Curator Dashboard

A network of protein-protein, protein-DNA and modulatory interactions in human B cells. The network contains known interactions (reported in public databases) and predicted interactions by a Bayesian evidence integration framework which integrates a variety of generic and context specific experimental clues about protein-protein and protein-DNA interactions with inferences from different reverse engineering algorithms, such as GeneWays and ARACNE. Modulatory interactions are predicted by the MINDY, an algorithm for the prediction of modulators of transcriptional interactions (please refer to the publication section for more information). The BCI can be downloaded as one tab delimited file containing the complete network (BCI.txt) with each type of interaction explicitly defined.

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• SciCrunch
• 17 years ago - by Anonymous

Biological Concept Diagram Editor (BCDE) is a conceptual relationship diagramming tool specifically designed for biomedical researchers. It allows for efficient knowledge and data capture, fast diagram creation, easy data retrieval, and flexible exporting. The BCDE application is the main diagramming tool in the system. Through it, users can create, modify, load, and save BCDE diagrams. The diagrams created with BCDE application are network oriented. Each BCDE figure can be annotated using fields from the BioPAX level II format. In addition, a user can add URL links and attachments to a BCDE figure. Diagrams generated in BCDE are stored in the BCDE XML format for better database integration and better data extraction.

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• SciCrunch
• 17 years ago - by Anonymous

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

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• SciCrunch
• 17 years ago - by Anonymous

Many science fairs have a group of people called a Scientific Review Committee (or SRC) that reviews each project application to ensure that all safety and legal requirements will be met and that the appropriate forms have been completed. The committee also reviews the completed project displays. Typically, a Scientific Review Committee is composed of at least three people: a biomedical scientist, a physical scientist, and a science teacher. Some fairs also have an Institutional Review Board (IRB), which reviews all proposed projects that in any way involve human beings. An IRB''s purpose is to ensure that the project will not present undue risk to the subjects.

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• 17 years ago - by Anonymous

GeneTraffic is a web-based microarray data analysis and management software developed by Iobion Informatics that allows users to log onto a server, upload their microarray data and perform analysis and project management remotely. GeneTraffic was made by Iobion Informatics (now under Stratagene) and can be accessed thorough Internet Explorer 6.0 or greater on Windows XP.

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• SciCrunch
• 17 years ago - by Anonymous

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

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• SciCrunch
• 17 years ago - by Anonymous

This portal provides information about the neuroscience department at the University of Cambridge. Cambridge has a strong tradition in neuroscience having been host to the first analyses of neural signaling in the 1930s, determined the mechanisms of neuronal firing in the 1950s, and heralded some of the early theoretical approaches to the functions of neural circuitry in the 1960s. Neuroscience continues to grow at Cambridge, with an impressive record of achievement in multidisciplinary research.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An initiative to build connections among the many powerful resources across the region. Between colleges and universities, pharmaceutical and biotechnology companies, device developers, startups and service businesses, the Cure Corridor, Einsteins''s Alley, the Pharm Belt, or whatever you like to call the region, offers opportunities for discovery and development of new therapies that is unmatched. Sponsors: The NeuroScience Network is made possible, in part, through funding from Bio 1 WIRED.

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• 17 years ago - by Anonymous

Phenol-Explorer is the first comprehensive web-based database on polyphenol content in foods. It contains more than 37 000 original data points collected from 638 scientific articles published in peer-reviewed journals. The quality of these data has been evaluated before they were aggregated to produce final representative mean content values for 502 polyphenols in 452 foods. The web interface allows making various queries on the aggregated data to identify foods containing a given polyphenol or polyphenols present in a given food. For each mean content value, it is possible to trace all original content values and their literature sources. Phenol-Explorer is a major step forward in the development of databases on food constituents and the food metabolome. It should help researchers to better understand the role of phytochemicals in the technical and nutritional quality of food, and food manufacturers to develop tailor-made healthy foods. Sponsors: The project has been supported by the NUTRIALIS program of the French Ministry of Research (2002-2004) and by Unilever, Danone and Nestl (2005-2009).

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• SciCrunch
• 17 years ago - by Anonymous

V3D is a handy, fast, and versatile 3D/4D/5D Image Visualization & Analysis System for Bioimages & Surface Objects. It also provides many unique functions, is Open Source, supports a very simple and powerful plugin interface and thus can be extended & enhanced easily. V3D-Neuron is a powerful 3D neuron reconstruction, visualization, and editing software built on top of V3D. Both V3D and V3D-Neuron have recently been published in Nature Biotechnology (April, 2010), and Highlighted in Nature Methods (May, 2010), and Science News (April, 2010), etc. V3D is a cross-platform (Mac, Linux, and Windows) tool for visualizing large-scale (gigabytes, and 64-bit data) 3D image stacks and various surface data. It is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. This makes V3D suitable for various bioimage informatics applications, and a nice platform to develop new 3D image analysis algorithms for high-throughput processing. In short, V3D streamlines the workflow of visualization-assisted analysis. In the latest V3D development, it can render 5D (spatial-temporal) data directly in 3D volume-rendering mode; it supports convenient and interactive local and global 3D views at different scales. It even has a Matlab file IO toolbox. A user can now write his/her own plugins to take advantage of the V3D platform very easily.

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 27, 2013. Web-based portal to connect all the constituencies in the global biobank community. The project seeks to increase the transparency and accessibility of the scientific research process by connecting researchers with an additional source of funding - microinvestments received from the broader online community. In exchange for these public investments, researchers will maintain research logs detailing the play-by-play progress made in their project, as well as publishing all of their data in a public database under a science commons license. These research projects, in turn, will serve to continually update a research-based neuroscience-based human brain & body curriculum. Biobanks are the meeting point of two major information trends in biomedical research: the generation of huge amounts of genomic and other laboratory data, and the electronic capture and integration of patient clinical records. They are comprised of large numbers of human biospecimens supplemented with clinical data. Biobanks when implemented effectively can harness the power of both genomic and clinical data and serve as a critical bridge between basic and applied research, linking laboratory to patient and getting to cures faster. As science and technology leaders work to address the many challenges facing U.S. biobanks logistical, technical, ethical, financial, intellectual property, and IT BioBank Central will serve as an accurate and timely source of knowledge and news about biorepositories and their role in research and drug development. The Web site also provides a working group venue, patient and public education programs, and a forum for international collaboration and harmonization of best practices.

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• SciCrunch
• 17 years ago - by Anonymous

The data for the smoking challenge consisted exclusively of discharge summaries from Partners HealthCare which were preprocessed and converted into XML format, and separated into training and test sets. I2B2 is a data warehouse containing clinical data on over 150k patients, including outpatient DX, lab results, medications, and inpatient procedures. ETL processes authored to pull data from EMR and finance systems Institutional review boards of Partners HealthCare approved the challenge and the data preparation process. The data were annotated by pulmonologists and classified patients into Past Smokers, Current Smokers, Smokers, Non-smokers, and unknown. Second-hand smokers were considered non-smokers. Other institutions involved include Massachusetts Institute of Technology, and the State University of New York at Albany. i2b2 is a passionate advocate for the potential of existing clinical information to yield insights that can directly impact healthcare improvement. In our many use cases (Driving Biology Projects) it has become increasingly obvious that the value locked in unstructured text is essential to the success of our mission. In order to enhance the ability of natural language processing (NLP) tools to prise increasingly fine grained information from clinical records, i2b2 has previously provided sets of fully deidentified notes from the Research Patient Data Repository at Partners HealthCare for a series of NLP Challenges organized by Dr. Ozlem Uzuner. We are pleased to now make those notes available to the community for general research purposes. At this time we are releasing the notes (~1,000) from the first i2b2 Challenge as i2b2 NLP Research Data Set #1. A similar set of notes from the Second i2b2 Challenge will be released on the one year anniversary of that Challenge (November, 2010).

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, it has been replaced by Monarch Initiative. LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal model for their research. LAMDHI is a free, Web-based, resource to help researchers bridge the gap between bench testing and human trials. It provides a free, unbiased resource that enables scientists to quickly find the best animal models for their research studies. LAMHDI includes mouse data from MGI, the Mouse Genome Informatics website; zebrafish data from ZFIN, the Zebrafish Model Organism Database; rat data from RGD, the Rat Genome Database; yeast data from SGD, the Saccharomyces Genome Database; and fly data from FlyBase. LAMHDI.org is operational today, and data is added regularly. Enhancements are planned to let researchers contribute their knowledge of the animal models available through LAMHDI. The LAMHDI goal is to allow researchers to share information about and access to animal models so they can refine research and testing, and reduce or replace the use of animal models where possible. LAMHDI Database Search: LAMHDI brings together scientifically validated information from various sources to create a composite multi-species database of animal models of human disease. To do this, the LAMHDI database is prepared from a variety of sources. The LAMHDI team takes publicly available data from OMIM, NCBI''s Entrez Gene database, Homologene, and WikiPathways, and builds a mathematical graph (think of it as a map or a web) that links these data together. OMIM is used to link human diseases with specific human genes, and Entrez provides universal identifiers for each of those genes. Human genes are linked to their counterpart genes in other species with Homologene, and those genes are linked to other genes tentatively or authoritatively using the data in WikiPathways. This preparatory work gives LAMHDI a web of human diseases linked to specific human genes, orthologous human genes, homologous genes in other species, and both human and non-human genes involved in specific metabolic pathways associated with those diseases. LAMHDI includes model data that partners provide directly from their data structures. For instance, MGI provides information about mouse models, including a disease for each model, as well as some genetic information (the ID of the model, in fact, identifies one or more genes). ZFIN provides genetic information for each zebrafish model, but no diseases, so zebrafish models are integrated by using the genes as the glue. For instance, a zebrafish model built to feature the zebrafish PKD2 gene would plug into the larger disease-gene map at the node representing the zebrafish PKD2 gene, which is connected to the node representing the human PKD2 gene, which in turn is connected to the node representing the human disease known as polycystic kidney disease. (Some of the partner data LAMHDI receives can even extend the base map. MGI provides a disease for every model, and in some cases this allows the creation of a disease-to-gene relationship in the LAMHDI database that might not already be documented in the OMIM dataset.) With curatorial and model information in hand, LAMHDI runs a lengthy automated process that exhaustively searches for every possible path between each model and each disease in the data, up to a set number of hops, producing for each disease-to-model pair a set of links from the disease to the model. The algorithm avoids circular paths and paths that include more than one disease anywhere in the middle of the path. At the end of this phase, LAMHDI has a comprehensive set of paths representing all the disease-to-model relationships in the data, varying in length from one hop to many hops. Each disease-to-model path is essentially a string of nodes in the data, where each node represents a disease, a gene, a linkage between genes (an orthologue, a homologue, or a pathway connection, referred to as a gene cluster or association), or a model. Each node has a human-friendly label, a set of terms and keywords, and - in most cases - a URL linking the node to the data source where it originated. When a researcher submits a search on the LAMHDI website, LAMHDI searches for the user''s search terms in its precomputed list of all known disease-to-model paths. It looks for the terms not only in the disease and model nodes, but also in every node along each path. The complete set of hits may include multiple paths between any given disease-to-model pair of endpoints. Each of these disease-to-model pair sets is ordered by the number of hops it involves, and the one involving the fewest hops is chosen to represent its respective disease-to-model pair in the search results presented to the user. Results are sorted by scores that represent their matches. The number of hops is one barometer of the strength of the evidence linking the model and the disease; fewer hops indicates the relationship is stronger, more hops indicates it may be weaker. This indicator works best for comparing models from a single partner dataset: MGI explicitly identifies a disease for each mouse model, so there can be disease-to-model hits for mice that involve just one hop. Because ZFIN does not explicitly identify a disease for each model, no zebrafish model will involve fewer than four hops to the nearest disease, from the zebrafish model to a zebrafish gene to a gene cluster to a human gene to a human disease.

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• 17 years ago - by Anonymous

A viewing program for Statistical Parametric Mapping (SPM2, SPM5 and SPM8). p-value slider, displays multiple images at a time and can be used to build Region of Interest (ROI) masks. For a given region you can find the anatomical name and search the selected region in online database (wiki, Google scholar and PubMed).

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• 17 years ago - by Anonymous

The Transgenic Hydra Facility is a non-profit facility in the laboratory of Thomas Bosch at the University of Kiel that assists scientists to use and to develop transgenic Hydra polyps. Our mission is to provide investigators access to the latest technology for the efficient production of transgenic polyps. We particularly encourage scientists from laboratories lacking the infrastructure for transgenic Hydra technologies to use our services. Abstract: Understanding the evolution of development in large part relies on the study of phylogenetically old organisms. Cnidarians, such as Hydra, have become attractive model organisms for these studies. However, despite long-term efforts, stably transgenic animals could not be generated, severely limiting the functional analysis of genes. Here we report the efficient generation of transgenic Hydra lines by embryo microinjection. One of these transgenic lines expressing EGFP revealed remarkably high motility of individual endodermal epithelial cells during morphogenesis. We expect that transgenic Hydra will become important tools to dissect the molecular mechanisms of development at the base of the Metazoan tree. Sponsors: Financial support for this research was provided by the German Research Foundation [Deutsche Forschungsgemeinschaft Grants B0848/13 and SFB617.

