Curator Dashboard

go-moose is intended as a replacement for the aging go-perl and go-db-perl Perl libraries. It is written using the object oriented Moose libraries. It can be used for performing a number of analyses on GO data, including the remapping of GO annotations to a selected subset of GO terms. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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• SciCrunch
• 15 years ago - by Anonymous

Service to summarize the GO function associated with a data set using prepared GO Slim sets. The input is a tab separated list of gene product IDs and GO IDs.

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. KI Biobank - Gallstone aims at investigating genetics of gallstone disease on Swedish Twins. Types of samples * EDTA whole blood * DNA * Plasma Number of sample donors: 82

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• SciCrunch
• 15 years ago - by Anonymous

Web-service providing access to database that brings together information from broad range of resources. Web application for functional annotation and statistical hypothesis testing. Provides tools for analysis of genomic and microarray data. Collection of tools include Bibliographic Information,Databases,Gene Annotation,Gene Regulation, Microarray,Proteins,Sequence Manipulation - Nucleic Acids,Sequence Manipulation - Protein, Systems Biology.

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• SciCrunch
• 15 years ago - by Anonymous

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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• SciCrunch
• 15 years ago - by Anonymous

Collects mammalian cis- and trans-regulatory elements together with experimental evidence. Regulatory elements were mapped on to assembled genomes. Resource for gene regulation and function studies. Users can retrieve primers, search TF target genes, retrieve TF motifs, search Gene Regulatory Networks and orthologs, and make use of sequence analysis tools. Uses databases such as Genbank, EPD and DBTSS, and employ promoter finding program FirstEF combined with mRNA/EST information and cross-species comparisons. Manually curated.

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• SciCrunch
• 17 years ago - by Anonymous

Audio clips that highlight research efforts at the National Institute on Drug Abuse and include interviews with prominent NIDA scientists. To listen to these clips, just click Listen Now under the clip summary. You must have Real Media Player or Windows Media Player installed to download these clips. To view a printable transcript of a clip, click View Transcript under the clip summary.

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• SciCrunch
• 15 years ago - by Anonymous

A public repository of information on tandem repeats in genomic DNA and contains a variety of tools for their analysis. These currently include the Tandem Repeats Finder algorithm, query and filtering capabilities for finding particular repeats of interest, repeat clustering algorithms based on sequence similarity, polymorphism prediction based on common patterns of mutation, PCR primer selection, and data download in a variety of formats. In addition, TRDB serves as a centralized research workbench, provides storage space for results of analysis, and permits collaborators to privately share their data and analysis.

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• SciCrunch
• 17 years ago - by Anonymous

This TRbase is a relational tandem repeat database that relates tandem repeats to gene locations and disease genes of the human genome. The TRbase stores both perfect and imperfect repeats of 1 to 2000 bp unit lengths that were identified using the Tandem Repeat Finder program. Disease information for all 24 chromosomes was retrieved from the Online Mendelian Inheritance in Man (OMIM) database. There are five main search forms by which the user may query the database: 1. The Advanced tandem repeat search: This allows a complete search for tandem repeats using a combination of criteria, such as total tandem repeat length, repeat unit length, copy number of the repeats, percentage matches and the consensus repeat pattern. On submission, the number of repeats and the detailed tandem repeat characteristics of each repeat that match the user query are tabulated. 2. The Main search: This relates tandem repeat data to genes and diseases. The user may specify a gene of interest to view details of all repeats associated with it or search for tandem repeats present in a particular disease by entering the name/keyword for the disease or the MIM number of the disease gene. 3. The Composite search: This more advanced search allows the user to query specifically for repeats present in exons, introns or intergenic regions of a gene or disease gene. 4. The Gene Search: Further information on genes can be available by a simple gene name search on this page. 5. The Disease search: This allows extensive information on disease genes on all chromosomes of the human genome. Searching for a MIM number, or keyword searches specifying the features of the disease, will retrieve the information on the disease and the chromosome in which the disease gene occurs. Each entry retrieved is linked to the OMIM database for detailed literature and gene map information on the disease.

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• SciCrunch
• 17 years ago - by Anonymous

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

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• SciCrunch
• 15 years ago - by Anonymous

Neuromorphometrics provides brain labeling and measurement services. Given raw MRI brain scans, we make precise quantitative measurements of the volume, shape, and location of specific neuroanatomical structures. Web tool for brain measurement services. Used for modeling living human brain and make quantitative measurements of volume, shape, and location of specific neuroanatomical structures using given MRI brain scans. Automated analyses are manually guided, inspected and certified by a neuroanatomical expert. Resource of neuroanatomically labeled MRI brain scans database. Resource for neuroanatomical localization and identification: NeuAtlas.

