We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
Division of the South Korea government responsible for formulating national science and technology policies and plans.
Educational resources that provide accurate and unbiased information about topics in genetics, bioscience and health for global and local audiences. They are jargon-free, target multiple learning styles, and often convey concepts through animation and interactivity. The Genetic Science Learning Center is a science and health education program located in the midst of the bioscience research being carried out at the University of Utah. Our mission is making science easy for everyone to understand. * Two websites, available free of charge to Internet users worldwide: ** Learn.Genetics delivers educational materials on genetics, bioscience and health topics. They are designed to be used by students, teachers and members of the public. The materials meet selected US education standards for science and health. ** Teach.Genetics provides resources for K-12 teachers, higher education faculty, and public educators. These include PDF-based Print-and-Go™ activities, unit plans and other supporting resources. The materials are designed to support and extend the materials on Learn.Genetics. *Professional development programs that update K-16 teachers' expertise in bioscience and health topics as well as prepare them to implement the materials on our websites. * Community programs that engage with diverse communities in discussions about genetics and health, and in developing culturally and linguistically-appropriate educational materials. Some topics in genetics and bioscience research are controversial. The Center does not take sides in political or ethical controversies. Rather, our goal is to provide comprehensive information that promotes a lively discussion of these topics, so that individuals can arrive at their own informed decisions.
A Java consistency based multiple sequence alignment software program.
Software toolbox that manages your RNA-Seq and ChIP-Seq data and also produces many different plots to visualize your data. It performs several tasks that are usually required during the analysis of mapped RNA-Seq and ChIP-Seq reads, including data selection and data visualization. It includes the selection (or the exclusion) of the data that overlaps with a reference set, clustering and comparative analysis. It also provides many ways to visualize data: size of the reads, density on the genome, distance with respect to a reference set, and the correlation of two data sets (with cloud plots). A computer science background is not required to run it through a graphical interface and it can be run on any personal computer, yielding results within an hour for most queries.
Nonprofit American medical research facility that focuses on research and education in the biomedical sciences. Headquartered in San Diego, California with a sister facility in Jupiter, Florida, the institute has laboratories employing scientists, technicians, graduate students, and administrative and other staff, making it the largest private, non-profit biomedical research organization in the United States and among the largest in the world.
Public datasets that have been transcoded into multiple formats. This library of valid file format conversions (DICOM->NIFTI, DICOM->PAR/REC, etc.) will provide a reference for tool developers seeking to support multiple sources of data.
Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.
Software package consisting of a default back end, which prepares raw sequencing or Affymetrix microarray data, and a web-based front end, which offers a biologically centered interface to browse, visualize, and compare different data sets.
Tool that provides an interactive method to examine quantitative relationships between brain regions defined by different digital atlases or parcellation methods. Its current focus is for human brain imaging, though the techniques generalize to other domains. The method offers a quantitative answer to the nomenclature problem in neuroscience by comparing brain parts on the basis of their geometrical definitions rather than on the basis of name alone. Thus far these tools have been used to quantitatively compare eight distinct parcellations of the International Consortium for Brain Mapping (ICBM) single-subject template brain, each created using existing atlasing methods. This resources provides measures of global and regional similarity, and offers visualization techniques that allow users to quickly identify the correspondences (or lack of correspondences) between regions defined by different atlases.
Institute dedicated to research in science and technology in South Korea modeled after a research university.
Database providing a sequence-centered genome view for Arabidopsis thaliana, with a narrow focus on gene structure annotation. The current genome assembly displayed at AtGDB is version TAIR9. Annotated gene models are TAIR10. They have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing.
Postdoctoral positions within the UCSD Department of Psychiatry available for qualified candidates. The following are the available postdoctoral opportunities: - Post-Doctoral Position in Co-Occurring Disorders - Postdoctoral Positions in Behavioral Neuroscience in the areas of nicotine dependence, depression and schizophrenia - Postdoctoral Position in Neuroimaging and Twin Research - Postdoctoral Fellowship in Behavioral Neuroscience in the area of methamphetamine dependence and HIV
A project of the Mind and Life Institute, fosters multidisciplinary communication about scientific research on meditation and other contemplative practices. It is dedicated to fostering dialog and research at the highest possible level between modern science and the great living contemplative traditions, especially Buddhism. It builds on a deep commitment to the power and value of both of these ways of advancing knowledge and their potential to alleviate suffering. Membership is free, and this loose affiliation of scientists, meditators, and people interested in research promotes opportunities for researchers and meditators to communicate together. All perspectives, scientific fields, and styles of meditation are welcome. The MLRN includes cognitive neuroscientists who skillfully use scientific methods in the study of meditation, meditation scholars interested in scientific interfaces, and people who can help support meditation research. MLRN members are likely to be recruited to serve as advisors, referees, participants, and collaborators in upcoming studies on meditation. The MLRN encompasses a variety of meditation practices, and incorporates both contemplative and scientific approaches. The MLRN includes a low-volume, moderated electronic announcement list. This list maintains a high signal-to-noise ratio by distributing infrequent but important messages to large numbers of recipients. Members of this announcement list receive bibliographic updates on recent publications, announcements of upcoming conferences, calls for papers for special-issue journals and conference symposia, synopses of recent meetings, announcements of relevant email lists, websites, and other resources, and other announcements appropriate for widespread distribution. Sponsors: The Hershey Family Foundation has been patron since 1990. This Institute has received generous financial support from the Fetzer Institute, The Nathan Cummings Foundation, Branco Weiss, Adam Engle, Michael Sautman, Mr. and Mrs. R. Thomas Northcote, Christine Austin, Dennis Perlman, Marilyn and the late Don Gevirtz, Michele Grennon, Klaus Hebben, Joe and Mary Ellyn Sensenbrenner, and Edwin and Adrienne Joseph.
Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.
Society that develop standards for biological research data quality, annotation and exchange. They facilitate the creation and use of software tools that build on these standards and allow researchers to annotate and share their data easily. They promote scientific discovery that is driven by genome wide and other biological research data integration and meta-analysis. Historically, FGED began with a focus on microarrays and gene expression data. However, the scope of FGED now includes data generated using any technology when applied to genome-scale studies of gene expression, binding, modification and other related applications.
Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. It stores raw and normalized data from microarray experiments, as well as their corresponding image files. In addition, LAD provides interfaces for data retrieval, analysis, and visualization.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. ATGC stands for Alignable Tight Genomic Cluster, which is cluster of closely related prokaryotic genomes. ATGC is the principal notion of this web resource. The purpose of this web resource is to prepare ATGC-derived data sets for a variety of research projects in functional and evolutionary genomics. Unique features of ATGC include: * Reliable identification of orthologs (high degree of similarity between the genomes in the set allow an extensive use of synteny in ortholog identification); * Fine granularity of protein classification (in comparisons of more distant genomes, proteins belonging to families of paralogs are often lumped into a singlegroup; under the ATGC approach, comparison of genomic sequences from highly similar genomes allows one to track each set of orthologs separately); * Relative rarity of changes of any kind (in sequence, genome organization and gene content) allows the use of parsimony-related methods of analysis.
Software collection of libraries and tools for 3D reconstruction, geometric analysis, mesh generation and surface data analysis for image-based modeling of blood vessels.
Software package for Bayesian analysis of protein, DNA and RNA sequences. It utilizes multiple alignments, phylogenetic trees and evolutionary parameters to quantify uncertainty in these analyses. It is written in Java.