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• 17 years ago - by Anonymous

The goal of this project is to decipher the transcriptional information contained in the extensive cis-acting DNA sequences that direct the patterns of gene expression that underlie animal development. Using the early embryo of the fruitfly Drosophila melanogaster as a model, these researchers are developing experimental and computational methods to systematically characterize and dissect the complex expression patterns and regulatory interactions already present prior to gastrulation. They have identified 37 principal regulatory factors within this network for initial analysis together with their target genes. Sponsors: This project is chiefly funded by a grant from NIGMS and NHGRI, R01 GM070444. Additional funding comes from grants to Michael Eisen, Sue Celniker, and Bernd Hamann.

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• 17 years ago - by Anonymous

Our genes and lifestyle factors, such as calorie rich diets and a lack of exercise, contribute to the development of Type 2 diabetes. But what we dont know is the exact nature of the genetic risk and how this interacts with lifestyle factors to cause diabetes. The Diabetes UK Warren 2 Group was formed in 1992 to investigate the genetic basis of Type 2 diabetes. The Group, comprising of researchers from six UK diabetes research centres, began by recruiting families into the study enriched for Type 2 diabetes ie having two or more siblings with the condition. With over 2000 individuals from 843 families in the collection, it is now being used to search for the genes that make people susceptible to Type 2 diabetes. When identifying susceptibility genes it is important to know how the gene affects normal metabolism in relatives without diabetes. In 1999. the Warren 2 Extension study recruited first degree relatives (siblings and children) of the original Warren 2 families, who did not have diabetes, in the knowledge that they would also be enriched with the same susceptibility genes. This study recruited 811 relatives without diabetes (586 offspring and 225 siblings) all of whom have undergone detailed metabolic assessment. A similar study was undertaken in Oxford called the Diabetes In Families (DIF) Study. In 2001, the Warren 2 Trios and Duos Study recruited 500 families from around the country consisting of an individual with Type 2 diabetes and both their parents (trios) or an individual with diabetes, one of their parents and at least 2 siblings (duos). In addition to this, a further 1500 individuals with diabetes were recruited as part of the Warren 2 Cases study. This website is run by the Diabetes Research department and the Centre for Molecular Genetics at the Peninsula Medical School and Royal Devon and Exeter Hospital, Exeter, UK.

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• 17 years ago - by Anonymous

The Tropical Disease Initiative aims to provide a kernel for open source drug discovery. Such kernel should allow scientists from laboratories, universities, institutes, and corporations to work together for a common cause: find new drugs against tropical disieases such as Malaria or Tuberculosis. Computation plays an increasing role in biology. The convergence between computing and biology suggests that open source methods can be used to organize early phase drug discovery. We argue that a new approach, which we call open source drug discovery, would significantly reduce the cost of discovering, developing and manufacturing cures for tropical diseases. First, it would give hundreds of scientists a practical way to donate urgently needed manpower. Second, open source discoveries would not be patented, permitting sponsors to award development contracts to the company that offered the lowest bid. Finally, competition from generic drug makers would keep manufacturing prices at or near the cost of production, significantly accelerating drug development for the 500 million people who currently suffer from tropical diseases. The TDI was initiated by: Thomas Kepler - Duke University Marc A. Marti-Renom - Prince Felipe Research Center, Valencia, Spain Stephen Maurer - University of California, Berkeley Arti Rai - Duke University Andrej Sali- University of California, San Francisco

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• 17 years ago - by Anonymous

Web server to search for tRNA genes in genomic sequence. If you would like to run tRNAscan-SE locally, you can get the UNIX source code (gzip''d tar file).

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• 14 years ago - by Anonymous

tRNAdb 2009 provides a powerful and fast search engine. Taxons can be identified by browsing the taxonomic tree or by using the search form. Queries can include DNA or RNA sequences, amino acid family, anticodon, references, Pubmed-ID of the reference, gene ID as well as comments. In addition, individual searches concerning sequence or structure characteristics are possible. The server accepts IDs of the new as well as the old tRNA database as queries and can perform BLAST searches. All sequences can be downloaded in several file- and alignment formats on the result list. This site is hosted and maintained in a cooperation between the universities of Leipzig (Germany), Marburg (Germany) and Strasbourg (France). Recent Visitors

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• 17 years ago - by Anonymous