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Found 6 result(s)

iNaturalist.org

iNat

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iNaturalist is a citizen science project and online social network of naturalists, citizen scientists, and biologists built on the concept of mapping and sharing observations of biodiversity across the globe. iNat is a platform for biodiversity research, where anyone can start up their own science project with a specific purpose and collaborate with other observers.

Project Achilles

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Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/

Cancer Cell Line Encyclopedia

CCLE

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The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.

HJ Andrews Experimental Forest

HJA

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The Andrews Forest is a place of inquiry. Our mission is to support research on forests, streams, and watersheds, and to foster strong collaboration among ecosystem science, education, natural resource management, and the humanities. Our place and our work are administered cooperatively by the USDA Forest Service's Pacific Northwest Research Station, Oregon State University, and the Willamette National Forest. First established in 1948 as an US Forest Service Experimental Forest, the H.J. Andrews is a 16,000-acre ecological research site in Oregon's beautiful western Cascades Mountains. The landscape is home to iconic Pacific Northwest old-growth forests of Cedar and Hemlock, and moss-draped ancient Douglas Firs; steep terrain; and fast, cold-running streams. In 1980 the Andrews became a charter member of the National Science Foundation's Long-Term Ecological Research (LTER) Program.

PhenoGen Informatics

PhenoGen

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The PhenoGen website shares experimental data with a worldwide community of investigators and provides a flexible, integrated, multi-resolution repository of neuroscience transcriptomic genetic data for collaborative research on genomic disorders. The main development focus is on providing Hybrid Rat Diversity Panel transcriptomic data (sequencing, genome coverage, reconstructed totalRNA/smallRNA transcriptomes, quanification of the transcriptome, eQTLs, and WGCNA) and integrating additional tools to provide platform for visualization and analysis of HRDP transcriptome data.

Sicas Medical Image Repository

SMIR

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The SICAS Medical Image Repository is a freely accessible repository containing medical research data including medical images, surface models, clinical data, genomics data and statistical shape models. The data can freely be organized and shared on SMIR and made publicly accessible with a DOI. Dedicated data sets are organized as collections of anatomical regions (e.g Cochlea). The data can be filtered using a modular search and accessed on the web or through the SMIR API.