003220435/encyclopedia-astronomy-astrophysics-murdin >>>!!!>>> This unique resource covers the entire field of astronomy and astrophysics and this online version includes the full text of over 2,750 articles, plus sophisticated search and retrieval functionality, links to the primary literature, and is frequently updated with new material. An active editorial team, headed by the Encyclopedia's editor-in-chief, Paul Murdin, oversees the continual commissioning, reviewing and loading of new and revised content.In a unique collaboration, Nature Publishing Group and Institute of Physics Publishing published the most extensive and comprehensive reference work in astronomy and astrophysics in both print and online formats. First published as a four volume print edition in 2001, the initial Web version went live in 2002, and contained the original print material and was rapidly supplemented with numerous updates and newly commissioned material. Since July 2006 the Encyclopedia is published solely by Taylor & Francis.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies