Curator Dashboard

A software package designed to determine the methylation parameter at each cytosine or cytosine-guanine position in the human genome. FadE uses color reads produced by the SOLiD sequencer or nucleotide reads produced by the Illumina or 454 sequencing platforms.

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• SciCrunch
• 13 years ago - by Anonymous

miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. miniTUBA represents in a network view possible influences that occur between time varying variables in your dataset. For these networks of influence, miniTUBA predicts time courses of disease progression or response to therapies. minTUBA offers a probabilistic framework that is suitable for medical inference in datasets that are noisy. It conducts simulations and learning processes for predictive outcomes. The DBN analysis conducted by miniTUBA describes from variables that you specify how multiple measures at different time points in various variables influence each other. The DBN analysis then finds the probability of the model that best fits the data. A DBN analysis runs every combination of all the data; it examines a large space of possible relationships between variables, including linear, non-linear, and multi-state relationships; and it creates chains of causation, suggesting a sequence of events required to produce a particular outcome. Such chains of causation networks - are difficult to extract using other machine learning techniques. DBN then scores the resulting networks and ranks them in terms of how much structured information they contain compared to all possible models of the data. Models that fit well have higher scores. Output of a miniTUBA analysis provides the ten top-scoring networks of interacting influences that may be predictive of both disease progression and the impact of clinical interventions and probability tables for interpreting results. The DBN analysis that miniTUBA provides is especially good for biomedical experiments or clinical studies in which you collect data different time intervals. Applications of miniTUBA to biomedical problems include analyses of biomarkers and clinical datasets and other cases described on the miniTUBA website. To run a DBN with miniTUBA, you can set a number of parameters and constrain results by modifying structural priors (i.e. forcing or forbidding certain connections so that direction of influence reflects actual biological relationships). You can specify how to group variables into bins for analysis (called discretizing) and set the DBN execution time. You can also set and re-set the time lag to use in the analysis between the start of an event and the observation of its effect, and you can select to analyze only particular subsets of variables.

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• SciCrunch
• 15 years ago - by Anonymous

Software using a beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.

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• SciCrunch
• 13 years ago - by Anonymous

Web application that allows users to build and manage online surveys and databases. Using REDCap's stream-lined process for rapidly developing projects, you may create and design projects using 1) the online method from your web browser using the Online Designer; and/or 2) the offline method by constructing a "data dictionary" template file in Microsoft Excel, which can be later uploaded into REDCap. Both surveys and databases (or a mixture of the two) can be built using these methods. REDCap provides audit trails for tracking data manipulation and user activity, as well as automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R). Also included are a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as branching logic, file uploading, and calculated fields. REDCap has a quick and easy software installation process, so that you can get REDCap running and fully functional in a matter of minutes. Several language translations have already been compiled for REDCap (e.g. Chinese, French, German, Portuguese), and it is anticipated that other languages will be available in full versions of REDCap soon. The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by researchers at REDCap partner institutions.

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• SciCrunch
• 14 years ago - by Anonymous

The Cancer Text Information Extraction System (caTIES) provides tools for de-identification and automated coding of free-text structured pathology reports. It also has a client that can be used to search these coded reports. The client also supports Tissue Banking and Honest Broker operations. caTIES focuses on two important challenges of bioinformatics * Information extraction (IE) from free text * Access to tissue. Regarding the first challenge, information from free-text pathology documents represents a vital and often underutilized source of data for cancer researchers. Typically, extracting useful data from these documents is a slow and laborious manual process requiring significant domain expertise. Application of automated methods for IE provides a method for radically increasing the speed and scope with which this data can be accessed. Regarding the second challenge, there is a pressing need in the cancer research community to gain access to tissue specific to certain experimental criteria. Presently, there are vast quantities of frozen tissue and paraffin embedded tissue throughout the country, due to lack of annotation or lack of access to annotation these tissues are often unavailable to individual researchers. caTIES has three goals designed to solve these problems: * Extract coded information from free text Surgical Pathology Reports (SPRs), using controlled terminologies to populate caBIG-compliant data structures. * Provide researchers with the ability to query, browse and create orders for annotated tissue data and physical material across a network of federated sources. With caTIES the SPR acts as a locator to tissue resources. * Pioneer research for distributed text information extraction within the context of caBIG. caTIES focuses on IE from SPRs because they represent a high-dividend target for automated analysis. There are millions of SPRs in each major hospital system, and SPRs contain important information for researchers. SPRs act as tissue locators by indicating the presence of tissue blocks, frozen tissue and other resources, and by identifying the relationship of the tissue block to significant landmarks such as tumor margins. At present, nearly all important data within SPRs are embedded within loosely-structured free-text. For these reasons, SPRs were chosen to be coded through caTIES because facilitating access to information contained in SPRs will have a powerful impact on cancer research. Once SPR information has been run through the caTIES Pipeline, the data may be queried and inspected by the researcher. The goal of this search may be to extract and analyze data or to acquire slides of tissue for further study. caTIES provides two query interfaces, a simple query dashboard and an advanced diagram query builder. Both of these interfaces are capable of NCI Metathesaurus, concept-based searching as well as string searching. Additionally, the diagram interface is capable of advanced searching functionalities. An important aspect of the interface is the ability to manage queries and case sets. Users are able to vet query results and save them to case sets which can then be edited at a later time. These can be submitted as tissue orders or used to derive data extracts. Queries can also be saved, and modified at a later time. caTIES provides the following web services by default: MMTx Service, TIES Coder Service

