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1,037 results for “large-scale”
Data used in JGR-A paper "Observational relationship between the Convective Aggregation, Sea Surface Temperature, and Large-scale circulation"
<p>Data used in the JGR-A paper "Observational relationship between the Convective Aggregation, Sea Surface Temperature, and Large-scale circulation" by Shuhei Matsugishi and Masaki Satoh </p>
Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation
<p>Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. The paper can be found at https://arxiv.org/pdf/2206.08023.pdf</p> <p>In addition to providing the labeled 600 CT and MRI scans, we expect to provide 2000 CT and 1200 MRI scans without labels to support more learning tasks (semi-supervised, un-supervised, domain adaption, ...). The link can be found in:</p> <ul> <li><a href="https://zenodo.org/deposit/7262581">labeled data (500CT+100MRI)</a></li> <li><a href="https://zenodo.org/record/7262757#.Y2iSQ9JBwYs">unlabeled data Part I (900CT)</a></li> <li><a href="https://zenodo.org/record/7295661#.Y2iR_9JBwYs">unlabeled data Part II (1100CT)</a> (Now there are 1000CT, we will replenish to 1100CT)</li> <li><a href="https://zenodo.org/record/7295816">unlabeled data Part III (1200MRI)</a></li> </ul> <p>if you found this dataset useful for your research, please cite:</p> <blockquote> <pre>@inproceedings{NEURIPS2022_ee604e1b, author = {Ji, Yuanfeng and Bai, Haotian and GE, Chongjian and Yang, Jie and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhanng, Lingyan and Ma, Wanling and Wan, Xiang and Luo, Ping}, booktitle = {Advances in Neural Information Processing Systems}, editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh}, pages = {36722--36732}, publisher = {Curran Associates, Inc.}, title = {AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation}, url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/ee604e1bedbd069d9fc9328b7b9584be-Paper-Datasets_and_Benchmarks.pdf}, volume = {35}, year = {2022} } </pre> </blockquote> <p> </p>
STAVER: A Standardized Dataset-Based Algorithm for Efficient Variation Reduction in Large-Scale DIA MS Data
<p>This project focuses on the development and application of STAVER, a standardized dataset-based algorithm designed to reduce variation in large-scale data-independent acquisition (DIA) mass spectrometry data. By using a reference dataset to standardize mass spectrometry signals, STAVER effectively reduces noise and enhances protein quantification accuracy, especially in the context of multi-library search. The effectiveness of STAVER is demonstrated in several large-scale DIA datasets, showing improved identification and quantification of thousands of proteins. The project aims to promote the adoption of multi-library search and improve the quality of DIA proteomics data through the open-source STAVER software package.</p>
Codes for A hidden connection of meso-scale convective rainfall and large-scale circulations over the eastern Pacific
<h4><strong>README</strong></h4><h4><strong>System requirments</strong></h4><ul><li><strong>Figure 1, ED_Figure_1, and ED_FIGURE_3</strong>: IDL (v8.5) on Linux OS</li><li><strong>Figure 3, Figure 4, ED_Figure_4, and ED_FIGURE_5</strong>: Python (v3.7.3) on Linux OS</li><li><strong>Figure 2 and ED_Figure_2</strong>: Sigmaplot (v10.0)</li></ul><h4><strong>Installation guide</strong></h4><p>The modules needed to run are in each directory. Each code requires execution time of less than 1 minute.</p><h4><strong>Demo</strong></h4><p>Sample data, code, and expected output are located in their repective directories.</p><h4><strong>Instruction for use</strong></h4><p>IDL code) type <i>idl</i> to enter IDL mode</p><p>idl> .r (figure name).pro </p><p>Python code) </p><p>> python (figurename).py</p>
Large-scale Chemical Screen Identifies a Geroprotective Role of Gallic Acid in Premature Aging
GEO Series GSE181445. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Large-scale tethering of RNA binding proteins discovers alternative splicing regulators
GEO Series GSE100638. Homo sapiens. 220 samples. Type: Expression profiling by high throughput sequencing; Expression profiling by array.
Large-scale characterisation of cell line xenografts identifies SMAD4 as key regulator of breast cancer morphology and aggressiveness
GEO Series GSE263474. Homo sapiens. 39 samples. Type: Expression profiling by high throughput sequencing.
Engineering Large-Scale and Innervated Functional Human Gut for Transplantation
GEO Series GSE233439. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni
GEO Series GSE146720. Schistosoma mansoni. 12 samples. Type: Expression profiling by high throughput sequencing.
Large-scale manipulation of radial positioning does not affect most aspects of genome organization
GEO Series GSE276554. Homo sapiens. 8 samples. Type: Other.
Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes
GEO Series GSE313593. Canis lupus familiaris. 114 samples. Type: Expression profiling by array.
MYC activation and BCL2L11 silencing by a tumor virus through the large-scale reconfiguration of enhancer-promoter hubs
GEO Series GSE82150. Homo sapiens. 10 samples. Type: Other.
