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http://igdb.nsclc.ibms.sinica.edu.tw/

IGDB.NSCLC database is aiming to facilitate and prioritize identified lung cancer genes and microRNAs for pathological and mechanistic studies of lung tumorigenesis and for developing new strategies for clinical interventions. We integrated and curated various lung cancer genomic datasets to present # lung cancer genes with somatic mutations, experimental supports and statistic significance in association with clinicopathological features; # genomic alterations with copy number alterations (CNA) detected by high density SNP arrays, gain or loss regions detected by arrayed comparative genome hybridization (aCGH), and loss of heterozygosity (LOH) detected by microsatellite markers; # aberrant expression of genes and microRNAs detected by various microarrays. IGDB.NSCLC database provides user friendly interfaces and searching functions to display multiple layers of evidence for detecting lung cancer target genes and microRNAs, especially emphasizing on concordant alterations: # genes with altered expression located in the CNA regions; # microRNAs with altered expression located in the CNA regions; # somatic mutation genes located in the CNA regions; and # genes associated with clinicopathological features located in the CNA regions. These concordant altered genes and miRNAs should be prioritized for further basic and clinical studies.

Proper citation: IGDB.NSCLC (RRID:SCR_006048) Copy   

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http://www.hpppi.iicb.res.in/btox/

Database of Bacterial ExoToxins for Human is a database of sequences, structures, interaction networks and analytical results for 229 exotoxins, from 26 different human pathogenic bacterial genus. All toxins are classified into 24 different Toxin classes. The aim of DBETH is to provide a comprehensive database for human pathogenic bacterial exotoxins. DBETH also provides a platform to its users to identify potential exotoxin like sequences through Homology based as well as Non-homology based methods. In homology based approach the users can identify potential exotoxin like sequences either running BLASTp against the toxin sequences or by running HMMER against toxin domains identified by DBETH from human pathogenic bacterial exotoxins. In Non-homology based part DBETH uses a machine learning approach to identify potential exotoxins (Toxin Prediction by Support Vector Machine based approach).

Proper citation: DBETH - Database for Bacterial ExoToxins for Humans (RRID:SCR_005908) Copy   

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http://mint.bio.uniroma2.it/virusmint/

A virus protein interactions database that collects and annotates all the interactions between human and viral proteins and integrates this information in the human protein interaction network. It uses the PSI-MI standard and is fully integrated with the MINT database. You can search for any viral or human protein by entering either common names or database identifiers or display a complete viral interactome.

Proper citation: VirusMINT (RRID:SCR_005987) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/AmerUrological

AmerUrological's channel - YouTube are videos put out by the American Urological Association.

Proper citation: AmerUrological's channel - YouTube (RRID:SCR_005860) Copy   

•   Source: SciCrunch Registry

http://www.kabatdatabase.com/

The Kabat Database determines the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. The Kabat Database searching and analysis tools package is an ASP.NET web-based portal containing lookup tools, sequence matching tools, alignment tools, length distribution tools, positional correlation tools and much more. The searching and analysis tools are custom made for the aligned data sets contained in both the SQL Server and ASCII text flat file formats. The searching and analysis tools may be run on a single PC workstation or in a distributed environment. The analysis tools are written in ASP.NET and C# and are available in Visual Studio .NET 2003/2005/2008 formats. The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences at that time. Bence Jones proteins, mostly from human, were aligned, using the now-known Kabat numbering system, and a quantitative measure, variability, was calculated for every position. Three peaks, at positions 24-34, 50-56 and 89-97, were identified and proposed to form the complementarity determining regions (CDR) of light chains. Subsequently, antibody heavy chain amino acid sequences were also aligned using a different numbering system, since the locations of their CDRs (31-35B, 50-65 and 95-102) are different from those of the light chains. CDRL1 starts right after the first invariant Cys 23 of light chains, while CDRH1 is eight amino acid residues away from the first invariant Cys 22 of heavy chains. During the past 30 years, the Kabat database has grown to include nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules and other proteins of immunological interest. It has been used extensively by immunologists to derive useful structural and functional information from the primary sequences of these proteins.

