Curator Dashboard

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. MILANO provides a useful tool for the automatic custom annotation of microarray results which is based on all the available literature. It has two major advances over similar tools: the ability to expand gene names to include all their informative synonyms while removing synonyms that are not informative and access to the GeneRIF database which provides short summaries of curated articles relevant to known genes. MILANO allows annotation of lists of genes derived from microarray results by user defined terms. The annotation strategy is based on counting the number of literature co-occurrences of each gene on the list with a user defined term. This strategy allows the customization of the annotation procedure and thus overcomes one of the major limitations of the functional annotations usually provided with microarray results. MILANO expands the gene names to include all their informative synonyms while filtering out gene symbols that are likely to be less informative as literature searching terms. It supports searching two literature databases: GeneRIF and Medline (through PubMed), allowing retrieval of both quick and comprehensive results. MILANO''s ability can improve microarray analysis by analyzing a list of 150 genes that were affected by p53 overproduction. This analysis reveals that it enables immediate identification of known p53 target genes on this list and assists in sorting the list into genes known to be involved in p53 related pathways, apoptosis and cell cycle arrest. This program performs automatic searches in PubMed or the GeneRIF collection for articles containing co-occurrences of search terms with a list of genes (e.g. from a microarray experiment). The program is used by pasting the list of Gene ID''s or symbols in the Primary Search Term field, and the list of cross-reference search terms in the Secondary Search Term field. The output is a table containing the number of hits for each pair of search terms. Sample input is provided in the fields, so you can just click submit and see what happens. If you want to run data of your own, delete the sample input first.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

Infers both the sample genotypes and error parameters that produced a metagenome data set.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Set of databases and tools that handle genomic and metagenomic sequences in their environmental contexts.Includes geographic information system to systematically store and analyse marine genomic and metagenomic data in conjunction with contextual information; environmental genome browser with fast search functionalities; database with precomputed analyses for selected complete genomes; database and tool to classify metagenomic fragments based on oligonucleotide signatures.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

The University of West Bohemia is a university in Pilsen, Czech Republic. It was founded in 1991 and consists of nine faculties.