Large-scale tethering of RNA binding proteins discovers alternative splicing regulators [microarray]
GEO Series GSE100600. Homo sapiens. 172 samples. Type: Expression profiling by array.
Large-Scale Gene Expression Profiling of Developing Soybean Seeds of Evans
GEO Series GSE61350. Glycine max. 10 samples. Type: Expression profiling by array.
Large-scale analysis of the chicken transcriptomes
GEO Series GSE247725. Gallus gallus. 403 samples. Type: Expression profiling by array.
Analysis of Gsk-3-Deficient Embryonic Stem Cells Reveals Large-Scale Alterations in Gene Expression
GEO Series GSE27395. Mus musculus. 12 samples. Type: Expression profiling by array.
Database (1/5) for manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa'
<p>******************************************************************************************************************************************************<strong>NOTICE: </strong>all datasets and tools provided in this database can and should only be used to reproduce the original experiment for which the database was created. The use of any datasets and tools in this database is subject to third party restrictions. Before copying or using this database for other purposes than reproducing the original experiment for which it was created, please ask for adequate authorisations to the author (Moctar Dembélé, mocdembele@gmail.com), who might additionaly need the authorization of the providers of the data and the tools available in this database. ******************************************************************************************************************************************************</p> <p>This database provides model inputs and outputs for the manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa' by Dembélé et al.</p> <p>This is part 1 out of 5 of the full database.</p> <p>-input_morpho_calib contains the morphological data and the datasets used for model calibration and runs.</p> <p>-input_WFDEI contains the input datasets using meteorological variable from the WFDEI product in combination with different rainfall datasets.</p> <p>Other parts of the database can be found at:</p> <p>-Part 2: https://doi.org/10.5281/zenodo.3663063</p> <p>-Part 3: https://doi.org/10.5281/zenodo.3663065</p> <p>-Part 4: https://doi.org/10.5281/zenodo.3663069</p> <p>-Part 5: https://doi.org/10.5281/zenodo.3663071</p> <p>For further information, please contact Moctar Dembélé, mocdembele@gmail.com</p> <p> </p>
Database (5/5) for manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa'
<p>******************************************************************************************************************************************************<strong>NOTICE: </strong>all datasets and tools provided in this database can and should only be used to reproduce the original experiment for which the database was created. The use of any datasets and tools in this database is subject to third party restrictions. Before copying or using this database for other purposes than reproducing the original experiment for which it was created, please ask for adequate authorisations to the author (Moctar Dembélé, mocdembele@gmail.com), who might additionaly need the authorization of the providers of the data and the tools available in this database. ******************************************************************************************************************************************************</p> <p>These datasets are parts of the database for the manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa' by Dembélé et al.</p> <p>It contains parts of the output datasets used to calibrate and run the hydrological model.</p> <p>The folders contains the model outputs when using the input data from different data providers, i.e., ERA5, EWEMBI, JRA55, MERRA, PGF.</p> <p>Check the main database at https://doi.org/10.5281/zenodo.3662308</p> <p>For further information, please contact Moctar Dembélé, mocdembele@gmail.com</p>
Database (3/5) for manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa'
<p>******************************************************************************************************************************************************<strong>NOTICE: </strong>all datasets and tools provided in this database can and should only be used to reproduce the original experiment for which the database was created. The use of any datasets and tools in this database is subject to third party restrictions. Before copying or using this database for other purposes than reproducing the original experiment for which it was created, please ask for adequate authorisations to the author (Moctar Dembélé, mocdembele@gmail.com), who might additionaly need the authorization of the providers of the data and the tools available in this database. ******************************************************************************************************************************************************</p> <p>These datasets are parts of the database for the manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa' by Dembélé et al.</p> <p>It contains parts of the input datasets used to calibrate and run the hydrological model.</p> <p>Check the main database at https://doi.org/10.5281/zenodo.3662308</p> <p>For further information, please contact Moctar Dembélé, mocdembele@gmail.com</p>
Database (2/5) for manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa'
<p>******************************************************************************************************************************************************<strong>NOTICE: </strong>all datasets and tools provided in this database can and should only be used to reproduce the original experiment for which the database was created. The use of any datasets and tools in this database is subject to third party restrictions. Before copying or using this database for other purposes than reproducing the original experiment for which it was created, please ask for adequate authorisations to the author (Moctar Dembélé, mocdembele@gmail.com), who might additionaly need the authorization of the providers of the data and the tools available in this database. ******************************************************************************************************************************************************</p> <p>These datasets are parts of the database for the manuscript 'Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa' by Dembélé et al.</p> <p>It contains parts of the input datasets used to calibrate and run the hydrological model.</p> <p>Check the main database at https://doi.org/10.5281/zenodo.3662308</p> <p>For further information, please contact Moctar Dembélé, mocdembele@gmail.com</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.