We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
The Rodent Brain WorkBench is the portal to atlases, databases and tools developed by the Neural Systems and Graphics Computing Laboratory (NeSys) at the Centre for Molecular Biology and Neuroscience (CMBN), University of Oslo, Oslo, Norway. The Rodent Brain WorkBench presents a collection of brain mapping and atlasing oriented database applications and tools. The main category of available data is high resolution mosaic images covering complete histological sections through the rat and mouse brain. A highly structured relational database system for archiving, retrieving, viewing, and analysing microscopy and imaging data, aiming at presentation in standardized brain atlas space, is used to present a series of web applications for individual research projects. * Brain Connectivity * Atlases of Mouse Brain Promoter Gene Expression * General Brain Atlas and Navigation Systems * Downloadable tools for 3-DVisualization Open Access: * Atlas 3D * Cerebro-Cerebellar I * Cerebro-Cerebellar II * Neurotransporter Atlas * Rat Hippocampus * Tet-Off Atlas I (PrP) * Tet-Off Atlas II (PrP/CamKII) * Whole Brain Connectivity Atlas The data presented have been produced in collaboration with a large number of laboratories in Europe and the United States.
Community portal for researchers and content management system for data and databases. Intended to provide common source of data to research community and data about Research Resource Identifiers (RRIDs), which can be used in scientific publications. Central service where RRIDs can be searched and created. Designed to help communities of researchers create their own portals to provide access to resources, databases and tools of relevance to their research areas. Adds value to existing scientific resources by increasing their discoverability, accessibility, visibility, utility and interoperability, regardless of their current design or capabilities and without need for extensive redesign of their components or information models. Resources can be searched and discovered at multiple levels of integration, from superficial discovery based on limited description of resource at SciCrunch Registry, to deep content query at SciCrunch Data Federation.
Software application as multi-omics data analysis workflow. Comprises genome-wide DNA methylation, targeted metabolomics and behaviour data pre-processing, and integrative analysis methods. Individuals of a cohort are clustered using Similarity Network Fusion (SNF), latent feature dimensions are uncovered using different unsupervised methods including Multi-Omics Factor Analysis (MOFA) and Multiple Correspondence Analysis (MCA), and correlations between -omics and phenotype dimensions are determined in downstream analyses including results visualisation.
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. Database and customized tools to study the PFAM protein domain content of the transcriptome for all expressed genes of Homo sapiens, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans tethered to both a genomics array repository database and a range of external information resources. GeneSpeed has merged information from several existing data sets including the Gene Ontology Consortium, InterPro, Pfam, Unigene, as well as micro-array datasets. GeneSpeed is a database of PFAM domain homology contained within Unigene. Because Unigene is a non-redundant dbEST database, this provides a wide encompassing overview of the domain content of the expressed transcriptome. We have structured the GeneSpeed Database to include a rich toolset allowing the investigator to study all domain homology, no matter how remote. As a result, homology cutoff score decisions are determined by the scientist, not by a computer algorithm. This quality is one of the novel defining features of the GeneSpeed database giving the user complete control of database content. In addition to a domain content toolset, GeneSpeed provides an assortment of links to external databases, a unique and manually curated Transcription Factor Classification list, as well as links to our newly evolving GeneSpeed BetaCell Database. GeneSpeed BetaCell is a micro-array depository combined with custom array analysis tools created with an emphasis around the meta analysis of developmental time series micro-array datasets and their significance in pancreatic beta cells.
Data processing software for x-ray diffraction data. AIMLESS scales together multiple observations of reflections, and merges multiple observations into an average intensity.
Software standardized pipeline for ATAC-seq data analysis with serial alignments. Leverages unique features of ATAC-seq data to optimize for speed and accuracy, and provides several unique analytical approaches. Downstream analysis is simplified by standard definition format, modularity of components, and metadata APIs in R and Python. Restartable, fault-tolerant, and can be run on local hardware, using any cluster resource manager, or in provided Linux containers. We also emphasize the advantage of aligning to the mitochondrial genome serially, which improves alignment and quality control metrics. Includes quality control plots, summary statistics, and variety of data formats.
Knowledgebase that uses ontologies to integrate phenotypic data from genetic studies of zebrafish with evolutionary variable phenotypes from the systematic literature of ostariophysan fishes. Users can explore the data by searching for anatomical terms, taxa, or gene names. The expert system enables the broad scale analysis of phenotypic variation across taxa and the co-analysis of these evolutionarily variable features with the phenotypic mutants of model organisms. The Knowledgebase currently contains 565,158 phenotype statements about 2,527 taxa, sourced from 57 publications, as well as 38,189 phenotype statements about 4,727 genes, retrieved from ZFIN. 2013-01-26.
Community portal for a distributed data sharing platform and open protocol for building apps. The Dat Project imagines a web of commons created by global communities on open and secure protocols.
Software application for robust comparative analysis and contamination removal for metagenomics. Implements robust method for removal of negative control and crossover taxa from the rest of samples. Analyzes results from taxonomic classifiers using interactive charts with emphasis on confidence level of classifications. In addition to contamination subtracted samples, provides shared and exclusive taxa per sample, thus enabling robust contamination removal and comparative analysis in environmental and clinical metagenomics.