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• SciCrunch
• 15 years ago - by Anonymous

Software program providing a method for meta-analysis of case-control genetic association studies using random-effects logistic regression.

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• SciCrunch
• 13 years ago - by Anonymous

A biomedical ontology in the area of vaccine adverse events aimed to represent and analyze various vaccine-specific adverse events. OVAE is an extension of the Ontology of Adverse Events (OAE) and the Vaccine Ontology (VO).

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• SciCrunch
• 13 years ago - by Anonymous

A distributed file storage system that you can upload files to and download files from. All files uploaded to the repository are replicated several times to protect against their accidental loss. Files uploaded to the repository can be of any size, can be of any file type, and can be encrypted with a passphrase of your choosing. The Proteome Commons Tranche repository is the first instance of a Tranche repository. Tranche, was created so that anybody can take it and make their own Tranche repository. This is the first implementation of the Tranche software, and is useful as a test bed for the software. This repository relies on educational institutions to provide the hardware and facilities for Tranche servers. While we maintain a set of servers, the continued growth of this public resource will rely on the generosity of the institutions that use the repository most.

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• SciCrunch
• 17 years ago - by Anonymous

Public research university in Sha Tin, New Territories, Hong Kong.

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• SciCrunch
• 15 years ago - submitted by Stephen Larson

An ontology covering the domain of social entities that are related to health care, such as demographic information (social entities for recording gender (but not sex) and marital status, for example) and the roles of various individuals and organizations (patient, hospital, etc.)

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• SciCrunch
• 13 years ago - by Anonymous

A virtual biospecimen registry designed to support and facilitate basic science, clinical, and translational research that will advance understanding of mesothelioma pathophysiology with the goal of expediting the discovery of preventive measures, novel therapeutic interventions, and ultimately, cures for mesothelioma. The NMVB resource is designed to provide mesothelioma tissue samples with high-quality and well-characterized multimodal annotated data to researchers. The NMVB team strongly believes that progress in translational and clinical research - in cancer as well as other disease areas - depends on the ability of researchers to access high-quality tissue that is associated with meaningful annotation. MVB database version 3.0 has been released that provides researchers real-time access to demographic, epidemiologic, pathologic, genotype, and follow-up data associated with biospecimens at no cost. Researchers interested in utilizing NMVB samples for their research may submit an application. All researchers (academic or commercial, United States or foreign) may apply for NMVB tissue specimens. NMVB currently has 966 annotated cases and 1198 biospecimens including: * Paraffin Embedded Tissue * Fresh Frozen Tissue * Blood and DNA Samples The NMVB also has developed mesothelioma tissue microarrays (TMAs) with associated multimodal data annotation. Additional TMAs will be available shortly.

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• SciCrunch
• 17 years ago - by Anonymous

MIT's Department of Brain and Cognitive Sciences stands at the nexus of neuroscience, biology and psychology. We combine these disciplines to study specific aspects of the brain and mind including: vision, movement systems, learning and memory, neural and cognitive development, language and reasoning. Together, MIT's Department of Brain and Cognitive Sciences offers extraordinary learning opportunities for undergraduate, graduate and postdoctoral students. Because the human brain is immensely complex in many different ways at once, we pursue every level of inquiry - from molecules to cells to circuits to the mystery of the mind itself. As we study its diseases and disorders, its development and daily feats, like vision, speech, movement and memory, we also integrate methods and insights from every area of brain research. This unusual diversity of expertise fosters an intensely creative atmosphere that sparks startling collaborations. Already known for remarkable contributions to the field, our faculty members continually stretch the limits of knowledge, and bring the same passion to educating our exceptional students. A key part of the BCS mission is to offer its graduate and undergraduate students an educational experience of the highest quality. Our graduate students benefit from the impressive range of our program, and from the ability to participate in research projects with faculty members who are leaders in their fields. The department's undergraduate program, which includes both neuroscience and cognitive science, is one of the fastest-growing majors at MIT.

