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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.ncbi.nlm.nih.gov/pubmed/
Public bibliographic database that provides access to citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include fields of biomedicine and health, covering portions of life sciences, behavioral sciences, chemical sciences, and bioengineering. Provides access to additional relevant web sites and links to other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to full-text of articles at journal web sites using LinkOut.
Proper citation: PubMed (RRID:SCR_004846) Copy
http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/AnneOTate.cgi
A web based search tool to help you gain an overview of the set of articles (up to 25,000 most recent articles) retrieved by a PubMed query. Once you enter a query, you can select different types of summary information to view: Important words, Topics, Authors, Affiliations, Journals, Year, Clustered by topic.
Proper citation: Anne O'Tate (RRID:SCR_005340) Copy
http://gopubmed.org/web/gopubmed/
A web server which allows users to explore PubMed search results with the Gene Ontology, a hierarchically structured vocabulary for molecular biology. GoPubMed submits a user''''s keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation. Platform: Online tool
Proper citation: GoPubMed (RRID:SCR_005823) Copy
http://www.ebi.ac.uk/Rebholz-srv/ebimed/
A web application that combines Information Retrieval and Extraction from Medline. EBIMed finds Medline abstracts in the same way PubMed does. Then it goes a step beyond and analyses them to offer a complete overview on associations between UniProt protein/gene names, GO annotations, Drugs and Species. The results are shown in a table that displays all the associations and links to the sentences that support them and to the original abstracts. By selecting relevant sentences and highlighting the biomedical terminology EBIMed enhances your ability to acquire knowledge, relate facts, discover implications and, overall, have a good overview economizing the effort in reading.
Proper citation: EBIMed (RRID:SCR_005314) Copy
http://www.coremine.com/medical/#search
Service to access comprehensive information on diseases, drugs, treatments and medical biology. It is ideal for those seeking an overview of a complex subject while allowing the possibility to drill down to specific details. Search results are presented in a dashboard format comprized of panels containing various categories of information ranging from introductory sources to the latest scientific articles.
Proper citation: Coremine Medical (RRID:SCR_005323) Copy
A literature search tool providing gene and signal transduction pathway mining within NCBI''''s PubMed database. Its sophisticated gene recognition and intuitive color coding increase the readability of abstracts and lets you analyze signal transduction pathways, diseases and tissue associations in a snap. Note: LitInspector has become part of the Literature & Pathways module of the Genomatix Software Suite.
Proper citation: LitInspector (RRID:SCR_011870) Copy
Data analysis service that searches PubMed literature database (abstracts) about specific relationships between proteins, genes, or keywords using a NLP-based text-mining approach. The results are returned as a graph. The synonym database used in Chilibot is available, without fee, for academic use only. Several different search methods are supported including: * searching for relationship between two genes, proteins or keywords * searching for relationships between many genes, proteins, or keywords * searching for relationships between two lists of genes, proteins, or keywords Advanced options include: * Automated hypothesis generation (graph) * Restricting context using keywords * Providing your own synonyms * Modifying synonyms provided by Chilibot * Color coding nodes with gene expression values * Special search: modulation
Proper citation: Chilibot: Gene and Protein relationships from MEDLINE (RRID:SCR_001705) Copy
http://www.ncbi.nlm.nih.gov/pmc/
Collection of full text archive of biomedical and life sciences journal literature at U.S. National Institutes of Health National Library of Medicine (NIH/NLM). With PubMed Central, NCBI is taking lead in preserving and maintaining open access to electronic literature. Value of PubMed Central, in addition to its role as an archive, lies in what can be done when data from diverse sources is stored in common format in single repository. All articles in PMC are free (sometimes on a delayed basis). Some journals go beyond free, to Open Access.
Proper citation: PubMed Central (RRID:SCR_004166) Copy
http://www.ihop-net.org/UniPub/iHOP/
Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.
Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy
http://www.ncbi.nlm.nih.gov/CBBresearch/Wilbur/IRET/PIE/
A web service to extract Protein-protein interaction (PPI)-relevant articles from MEDLINE that provides protein interaction information (PPI) articles for biologists, baseline system performance for bio-text mining researchers and a compact PubMed-search environment for PubMed users. It accepts PubMed input formats including All Fields, Author, Journal, MeSH Terms, Publication Date, Title, and Title/Abstract with Boolean operations (AND, OR, and NOT). However, the output is the list of articles prioritized by PPI confidence rates. Some words (mostly gene/protein names) which contributed for PPI prediction are underlined and linked to Entrez or Entrez Gene. Even though our system focuses on a PubMed search environment, it also provides a CGI access for bio-text mining researchers. Using the CGI program, a list of PubMed IDs can be obtained as a query result, thus it can be utilized as a baseline system performance. PIE the search is based on a winning approach in the BioCreative III ACT competition (BC3)1. For input queries, MEDLINE articles are first retrieved through the PubMed service. PPI scores are calculated for the retrieved articles, and the articles are re-ranked based on scores. To effectively capture PPI patterns from biomedical literature, their approach utilizes both word and syntactic features for machine learning classifiers. Dependency parsing, gene mention tagging, and term-based features are utilized along with a Huber classifier.
Proper citation: PIE the search (RRID:SCR_005296) Copy
http://dm.postech.ac.kr/refmed/
Relevance Feedback Search Engine for PubMed. When a user enters a keyword in the search box, the PubMed search results will be returned. The user then specifies on a sample of results how much they are relevant to what she intends to find, for example, by specifying whether each article is high relevant, somewhat relevant, or not relevant. Once the user clicks Push Feedback button, the system learns a relevance function from the feedback and returns the top articles ranked highly according to the relevance function. The user can repeat the process until she gets satisfying results.
Proper citation: RefMED (RRID:SCR_011871) Copy
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