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http://www.knockoutmouse.org/

Database of the international consortium working together to mutate all protein-coding genes in the mouse using a combination of gene trapping and gene targeting in C57BL/6 mouse embryonic stem (ES) cells. Detailed information on targeted genes is available. The IKMC includes the following programs: * Knockout Mouse Project (KOMP) (USA) ** CSD, a collaborative team at the Children''''s Hospital Oakland Research Institute (CHORI), the Wellcome Trust Sanger Institute and the University of California at Davis School of Veterinary Medicine , led by Pieter deJong, Ph.D., CHORI, along with K. C. Kent Lloyd, D.V.M., Ph.D., UC Davis; and Allan Bradley, Ph.D. FRS, and William Skarnes, Ph.D., at the Wellcome Trust Sanger Institute. ** Regeneron, a team at the VelociGene division of Regeneron Pharmaceuticals, Inc., led by David Valenzuela, Ph.D. and George D. Yancopoulos, M.D., Ph.D. * European Conditional Mouse Mutagenesis Program (EUCOMM) (Europe) * North American Conditional Mouse Mutagenesis Project (NorCOMM) (Canada) * Texas A&M Institute for Genomic Medicine (TIGM) (USA) Products (vectors, mice, ES cell lines) may be ordered from the above programs.

Proper citation: International Knockout Mouse Consortium (RRID:SCR_005574) Copy   

•   Source: SciCrunch Registry

http://swissregulon.unibas.ch/fcgi/sr/swissregulon

A database of genome-wide annotations of regulatory sites. The predictions are based on Bayesian probabilistic analysis of a combination of input information including: * Experimentally determined binding sites reported in the literature. * Known sequence-specificities of transcription factors. * ChIP-chip and ChIP-seq data. * Alignments of orthologous non-coding regions. Predictions were made using the PhyloGibbs, MotEvo, IRUS and ISMARA algorithms developed in their group, depending on the data available for each organism. Annotations can be viewed in a Gbrowse genome browser and can also be downloaded in flat file format.

Proper citation: SwissRegulon (RRID:SCR_005333) Copy   

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http://ssd.rbvi.ucsf.edu/

The SSD has been developed to address the need for resources and tools for understanding large sets of superpositions in order to understand evolutionary relationships and to make predictions of function. We have therefore created the Structure Superposition Database (SSD) for accessing, viewing and understanding large sets of structure superposition data. It contains the results of pairwise, all-by-all superpositions of a representative set of 115 (beta/alpha) barrel structures (TIM barrels). The initial implementation of the SSD contains the results of pairwise, all-by-all superpositions of a representative set of 115 (/alpha)8 barrel structures (TIM barrels). Future plans call for extending the database to include representative structure superpositions for many additional folds. The SSD can be browsed with a user interface module developed as an extension to Chimera, an extensible molecular modeling program. Features of the user interface module facilitate viewing multiple superpositions together.

Proper citation: Structure Superposition Database (RRID:SCR_005236) Copy   

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http://neurosphere.wordpress.com/

This blog belongs to me, Dave J Hayes PhD, a Neuroscientist at the University of Ottawa''s Institute of Mental Health Research. My research focuses on the neuroscience of motivation and emotion particularly regarding how brains and people respond to aversive and rewarding things in their environment. A neurosphere is a free-floating group of neural stem cells which can multiply, outside of their natural environment, and retain the ability to differentiate into functional brain cells. I don''t work on neurospheres. However, i like the metaphor of a group of people coming together, outside of their natural environment, through their interest in all things neuro which, incidentally, is everything. The sphere of human thought.

Proper citation: neurosphere (RRID:SCR_005478) Copy   

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http://transpogene.tau.ac.il/

A publicly available database of Transposed elements (TEs) which are located within protein-coding genes of 7 organisms: human, mouse, chicken, zebrafish, fruilt fly, nematode and sea squirt. Using TranspoGene the user can learn about the many aspects of the effect these TEs have on their hosting genes, such as: exonization events (including alternative splicing-related data), insertion of TEs into introns, exons, and promoters, specific location of the TE over the gene, evolutionary divergence of the TE from its consensus sequence and involvement in diseases. TranspoGene database is quickly searchable through its website, enables many kinds of searches and is available for download. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome.