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• SciCrunch
• 16 years ago - by Anonymous

A database and annotation tool that provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene. To be processed, a valid Gene ID must exist for the specific gene, or the Gene staff must have assigned an overall Gene ID to the species. The latter case is implemented via records in Gene with the symbol NEWENTRY.

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• SciCrunch
• 13 years ago - by Anonymous

Software R package for simplfiying common tasks in genomic feature analysis. Toolkit to summarize, annotate and visualize genomic intervals. Provides functions for reading BED and GFF files as GRanges objects, summarizing genomic features over predefined windows so users can make average enrichment of features over defined regions or produce heatmaps. Can annotate given regions with other genomic features such as exons,introns and promoters.

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• SciCrunch
• 13 years ago - by Anonymous

SAGA (Substructure Index-based Approximate Graph Alignment) is a tool for querying a biological graph database to retrieve matches between subgraphs of molecular interactions and biological networks. SAGA implements an efficient approximate subgraph matching algorithm that can be used for a variety of biological graph matching problems such as the pathway matching SAGA uses to compare pathways in KEGG and Reactome. You can also use SAGA to find matches in literature databases that have been parsed into semantic graphs. In this use of SAGA, portions of PubMed have been parsed into graphs that have nodes representing gene names. A link is drawn between two genes if they are discussed in the same sentence (indicating there is potential association between the two genes). SAGA lets you match graphs between different databases even though the content is distinct and the databases organize pathways in different ways. This cross-database matching is achieved by SAGA's flexible approximate subgraph matching model that computes graph similarity, and allows for node gaps, node mismatches, and graph structural differences. Comparing pathways from different databases can be a useful precursor to pathway data integration. SAGA is very efficient for querying relatively small graphs, but becomes prohibitory expensive for querying large graphs. Large graph data sets are common in many emerging database applications, and most notably in large-scale scientific applications. To fully exploit the wealth of information encoded in graphs, effective and efficient graph matching tools are critical. Due to the noisy and incomplete nature of real graph datasets, approximate, rather than exact, graph matching is required. Furthermore, many modern applications need to query large graphs, each of which has hundreds to thousands of nodes and edges. TALE is an approximate subgraph matching tool for matching graph queries with a large number of nodes and edges. TALE employs a novel indexing technique that achieves a high pruning power and scales linearly with the database size.

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• SciCrunch
• 17 years ago - by Anonymous

Matches a list of microarray probes across different microrarray platforms (GeneChip, EST from different vendors, Operon Oligos) and species (human, mouse and rat), based on NCBI UniGene and HomoloGene. The capability to match protein sequence IDs has just been added to facilitate proteomic studies. The ProbeMatchDB is mainly used for the design of verification experiments or comparing the microarray results from different platforms. It can be used for finding equivalent EST clones in the Research Genetics sequence verified clone set based on results from Affymetirx GeneChips. It will also help to identify probes representing orthologous genes across human, mouse and rat on different microarray platforms.

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• SciCrunch
• 17 years ago - by Anonymous

For selected articles and letters Nature presents streaming videos featuring interviews with scientists behind the research and analysis from Nature editors. To view the videos you will need the free Flash browser plugin. You can also visit the Nature Video YouTube channel which enables you to easily embed and share our videos through websites, mobile devices, blogs and email.

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• SciCrunch
• 15 years ago - by Anonymous

Database that provides experimentally determined thermodynamic interaction data between proteins and nucleic acids. It contains the properties of the interacting protein and nucleic acid, bibliographic information and several thermodynamic parameters such as the binding constants, changes in free energy, enthalpy and heat capacity.

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• SciCrunch
• 17 years ago - by Anonymous

Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.

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• SciCrunch
• 15 years ago - by Anonymous

Software for meta-analysis of genome-wide SNP association results.

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• SciCrunch
• 13 years ago - by Anonymous