• Organization
• SciCrunch
• 16 years ago - submitted by Andrea Stagg

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. An algorithm that finds articles most relevant to a genetic sequence. In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here, a new literature-mining tool MedBlast is developed, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided. The genome sequencing projects generate such a large amount of data every day that many molecular biologists often encounter some sequences that they know nothing about. Literature is usually the principal resource of such information. It is relatively easy to mine the articles cited by the sequence annotation; however, it is a difficult task to retrieve those relevant articles without direct citation relationship. The related articles are those described in the given sequence (gene/protein), or its redundant sequences, or the close homologs in various species. They can be divided into two classes: direct references, which include those either cited by the sequence annotation or citing the sequence in its text; indirect references, those which contain gene symbols of the given sequence. A few additional issues make the task even more complicated: (1) symbols may have aliases; and (2) one sequence may have a couple of relatives that we want to take into account too, which include redundant (e.g. protein and gene sequences) and close homologs. Here the issues are addressed by the development of the software MedBlast, which can retrieve the related articles of the given sequence automatically. MedBlast uses BLAST to extend homology relationships, precompiled species-specific thesauruses, a useful semantics technique in natural language processing (NLP), to extend alias relationship, and EUtilities toolset to search and retrieve corresponding articles of each sequence from PubMed. MedBlast take a sequence in FASTA format as input. The program first uses BLAST to search the GenBank nucleic acid and protein non-redundant (nr) databases, to extend to those homologous and corresponding nucleic acid and protein sequences. Users can input the BLAST results directly, but it is recommended to input the result of both protein and nucleic acid nr databases. The hits with low e-values are chosen as the relatives because the low similarity hits often do not contain specific information. Very long sequences, e.g. 100k, which are usually genomic sequences, are discarded too, for they do not contain specific direct references. User can adjust these parameters to meet their own needs.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects. Its transcriptomic data provide invaluable information for molecular entomology study of the insect and pave a way for comparative studies of other medically, agronomically, and ecologically relevant insects. This first transcriptomic database of the locust (LocustDB) has been developed, building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. It currently hosts 45,474 high quality EST sequences from the locust, which were assembled into 12,161 unigenes. This database contains original sequence data, including homologous/orthologous sequences, functional annotations, pathway analysis, and codon usage, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. LocustDB also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. It starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporation of in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modeling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. It is based on the annotation of key terms in article abstracts followed by statistical co-citation analysis of annotated key terms in order to predict relationships. Key terms belonging to four different categories are used for the annotation process: -Genes: Names of genes and gene products. Gene name recognition is based on Ensembl . Synonyms and aliases are resolved. -Chemical Compounds: Names of chemical compounds and their respective aliases. -Diseases and Phenotypes: Names of diseases and phenotypes -Tissues and Organs: Names of tissues and organs LitMiner uses a database of disease and phenotype terms for literature annotation. Currently, there are 2225 diseases or phenotypes, 801 tissues and organs, and 10477 compounds in the database.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. KinasePathwayDatabase is an integrated database concerning completed sequenced major eukaryotes, which contains the classification of protein kinases and their functional conservation and orthologous tables among species, protein-protein interaction data, domain information, structural information, and automatic pathway graph image interface. The protein-protein interactions are extracted by natural language processing (NLP) from abstracts using basic word pattern and protein name dictionary GENA: developed by our group. In this system, pathways are easily compared among species using protein interactions data more than 47,000 and orthologous tables.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. International interdisciplinary Internet based unbiased forum for review of medical literature. Very much like an on-line journal club, we aim to provide a venue which will improve communication amongst physicians and lead to better understanding and interpretation of medical literature. In the academic world, Journal Clubs are a common way to discuss and critically question medical literature. The knowledge gained by this activity can be immeasurable, and often leads to ideas both relating to patient care and to future research. However, many clinicians are unable to participate in these academic activities. In addition, information shared within an individual journal club is seldom disseminated. Here you will find a free, user-friendly website where you can rate and discuss medical literature. It offers innovative and powerful search tools that will allow you to quickly query the medical literature and identify the information you need. In addition, their exclusive tools will help identify the most important and controversial articles. It is their hope to bring both insight and questions to the literature -- both of which will be used to shape future research. Clinicians will have a better understanding of the evidence, and ability to partake in a venue that fosters communication between peers.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. MAP-O-MAT is a web-based server for automated linkage mapping of human polymorphic DNA markers. The server uses publicly available genotype data for over 15,000 markers. It facilitates the verification of order and map distances for custom mapping sets using genotype data from the CEPH database, and from the Marshfield, SNP Consortium and Rutgers linkage maps. The CRI-MAP program is used for likelihood calculations and some mapping algorithms, and physical map positions are provided from the human genome assembly.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

ITER is a toxicology data file on the National Library of Medicine''s (NLM) Toxicology Data Network. It contains data in support of human health risk assessments. It is compiled by Toxicology Excellence for Risk Assessment (TERA) and contains over 600 chemical records with key data from the Agency for Toxic Substances & Disease Registry (ATSDR), Health Canada, National Institute of Public Health & the Environment (RIVM) - The Netherlands, U.S. Environmental Protection Agency (EPA), and independent parties whose risk values have undergone peer review. ITER provides a comparison of international risk assessment information in a side-by-side format and explains differences in risk values derived by different organizations. ITER data, focusing on hazard identification and dose-response assessment, is extracted from each agencys assessment and contains links to the source documentation. Among the key data provided in ITER are ATSDRs minimal risk levels; Health Canadas tolerable intakes/concentrations and tumorigenic doses/concentrations; EPAs carcinogen classifications, unit risks, slope factors, oral reference doses, and inhalation reference concentrations; RIVMs maximum permissible risk levels; NSF International''s reference doses and carcinogen risk levels, IARC''s cancer classifications, and noncancer and/or cancer risk values (that have undergone peer review) derived by independent parties. Users can search by chemical or other name, chemical name fragment, or Chemical Abstracts Service Registry Number(RN), and/or subject terms. Search results can easily be viewed, printed or downloaded. Search results are displayed in relevancy ranked order. Users may select to display exact term matches, complete records, or any combination of data from the following broad groupings: -Noncancer Oral -Cancer Oral -Noncancer Inhalation -Cancer Inhalation