Proper citation: TranspoGene (RRID:SCR_005634) Copy   

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http://blogs.nejm.org/now/

A blog produced by the NEJM publishing communications team about new and innovative content in the New England Journal of Medicine (NEJM.org). Our goal is to inform you about what''s new and provide some additional context to complement the content published in NEJM. Each week we post a piece under Insights about one of the latest research papers in NEJM, discussing its clinical significance, where it may lead us in practice and research, and often giving an editor''s thoughts about why it was important to publish. We pose questions to stimulate your thinking and discussion. The idea is to make it easy for you to give us your views on a particular topic and make the conversation accessible to other doctors and physicians-in-training. Posts contain links to the full article, which will be free to all visitors for a limited time. We also feature two posts from the Resident e-Bulletin each week, with an article summary, Clinical Pearls, and Morning Report Questions teaching points that many of you find so useful in your roles as teachers or trainees. The blog gives us a new way to distribute and store this educational information on the social web, again, inviting comment and discussion. You''ll also hear about new products and applications as we bring them out, such as new Interactive Medical Cases, or iPhone applications, like NEJM This Week and the Image Challenge. We link to videos on the NEJMvideo channel on YouTube, share our Twitter feed, and links to NEJM in the News, too. We''d like this to be an open forum, complementary to the core content of NEJM, engaging you in a new experience beyond the journal page in a more interactive community.

Proper citation: Now at NEJM (RRID:SCR_005239) Copy   

•   Source: SciCrunch Registry

http://plantta.jcvi.org/

The TIGR database is a collection of plant transcript sequences. Transcript assemblies are searchable using BLAST and accession number. The construction of plant transcript assemblies (TAs) is similar to the TIGR gene indices. The sequences that are used to build the plant TAs are expressed transcripts collected from dbEST (ESTs) and the NCBI GenBank nucleotide database (full length and partial cDNAs). "Virtual" transcript sequences derived from whole genome annotation projects are not included. All plant species for which more than 1,000 ESTs or cDNA sequences are available are included in this project. TAs are clustered and assembled using the TGICL tool (Pertea et al., 2003), Megablast (Zhang et al., 2000) and the CAP3 assembler (Huang and Madan, 1999). TGICL is a wrapper script which invokes Megablast and CAP3. Sequences are initially clustered based on an all-against-all comparisons using Megablast. The initial clusters are assembled to generate consensus sequences using CAP3. Assembly criteria include a 50 bp minimum match, 95% minimum identity in the overlap region and 20 bp maximum unmatched overhangs. Any EST/cDNA sequences that are not assembled into TAs are included as singletons. All singletons retain their GenBank accession numbers as identifiers. Plant TA identifiers are of the form TAnumber_taxonID, where number is a unique numerical identifier of the transcript assembly and taxonID represents the NCBI taxon id. In order to provide annotation for the TAs, each TA/singleton was aligned to the UniProt Uniref database. For release 1 TAs, a masked version of the Uniref90 database was used. For release 2 and onwards, a masked version of the UniRef100 database is used. Alignments were required to have at least 20% identity and 20% coverage. The annotation for the protein with the best alignment to each TA or singleton was used as the annotation for that sequence. Additionally, the relative orientation of each TA/singleton to the best matching protein sequence was used to determine the orientation of each TA/singleton. Some sequences did not have alignments to the protein database that met our quality criteria, and those sequences have neither annotation nor orientation assignments. The release number for the plant TAs refers to the release version for a particular species. For the initial build, all TA sets are of version 1. Subsequent TA updates for new releases will be carried out when the percentage increase of the EST and cDNA counts exceeds 10% of the previous release and when the increase contains more than 1,000 new sequences. New releases will also include additional plant species with more than 1,000 EST or cDNA sequences that have become publicly available.