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• SciCrunch
• 15 years ago - by Anonymous

A database providing access to mRNA sequences and associated regulatory elements. Users can obtain data relating to translation (by species in a non-redundant format), search for regulatory elements in a defined set, or search their own sequence for known regulatory elements. The mRNA sequences are processed from Genbank, including complete genomes. They are divided into biologically relevant sections 5' UTRs and 3' UTRs, initiation and termination regions and the full CDS sequences. This data or your own sequences can be searched for defined regulatory elements. Recent Developments The web interface has been revised to allow users to analyse their own sequences. All motifs description have been revised new specific patterns have been added. Transterm data was updated with Genbank 122 (Feb 2001). Acknowledgements Health Research Council of New Zealand Marsden Fund of New Zealand translation, translational control of protein synthesis, mRNA, biologically relevant mRNA regions, GenBank, taxonomy, initiation codon (Kozaks consensus or Shine Dalgarno sequences), termination codon, coding regions or 3' flanking regions, Nucleotide Sequence, Transcriptional regulator, transcription factor

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• SciCrunch
• 17 years ago - by Anonymous

The Hungarian Academy of Sciences is the most important and prestigious learned society of Hungary. Its seat is at the bank of the Danube in Budapest, between Széchenyi rakpart and Akadémia utca.

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• SciCrunch
• 13 years ago - submitted by Andrea Stagg

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.

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• SciCrunch
• 14 years ago - by Anonymous

By collecting and analyzing blood samples from Geisinger''s large patient population, MyCode will help unlock the mysteries of some of the most devastating and debilitating diseases. Blood samples are obtained from patients of certain Geisinger specialty clinics to study specific conditions, such as obesity and cardiovascular disease, and also from patients of Geisinger primary care clinics to provide a representative sample of the regional population. More than 60,000 samples from over 23,000 Geisinger patients have been collected so far, and sample collection is ongoing. MyCode researchers use the blood samples to study the genetic causes of diseases and certain disease-related molecular mediators. Knowledge gained from these studies will allow researchers to pursue innovative approaches to disease prevention, diagnosis and treatment. To be of value for Genomic Medicine research, bio-banked samples must be connected to clinical data: MyCode allows genetic and molecular data about the samples to be connected to medical data in a way that protects patient identity. When a patient agrees to participate in MyCode, blood samples for the MyCode Project are collected during blood draws ordered as part of the patient''s routine medical care. After the sample is drawn and labeled, a staff member from the Weis Center for Research transports the blood to the Geisinger Clinic Genomics Core (GCGC) where it is processed for storage. At this stage, all personal identification markers are removed and the samples are assigned a randomly-selected identification number. A secure key is maintained that allows approved researchers to connect the samples to the clinical data for genomic studies in a way that ensures confidentiality of the information. To maintain confidentiality of MyCode data the code linking the research numbers and the electronic health records are kept in a password-protected files accessible only to MyCode team members. Additionally, all results generated from the samples are reported as a group so that individuals are not identified. The samples are stored indefinitely.

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• SciCrunch
• 16 years ago - by Anonymous

Genome browser that encodes the genome sequence by physico-chemical dinucleotide properties such as stacking energy, melting temperature or twist angle. Analyses can be performed for the + and ?, as well as for the double strand.

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• SciCrunch
• 13 years ago - by Anonymous

A graphical tool for sequence finishing (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)

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• SciCrunch
• 13 years ago - by Anonymous

A variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. Bambino may be launched online via Java Web Start or downloaded and run locally.

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• SciCrunch
• 13 years ago - by Anonymous

Software to easily visualize the short reads alignment, identify the genetic variation and associate with the annotation information of reference genome. MagicViewer provides a user-friendly interface in which large-scale short reads and sequencing depth can be easily visualized in zoomable images under user definable color scheme through an operating system-independent manner with the implement of Java language. Meanwhile, it holds a versatile genetic variation annotation and visualization interface, providing details of the query options, functional classifications, subset selection, sequence association and primer design.

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• SciCrunch
• 13 years ago - by Anonymous

Established in 1986, the Center for AIDS Prevention Studies (CAPS) at the University California, San Francisco (UCSF) is the world''s largest research center dedicated to social, behavioral, and policy science approaches to HIV. The mission of the CAPS is to conduct research to prevent new HIV infections, improve health outcomes among those infected, and reduce disparities. This is how we do it: * CAPS provides core support for multidisciplinary and high-impact HIV research, enhances the excellence of research projects, trains a new generation of HIV scientists, and assists implementing partners. * Our Administrative Core provides strong leadership and management to stimulate innovative research and ensure scientific rigor and sound fiscal operations. * Our Developmental Core fosters innovative, high-impact, multidisciplinary HIV research by providing funds for innovative pilot work, sponsoring training and education, and ensuring the scientific excellence of research. * Our Methods Core provides comprehensive methodological training and consultation in research design, qualitative and quantitative analysis, and state-of-the-art data collection and management. * Our Policy and Ethics Core stimulates and supports policy-relevant research, identifies and analyzes the policy and ethics implications of research, and ensures the highest ethical conduct of research. * Our Technology and Information Exchange (Domestic Response) Core responds to the domestic epidemic by disseminating information, fostering community collaborative research, providing technical assistance and capacity-building to community-based organizations, and learning from community expertise. * Our Global Response Core responds to the global epidemic by fostering collaborative research with scientists in developing countries, completing and disseminating Cochrane Collaborative scientific reviews, and providing technical assistance, capacity building, and an evidence base to implementing partners.

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• SciCrunch
• 15 years ago - by Anonymous