• Resource
• SciCrunch
• 17 years ago - by Anonymous

INFOMINE is a virtual library of Internet resources relevant to faculty, students, and research staff at the university level. It contains useful Internet resources such as databases, electronic journals, electronic books, bulletin boards, mailing lists, online library card catalogs, articles, directories of researchers, and many other types of information. It is librarian built. Librarians from the University of California, Wake Forest University, California State University, the University of Detroit - Mercy, and other universities and colleges have contributed to building INFOMINE.INFOMINE is a unique Web resource featuring well organized access to important university level research and educational tools on the Internet. A virtual library, INFOMINE is notable for its collection of annotated and indexed links. Information in INFOMINE is easy to find given the multiplicity of access points provided (ways of finding the information contained). It contains over 100,000 links (26,000 librarian created links and 75,000 plus robot/crawler created links). Substantive databases, electronic journals, guides to the Internet for most disciplines, textbooks and conference proceedings are among the many types of resources included. The life sciences INFOMINE alone, for example, provides interactive access to several hundred databases. Separate virtual collections or INFOMINEs exist in most major areas of university level research and educational interests. Click here to see the Database Content Information. It began in January of 1994 as a project of the Library of the University of California, Riverside. It was one of the first Web resources of any type offered by a Library. It was also one of the first Web-based, academic virtual libraries as well as one of the first to develop a system combining the advantages of the hypertext and multi-media capabilities of the Web with those of the organizational and retrieval functions of a database manager. We now include focused, automatic Internet crawling as well as automatic text extraction and metadata creation functions to assist our experts in content creation and users in searching. Many of INFOMINE''s important features and services, described below, remain unique among Internet resource collections. INFOMINE, as mentioned, provides a great number of access points, BROWSE (What''s New, Title, Table of Contents, Subject -- LCSH, Subject - LCC, Search -- Research Discipline, Key Word, Megatopics - Keyword in context, Title, Author, hyperlinked indexing) and SEARCH (Title, Subject -- LCSH, Key Word, Author, Description, Full-text), and LIMIT search (Resource Type, Resource Origin and Access) modes. Searching in fielded and full-text mode allows the user to quickly find high quality resources on the chosen subject(s). Nested, boolean searching capabilities are featured as is exact searching. Search results come back in the form of dynamically created Web pages. Results within these can be ranked by relevance to the search or alphabetically by title. Displays available include title only, regular display, long display and full display. Many of the displays feature indexing terms that are viewable and in hyperlink form and, when clicked upon, allow further broadening or narrowing of the search as desired. Noteworthy as well is that INFOMINE is augmenting its content with a large, second-tier collection of automatically selected and described resources that should complement its first-tier collection of expert created records and allow the user more detail in searching and a greater number of useful results. Finally, on the Advanced Search page, we have browsing indexes which cover all topics and more. These include: * Subjects -- LCSH (Library of Congress Subject Headings), Table of Contents (LCSH with titles filing under each heading), LCC (Library of Congress Classifications) and Research Disciplines * Keywords -- MegaTopics (keyphrases drawn from our title, subject, keyword and annotation fields) and standard Keywords * Other Indexes: Authors, Titles, Resource Types and What''s New Among the contributions of INFOMINE is the essential enrichment or value added service, as mentioned, of providing concise descriptive information (e.g., an annotation as well as in-depth indexing terminology including Library of Congress Subject Headings) for each record. This greatly helps users to quickly retrieve a focused results set, examine the relevance of individual records and then choose among them immediately prior to accessing thus saving considerable time. Librarian collection expertise and concerns regarding resource comprehensiveness, quality and general usefulness from an academic perspective guide all INFOMINE resource selection activities. Also a crucial behind-the-scenes contribution from INFOMINE is that we are addressing the challenge of better subject portal scaling (keeping up with the growth of important resources on the Internet) by semi-automating or automating a number of collection building tasks (e.g., identification of significant resources for collecting and developing metadata descriptions of these resources). This will help us save crucial resources and redirect them into creating a better and larger collection. In-depth description and indexing, careful selection, a considerable number of options in browsing/searching, and ample help in usage mean that faculty, students and staff can find important, relevant Internet resources quickly and easily via INFOMINE. Sponsors: INFOMINE is supported by the University of California, Riverside.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