Proper citation: TIGR Plant Transcript Assembly database (RRID:SCR_005470) Copy   

•   Source: SciCrunch Registry

http://oger.tu-bs.de/strepto_db

A database for comparative genomics of group A and group B streptococci. It is based on OGeR (Open Genome Resource for comparative analysis of prokaryotic genomes) and includes all sequenced GAS and GBS strains and serovars available as EMBL genome review or NCBI GenBank files. Strepto-DB identifies the homologous proteins deduced from the genomes of interest. It allows for the elucidation of the GAS and GBS core- and pan-genomes via genome-wide comparisons. Moreover, an intergenic region analysis tool provides alignments and predictions for transcription factor binding sites in the non-coding sequences. An interactive genome browser visualizes functional annotations. Strepto-DB (http://oger.tu-bs.de/strepto_db) was created by the use of OGeR, the Open Genome Resource for comparative analysis of prokaryotic genomes. OGeR is a newly developed open source database and tool platform for the web-based storage, distribution, visualization and comparison of prokaryotic genome data. The system automatically creates the dedicated relational database and web interface and imports an arbitrary number of genomes derived from standardized genome files.

Proper citation: Strepto-DB (RRID:SCR_005196) Copy   

•   Source: SciCrunch Registry

http://ogremk5.wordpress.com/

Science, Technology, Education, Government, and anti-woo. Cassandra had the gift of seeing the future, but the curse of having no one believe her.

Proper citation: Cassandras Tears (RRID:SCR_005229) Copy   

•   Source: SciCrunch Registry

http://tabit.ucsd.edu/sdec/

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

Proper citation: Systems Transcriptional Activity Reconstruction (RRID:SCR_005622) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/sfnvideo

The Society for Neuroscience (SfN) is a nonprofit membership organization of scientists and physicians who study the brain and nervous system. SFNVideo - YouTube are videos uploaded to YouTube by the Society for Neuroscience (SfN). Since inception in 1969, the Society has grown from 500 members to more than 41,000. Today, SfN is the world''s largest organization of scientists and physicians devoted to advancing understanding of the brain and nervous system.

Proper citation: sfnvideo - YouTube (RRID:SCR_005463) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html#transfac

Manually curated database of eukaryotic transcription factors, their genomic binding sites and DNA binding profiles. Used to predict potential transcription factor binding sites.

Proper citation: TRANSFAC (RRID:SCR_005620) Copy   

•   Source: SciCrunch Registry

http://www.tigr.org/tdb/e2k1/plant.repeats

It assists in the compilation and identification of repeat sequences in plant genomes. All of the repetitive sequences in the database are coded for the convenience of future analyses. In plants, ploidy levels and repetitive sequences contribute significantly to genome size. A number of different repetitive sequences have been reported in the plant genome and these can be classified into super-classes, classes, and subclasses based on structure and sequence composition. The transposable element (TEs) super-class includes retrotransposons, transposons, and miniature inverted-repeat transposable elements (MITEs). Other repetitive sequences are associated the centromere and telomere. Another super-class of repetitive sequences are rDNAs which encode the structural RNA components of ribosomes.

Proper citation: Plant Repeat Databases (RRID:SCR_005460) Copy   

•   Source: SciCrunch Registry

https://www.youtube.com/user/iniusc

Videos uploaded to YouTube by the Laboratory of Neuro Imaging (LONI). The Laboratory of Neuro Imaging at UCLA strives to improve our understanding of the brain in health and disease. LONI is a leader in the development of advanced computational algorithms and scientific approaches for the comprehensive and quantitative mapping of brain structure and function.

