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Found 7 result(s)
Currently, the IMS repository focuses on resources provided by the Institute for Natural Language Processing in Stuttgart (IMS) and other CLARIN-D related institutions such as the local Collaborative Research Centre 732 (SFB 732) as well as institutions and/or organizations that belong to the CLARIN-D extended scientific community. Comprehensive guidelines and workflows for submission by external contributors are being compiled based on the experiences in archiving such in-house resources.
This is a database for vegetation data from West Africa, i.e. phytosociological and dendrometric relevés as well as floristic inventories. The West African Vegetation Database has been developed in the framework of the projects “SUN - Sustainable Use of Natural Vegetation in West Africa” and “Biodiversity Transect Analysis in Africa” (BIOTA, https://www.biota-africa.org/).
The Cancer Immunome Database (TCIA) provides results of comprehensive immunogenomic analyses of next generation sequencing data (NGS) data for 20 solid cancers from The Cancer Genome Atlas (TCGA) and other datasource. The Cancer Immunome Atlas (TCIA) was developed and is maintained at the Division of Bioinformatics (ICBI). The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). Moreover it provides survival analyses for different types immunological parameters. TCIA will be constantly updated with new data and results.
ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.
ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional or subject-based repositories of the research communities. ZENODO enables researchers, scientists, EU projects and institutions to: easily share the long tail of small research results in a wide variety of formats including text, spreadsheets, audio, video, and images across all fields of science. display their research results and get credited by making the research results citable and integrate them into existing reporting lines to funding agencies like the European Commission. easily access and reuse shared research results.
BeiDare2 is currently at beta version. All new users should try the new service as we no longer provide training for the classic BioDare. - BioDare stands for Biological Data Repository, its main focus is data from circadian experiments. BioDare is an online facility to share, store, analyse and disseminate timeseries data, focussing on circadian clock data, with browser and web service interfaces. Toolbox features include an improved, speedier FFT-NLLs routine and ROBuST’s Spectrum Resampling tool that will analyse rhythmic time series data.