Comprehensive collection of spatially interacting motifs in proteins. Interacting motif database lists interacting motifs that are identified for all structural entries in PDB. Conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting common motifs shared among all superfamily members.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. It contains annotated structural elements characteristic for certain classes of structural and/or functional RNAs. These elements are described in a language specifically designed for this purpose. The language allows convenient specification of hybrid patterns, i.e. motifs consisting of sequence features and structural elements together with sequence similarity and thermodynamic constraints. A system that searches complex patterns (on nucleic-acid or protein level) in large biosequence-databases. As patterns, they allow hybrid patterns, which combine sequence similarity, structure similarity and arbitrary characteristics, like thermodynamic constraints. Applications are in the research of highly specific Protein/RNA-interactions or in the search of RNA-tertiary-structure-interactions. They developed a declarative pattern description language, which is implemented by known and new pattern-matching algorithms and an optimizing backtracking procedure. To achieve high efficiency when screening large data sets, the patterns are divided and queries are composed. The significance of patterns is estimated by a Monte-Carlo procedure. Complex results of queries are processed by a visualizing component. A library of biologically relevant patterns is developed and it is provided on the WWW together with the search-tool. The evaluation of the tool w.r.t. to the biosequence databases will in some cases mean to make laboratory-experiments, in order to check algorithmically developed functional hypothesis. Sponsors: This project is supported by a grant from the Deutsche Forschungsgemeinschaft. It is part of the special program on Computational Methods for the Analysis and Interpretation of large genomic data

• Resource
• SciCrunch
• 17 years ago - by Anonymous

A REST-based web application designed for visualizing deep sequencing data and other genome annotation data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

JenPep is a database of quantitative binding data for immunological protein-peptide interactions. It is a system which allows speedy access to this binding data through simple on-line interfaces and effective search mechanisms.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

The Foundational Model Explorer (FME) is an internet based software application developed for viewing the content and organization of the Foundational Model of Anatomy Ontology (FMA). The initial purpose of the FME was to provide a simple and intuitive interface to the FMA for domain experts, in the field of anatomy, participating in the evaluation of the FMA. The FME also provides an easily available method of exploring the FMA to individuals or groups considering the adoption of the Foundational Model of Anatomy knowledge base. The FME display consists of two panes: a hierarchical tree may be opened up in the pane on the left side; if a class is selected in the hierarchical tree, the pane on the right side displays the information that has been entered in the FMA for that class. The information associated with a given class is organized in so-called slots. Each slot has a name (e.g., Definition, Parts) and some content, which is that particular slots value (e.g., the English definition and the names of parts of the selected class, respectively). For an explanation of the interactive features of the FME, see the Knowledge Navigation Section. For a guided tutorial check out the Conducted Tour. In the left pane, the default tree is a subclass hierarchy, based on the -is a- or -kind of- relationship; it is the instantiation of the Anatomy taxonomy (At) component in the high level scheme of the Foundational Model of Anatomy. Apart from the slots Preferred Name and Synonyms, other slots relate to the Anatomical Structural Abstraction (ASA) component in the FMAs high level scheme. Hierarchies based on various part-whole relationships can also be opened up in the left pane. Once a class has been highlighted in the subclass hierarchy, you can choose a relationship from a drop down list labeled Select navigation tree type. Some other transitive relationships (e.g., -branch of- and -tributary of-) are also available. The Search facility matches a search term to the preferred name, as well as to the Latin name, or synonym of an FMA class (if such exist). The tree is expanded to reveal the matching class and the information about this class is displayed. The wildcard * is allowed in the search term and will match to any sequence of characters. For example the search term h*d matches the class names Head and Hepatic cord (amongst others). The search function is not case sensitive. If more than one class name matches with the search term, a list of matching terms is presented for the user to choose between.

• Resource
• SciCrunch
• 17 years ago - by Anonymous