Proper citation: Kabat Database of Sequences of Proteins of Immunological Interest (RRID:SCR_006465) Copy   

•   Source: SciCrunch Registry

http://humanmetabolism.org/

A comprehensive biochemical knowledge-base on human metabolism, this community-driven, consensus metabolic reconstruction integrates metabolic information from five different resources: * Recon 1, a global human metabolic reconstruction (Duarte et al, PNAS, 104(6), 1777-1782, 2007) * EHMN, Edinburgh Human Metabolic Network (Hao et al., BMC Bioinformatics 11, 393, 2010) * HepatoNet1, a liver metabolic reconstruction (Gille et al., Molecular Systems Biology 6, 411, 2010), * Ac/FAO module, an acylcarnitine/fatty acid oxidation module (Sahoo et al., Molecular bioSystems 8, 2545-2558, 2012), * a human small intestinal enterocytes reconstruction (Sahoo and Thiele, submitted). Additionally, more than 370 transport and exchange reactions were added, based on a literature review. Recon 2 is fully semantically annotated (Le Nov��re, N. et al. Nat Biotechnol 23, 1509-1515, 2005) with references to persistent and publicly available chemical and gene databases, unambiguously identifying its components and increasing its applicability for third-party users. Here you can explore the content of the reconstruction by searching/browsing metabolites and reactions. Recon 2 predictive model is available in the Systems Biology Markup Language format.

Proper citation: Recon x (RRID:SCR_006345) Copy   

•   Source: SciCrunch Registry

http://www.ala.org.au/

Online repository of information about Australian plants, animals, and fungi. Development started in 2006. The Commonwealth Scientific and Industrial Research Organisation is organisation significantly involved in development of ALA.

Proper citation: Atlas of Living Australia (RRID:SCR_006467) Copy   

•   Source: SciCrunch Registry

http://arxiv.org/

Electronic archive and distribution server for research articles providing open access to more than 850,000 e-prints in Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics. Users can retrieve papers via the web interface. Registered authors may use the web interface to submit their articles to arXiv. Authors can also update their submissions if they choose, though previous versions remain available. Listings of newly submitted articles in areas of interest are available via the web interface, via RSS feeds, and by subscription to automatic email alerts.

Proper citation: arXiv (RRID:SCR_006500) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

•   Source: SciCrunch Registry

http://www.disgenet.org

Database and discovery platform containing publicly available collections of genes and variants associated to human diseases. Integrates data from curated repositories, GWAS catalogues, animal models and scientific literature.

Proper citation: DisGeNET (RRID:SCR_006178) Copy   

•   Source: SciCrunch Registry

http://rapdb.dna.affrc.go.jp/

Database that provides the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. RAP-DB contains clone positions, structures and functions of genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison.

Proper citation: RAP-DB (RRID:SCR_006610) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/drugport/

DrugPort provides an analysis of the structural information available in the Protein Data Bank (PDB) relating to drug molecules and their protein targets. The drug-target data comes from the DrugBank database. You can search the entries by identifier, test or by protein sequence, or you can use the browse options in the menu on the left.

Proper citation: DrugPort (RRID:SCR_006573) Copy   

•   Source: SciCrunch Registry

http://www.botanical-dermatology-database.info/

BoDD is an electronic re-incarnation of BOTANICAL DERMATOLOGY by John Mitchell & Arthur Rook. This updated on-line version is made available to users with the kind permission of the original authors. The original edition has been digitized by Google Books. Although BoDD is actively being updated, updates are uploaded to the website only at about monthly intervals. A vast body of information collected by the Editor (Richard J. Schmidt PhD) awaits addition to the database. Users should be aware that some of the information that is currently accessible is neither accurate nor up-to-date. None of the information presented in BoDD should be regarded as a recommendation to treat any disease or disorder. The following are databases that are present in BoDD: -Balsaminaceae -Elaeagnaceae -Gelsemiaceae -Gentianaceae / Potaliacaceae -Hydroleaceae -Loganiaceae / Spigeliaceae / Strychnaceae -Martyniaceae -Orobanchaceae -Phrymaceae -Sabiaceae -Tamaricaceae

Proper citation: BoDD (RRID:SCR_006592) Copy   

•   Source: SciCrunch Registry

http://stemcelldb.nih.gov/public.do

Database characterizing and comparing pluripotent human stem cells. The growth and culture conditions of all 21 human embryonic stem cell lines approved under the August 2001 Presidential Executive Order have been analyzed. Available to the scientific community are the results of our rigorous characterization of these cell lines at a more advanced level.