Proper citation: Laboratory of Neuro Imaging - YouTube (RRID:SCR_005462) Copy   

•   Source: SciCrunch Registry

http://sciblogs.co.nz/

Sciblogs brings together the best science bloggers in the country (New Zealand) on one website, creating a hub for scientific analysis and discussion and facilitating reader interaction. The website is for scientists who want to reach out to a general audience to explain their science and how it relates to society. Some Sciblog contributors spend most of their time in the lab or buried in research. Others are authors or entrepreneurs. All of them know what they are talking about and have an interest in engaging in discussion on the big science-related issues facing society. Over time more bloggers will be added to the Sciblogs roster. If you would like to inquire about hosting a blog on Sciblogs contact us. You can easily keep an eye on new Sciblogs posts by subscribing via RSS or email or by following our Twitter feed. Alternatively, there is a Facebook page as well as a Facebook group feel free to join in! Categories: * Science * Agriculture * Technology * Health and Medicine * Environment and Ecology * Science and Society

Proper citation: Sciblogs (RRID:SCR_005219) Copy   

•   Source: SciCrunch Registry

http://www.hematology.org/Publications/Videos/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 18, 2016. ASH's video library includes a number of films produced on various topics, including ASH''s history and award winners, Society programs such as the Clinical Research Training Institute, and a trailer and clips from the hematology documentary Blood Detectives, which aired on Discovery Health. These videos were created for educational purposes, and we encourage members of the hematology community to share them with others.

Proper citation: ASH Video Library (RRID:SCR_005777) Copy   

•   Source: SciCrunch Registry

http://microrna.osu.edu/.UCbase4

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. UCbase & miRfunc is a database of (i) human, mouse and rat microRNAs and (ii) Ultraconserved elements providing information about function, expression and correlation between these classes of non-coding RNAs and the disorders related to their aberrant expression. The genomics interface allows the user to explore where whole-genome collections of miRNAs and UCRs are located with respect to annotation sets such as band, disorders and known genes. The Blast interface provides a web tool for matching miRNAs/UCRs elements against any given sequence and providing specific functional information on the results. 481 Ultraconserved sequences (UCRs) longer than 200 bases were discovered in the genomes of human, mouse and rat. These are DNA sequences showing 100 percent identity among the human, mouse and rat genomes. UCRs are frequently located at genomic regions involved in cancer, differentially expressed in human leukemias and carcinomas and in some instances regulated by microRNAs (miRNAs), the most extensively studied category of non-coding RNAs (ncRNAs). Here we present the first database which links UCRs and miRNAs with the related human disorders and genomic properties.

Proper citation: UCbase & miRfunc: Ultraconserved Sequences and miRNA Funciton Database (RRID:SCR_005771) Copy   

•   Source: SciCrunch Registry

http://bigg.ucsd.edu/

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.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry

http://the_brain.bwh.harvard.edu/uniprobe/

Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences.

Proper citation: UniPROBE (RRID:SCR_005803) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/downloads/

The Peptide Sequence Database contains putative peptide sequences from human, mouse, rat, and zebrafish. Compressed to eliminate redundancy, these are about 40 fold smaller than a brute force enumeration. Current and old releases are available for download. Each species'' peptide sequence database comprises peptide sequence data from releveant species specific UniGene and IPI clusters, plus all sequences from their consituent EST, mRNA and protein sequence databases, namely RefSeq proteins and mRNAs, UniProt''s SwissProt and TrEMBL, GenBank mRNA, ESTs, and high-throughput cDNAs, HInv-DB, VEGA, EMBL, IPI protein sequences, plus the enumeration of all combinations of UniProt sequence variants, Met loss PTM, and signal peptide cleavages. The README file contains some information about the non amino-acid symbols O (digest site corresponding to a protein N- or C-terminus) and J (no digest sequence join) used in these peptide sequence databases and information about how to configure various search engines to use them. Some search engines handle (very) long sequences badly and in some cases must be patched to use these peptide sequence databases. All search engines supported by the PepArML meta-search engine can (or can be patched to) successfully search these peptide sequence databases.

Proper citation: Peptide Sequence Database (RRID:SCR_005764) Copy   

•   Source: SciCrunch Registry