Computational biology research at Memorial Sloan-Kettering Cancer Center (MSKCC) pursues computational biology research projects and the development of bioinformatics resources in the areas of: sequence-structure analysis; gene regulation; molecular pathways and networks, and diagnostic and prognostic indicators. The mission of cBio is to move the theoretical methods and genome-scale data resources of computational biology into everyday laboratory practice and use, and is reflected in the organization of cBio into research and service components ~ the intention being that new computational methods created through the process of scientific inquiry should be generalized and supported as open-source and shared community resources. Faculty from cBio participate in graduate training provided through the following graduate programs: * Gerstner Sloan-Kettering Graduate School of Biomedical Sciences * Graduate Training Program in Computational Biology and Medicine Integral to much of the research and service work performed by cBio is the creation and use of software tools and data resources. The tools that we have created and utilize provide evidence of our involvement in the following areas: * Cancer Genomics * Data Repositories * iPhone & iPod Touch * microRNAs * Pathways * Protein Function * Text Analysis * Transcription Profiling
Database of sequence data generated from high-throughput immunosequencing of the TCR beta chain (TRB) and B cell receptor (BCR) immunoglobulin heavy chain (IGH). This data comes from cells from NPOD donors.
Software package provides interface to HDF5 library from Python. The low-level interface is intended to be complete wrapping of the HDF5 API, while the high-level component supports access to HDF5 files, datasets and groups using established Python and NumPy concepts.
Membership supported, nonprofit organization established dedicated to improving the lives of persons affected by ataxia through support, education, and research. The Foundation's primary purpose is to support promising ataxia research and to provide vital programs and services for ataxia families. The Foundation first began direct funding of ataxia research through the NAF Research Seed-Money Program. Since that time, the Foundation has established additional research programs which have included programs such as the NAF Young Investigator Award, the NAF Fellowship Award and other research initiatives. NAF research programs continue to fund promising ataxia research studies throughout the world. The Foundation supports research in dominant ataxia (including SCAs), recessive ataxia (including Friedreich's) and sporadic ataxia. The Foundation has developed an extensive library of NAF brochures, fact sheets, books, and videos on ataxia. Also available to its members is the Foundation's quarterly news publication, Generations. This 48 page ataxia news magazine provides the latest information on ataxia research, articles on living with ataxia, personal accounts from ataxia families throughout the United States, and much more.
Project that aims to provide a collection of Gold Standard gene phylogenies to the scientific community. This set of reference gene trees is suitable for phylogenomic databases to assess their current quality status, measure changes following new database releases and diagnose improvements subsequent to an upgrade of the analysis procedure.
Core provides consultative, laboratory, and bioinformatic services for next generation sequencing based applications.Core services include Pre- and post-experimental consultation to determine proper experimental approach, design, and interpretation; Standalone RNA preparation, RNA and DNA Bioanalyzer analyses, chromatin shearing/shear checks; Sample quality assessment of DNA and RNA using the BioAnalyzer and Qubit assays; Library preparation, sequencing, and analysis of transcriptomes (RNA-seq), cistromes (ChIP-seq), chromatin accessibility (ATAC-seq); Standalone sequencing on NextSeq500; Multiplexed 10x Single Cell/Nucleus Library RNA-seq Droplet generation, Library Preparation; Basic data analysis: quality assessment and normalization, genomic alignment, differential expression/enrichment, functional enrichment analysis (overrepresentation and GSEA), sample clustering, and motif enrichment; Bespoke data analysis, including integration of complex ChIP-seq and RNA-seq data sets, single-cell sequencing analyses.Core is located on the 7th floor of the Center for Life Sciences building in the Longwood Medical area (3 Blackfan Circle, CLS-728).
An open source C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way. Its broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. It can also be used from the Chimera molecular modeling system, or via one of several web applications.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 5th,2023. Core facility for the Emory Epithelial Pathobiology Research Development Center.
Software R package for pathway analysis in scRNA-seq data. It’s a different approach to pathway analysis that defines pathway activity as a change in multivariate distribution of a given pathway across conditions, rather than enrichment or over representation of genes.
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A community-driven knowledgebase of Alzheimer disease, in which researchers can annotate scientific claims, data, and information, putting these into the context of testable hypotheses and treatment discovery. This SWAN project adds a collection of hand-curated hypotheses to a research paper, which are then related through a set of discourse relationships. They can be browsed and relations between claims, as well as support networks for a specific claim, are made and visualized. AlzSWAN is where you explore scientific knowledge about Alzheimer disease and share your own ideas, comments and questions in a semantically structured system. AlzSWAN is enabled by Semantic Web technology, a new standard for knowledge organization and transfer on the Web. AlzSWAN organizes and manages knowledge using formal knowledge descriptions called ontologies. Using these formal knowledge descriptions, they can tie statements made in scientific publications or on the Web to scientific evidence, biological terminologies, and knowledgebases, and to claims and counterclaims made by other researchers.
Software basecaller for Oxford Nanopore Technologies' sequencers.