Proper citation: StemCellDB (RRID:SCR_006305) Copy   

•   Source: SciCrunch Registry

http://www.suba.bcs.uwa.edu.au/

SUBA provides a powerful tool to investigate subcellular localization in Arabidopsis. SUBA houses large scale proteomic and GFP localization sets from cellular compartments of Arabidopsis, and also contains pre-compiled bioinformatic predictions for protein subcellular localizations. The Database functions through the unification of disparate datasets and through the provision of a web accessible interface for the construction of user based queries resulting in a one-stop-shop for protein localization in this model plant. Subcellular localization information can contribute towards our understanding of protein function, protein redundancy and of biological inter-relationships. In an attempt to get a clearer picture of our experimental data and to more generally understand subcellular partitioning we have brought together various data sources to build SUBA.

Proper citation: SUB-cellular location database for Arabidopsis proteins II (RRID:SCR_006668) Copy   

•   Source: SciCrunch Registry

http://research.nhgri.nih.gov/CGD/

Manually curated database of all conditions with known genetic causes, focusing on medically significant genetic data with available interventions. Includes gene symbol, conditions, allelic conditions, inheritance, age in which interventions are indicated, clinical categorization, and general description of interventions/rationale. Contents are intended to describe types of interventions that might be considered. Includes only single gene alterations and does not include genetic associations or susceptibility factors related to more complex diseases.

Proper citation: Clinical Genomic Database (RRID:SCR_006427) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/genomes/PLANTS/PGC-word.pdf

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. A database of completed or in-progress sequenced plant genomes. The list of plant sequencing projects in this page includes those that have reached the stage where active sequence determination is currently producing, or is expected to produce in the near future. In addition, GenBank accession are provided toward the goal of determining the sequence of that plant genome.

Proper citation: Plant Genomes Central (RRID:SCR_006541) Copy   

•   Source: SciCrunch Registry

http://tardis.nibio.go.jp/homstrad/

A curated database of structure-based alignments for homologous protein families. All known protein structure are clustered into homologous families (i.e., common ancestry), and the sequences of representative members of each family are aligned on the basis of their 3D structures using the programs MNYFIT, STAMP and COMPARER. These structure-based alignments are annotated with JOY and examined individually.

Proper citation: HOMSTRAD - Homologous Structure Alignment Database (RRID:SCR_006544) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.intec.ugent.be/magic/

Web based interface for exploring and analyzing a comprehensive maize-specific cross-platform expression compendium. This compendium was constructed by collecting, homogenizing and formally annotating publicly available microarrays from Gene Expression Omnibus (GEO), and ArrayExpress.

Proper citation: Magic (RRID:SCR_006406) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage/Pfalciparum

Database of the most recent sequence updates and annotations for the P. falciparum genome. New annotations are constantly being added to keep up with published manuscripts and feedback from the Plasmodium research community. You may search by Protein Length, Molecular Mass, Gene Type, Date, Location, Protein Targeting, Transmembrane Helices, Product, GO, EC, Pfam ID, Curation and Comments, and Dbxrefs. BLAST and other tools are available. The P. falciparum 3D7 nuclear genome is 23.3 Mb in size, with a karyotype of 14 chromosomes. The G+C content is approximately 19%. The P. falciparum genome is undergoing re-annotation. This process started in October 2007 with a weeklong workshop co-organized by staff from the Wellcome Trust Sanger Intistute and the EuPathDB team. Ongoing curation and sequence checking is being carried out by the Pathogen Genomics group. Plasmodium falciparum is the most deadly of the five Plasmodium species that cause human malaria. Malaria has a massive impact on human health; it is the worlds second biggest killer after tuberculosis. Around 300 million clinical cases occur each year resulting in between 1.5 - 2.7 million deaths annually, the majority in sub-saharan Africa. It is estimated that 3,000 children under the age of five years fall victim to malaria each day. Around 40% of the worlds population are at risk. In collaboration with EuPathDB, genomic sequence data and annotations are regularly deposited on PlasmoDB where they can be integrated with other datasets and queried using customized queries.

Proper citation: GeneDB Pfalciparum (RRID:SCR_006567) Copy   

•   Source: SciCrunch Registry