Tools   Select Another Resource Report Type

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://www.ncats.nih.gov/research/reengineering/bridgs/bridgs.html

on a competitive basis, successful applicants receive access to NIH contractors who conduct preclinical studies at no cost to the investigator for the development of new therapeutic agents. In general, synthesis, formulation, pharmacokinetic and toxicology services in support of investigator-held Investigational New Drug (IND) applications to the Food and Drug Administration are available. Contract costs are supported by the NIH Common Fund and collaborating NIH Institutes and Centers. Access to contracts is based upon a peer-reviewed application process. The number of awards made will depend on the number of applications received, their scientific merit, and the availability of NIH funds. BrIDGs is not a complete drug development program or an unconditional commitment to develop a particular compound for the clinic. In some cases the program supports one or two key steps for preclinical development, while in other cases it assists with most of the development tasks needed to file an IND. The services provided by the program depend upon the stage of a given project and need for additional data. Once a project is approved, NIH staff work with principal investigators to develop a plan for the conduct of proposed studies. Contractors perform tasks approved by BrIDGs under the direction of NIH staff. Development proceeds sequentially in most cases and the start of one segment of the project (e.g., toxicology) may depend on satisfactory completion of preceding segments (e.g., formulation). Insurmountable difficulties in one segment may force the discontinuation of an entire project. BrIDGs supports projects proposed by academic institutions, not-for-profit organizations, and SBIR-eligible businesses. Foreign academic and non-profit institutions may also apply. Potential therapies for any disease or disorder may be submitted to BrIDGs. All proposed therapeutic agents should have demonstrated pharmacological activity in an appropriate in vivo disease model before applying.

Proper citation: Bridging Interventional Development Gaps (RRID:SCR_005635) Copy   

•   Source: SciCrunch Registry

http://fairbrother.biomed.brown.edu/spliceman/index.cgi

An online tool that takes a set of DNA sequences with point mutations and returns a ranked list to predict the effects of point mutations on pre-mRNA splicing. The current implementation includes 11 genomes: human, chimp, rhesus, mouse, rat, dog, cat, chicken, guinea pig, frog and zebrafish.

Proper citation: Spliceman (RRID:SCR_005354) Copy   

•   Source: SciCrunch Registry

http://blogs.scientificamerican.com/observations/

From the editors and reporters of Scientific American, this blog delivers commentary, opinion and analysis on the latest developments in science and technology and their influence on society and policy. From reasoned arguments and cultural critiques to personal and skeptical takes on interesting science news, you''ll find a wide range of scientifically relevant insights here.

Proper citation: Scientific American Observations (RRID:SCR_005195) 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://scienceblogs.com/

From climate change to intelligent design, HIV/AIDS to stem cells, science education to space exploration, science is figuring prominently in our discussions of politics, religion, philosophy, business and the arts. New insights and discoveries in neuroscience, theoretical physics and genetics are revolutionizing our understanding of who are are, where we come from and where we''re heading. Launched in January 2006, ScienceBlogs is a portal to this global dialogue, a digital science salon featuring the leading bloggers from a wide array of scientific disciplines. Today, ScienceBlogs is the largest online community dedicated to science. We believe in providing our bloggers with the freedom to exercise their own editorial and creative instincts. We do not edit their work and we do not tell them what to write about. We have selected our 80+ bloggers based on their originality, insight, talent, and dedication and how we think they would contribute to the discussion at ScienceBlogs. Our role, as we see it, is to create and continue to improve this forum for discussion, and to ensure that the rich dialogue that takes place at ScienceBlogs resonates outside the blogosphere. ScienceBlogs is always interested in bringing new contributors into our community. If you''re interested in blogging with us, please fill out our application, and we''ll be in touch.

Proper citation: ScienceBlogs (RRID:SCR_005197) 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://www.wanprc.org/primate-resources/pathology-tissue-program/

A comparative pathology unit offering pathology support, training programs, and a Tissue Distribution Program (TDP). The TDP provides a wide variety of nonhuman primate tissues to investigative groups within and outside the Washington National Primate Research Center (WaNPRC). Tissue and pathology services (ACVP board certified Veterinary Pathologists), full histology services (including immunohistochemistry and frozen sectioning), and protocol development consultation are available. The Pathology and Tissue Program is an integration of comparative pathology activities occurring at the Washington National Primate Research Center and those occurring within the University of Washington Department of Comparative Medicine ((DCM). Using this model, Washington National Primate Research Center pathologists provide routine pathology support for Washington National Primate Research Center animals, with ancillary support, expertise, and guidance provided by DCM pathologists and mission-dedicated technicians and laboratories. This integrated comparative pathology unit also provides an excellent training opportunity for students such as those enrolled in the Department of Comparative Medicine post-doctoral training program, which offers training in laboratory animal medicine and comparative pathology. A particularly important function of this comparative pathology unit is support of the Tissue Distribution Program. The TDP provides a wide variety of nonhuman primate tissues to investigative groups within and outside the WaNPRC. This program is an extremely valuable method of conserving the nonhuman primate resource. NHP tissues and biological materials are collected in preparation for RNA/DNA isolation, cell culture, immunohistochemistry/histology, anatomic dissection, and cell sorting. Capabilities of the TDP include, but are not limited to flash frozen preservation, sterile preparation, perfusion, technical surgical dissections, and OCT embedding. In conjunction with the Histology and Imaging core of the University of Washington DCM, research capabilities post-collection include in situ hybridization, confocal and fluorescent microscopy, live cell imaging (DeltaVision), and whole slide scanning with image analysis (Visiopharm, Nikon Elements, and Image Pro). Centralized coordination of nonhuman primate tissue requests with animal availability allows support for a large number of biomedical programs with significantly decreased impact on the animal resource.

Proper citation: WaNPRC Pathology and Tissue Program (RRID:SCR_005589) 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://www.plexdb.org/plex.php?database=Barley/funcexpression.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 11, 2012. FuncExpression is a web-based resource for functional interpretation of large scale genomics data. FuncExpression can be used for the functional comparison of plant, animal, and fungal gene name lists generated from genomics and proteomics experiments. Multiple gene lists can be classified, compared and visualized. FuncExpression supports two way-integration of plant gene functional information and the gene expression data, which allows for further cross-validation with plant microarray data from related experiments at BarleyBase. Platform: Online tool

Proper citation: FuncExpression (RRID:SCR_005773) Copy   

•   Source: SciCrunch Registry

http://www.dbs.ifi.lmu.de/~bundschu/LHGDN.html

A text mining derived database with focus on extracting and classifying gene-disease associations with respect to several biomolecular conditions. It uses a machine learning based algorithm to extract semantic gene-disease relations from a textual source of interest. The semantic gene-disease relations were extracted with F-measures of 78. More specifically, the textual source utilized here originates from Entrez Gene''''s GeneRIF (Gene Reference Into Function) database (Mitchell, et al., 2003). LHGDN was created based on a GeneRIF version from March 31st, 2009, consisting of 414241 phrases. These phrases were further restricted to the organism Homo sapiens, which resulted in a total of 178004 phrases. We benchmark our approach on two different tasks. The first task is the identification of semantic relations between diseases and treatments. The available data set consists of manually annotated PubMed abstracts. The second task is the identification of relations between genes and diseases from a set of concise phrases, so-called GeneRIF (Gene Reference Into Function) phrases. In our experimental setting, we do not assume that the entities are given, as is often the case in previous relation extraction work. Rather the extraction of the entities is solved as a subproblem. Compared with other state-of-the-art approaches, we achieve very competitive results on both data sets. To demonstrate the scalability of our solution, we apply our approach to the complete human GeneRIF database. The resulting gene-disease network contains 34758 semantic associations between 4939 genes and 1745 diseases. The gene-disease network is publicly available as a machine-readable RDF graph. We extend the framework of Conditional Random Fields towards the annotation of semantic relations from text and apply it to the biomedical domain. Our approach is based on a rich set of textual features and achieves a performance that is competitive to leading approaches. The model is quite general and can be extended to handle arbitrary biological entities and relation types. The resulting gene-disease network shows that the GeneRIF database provides a rich knowledge source for text mining.

Proper citation: Literature-derived human gene-disease network (RRID:SCR_005653) 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