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heiDATA is an institutional repository for Open Research Data from Heidelberg University. It is managed by the Competence Centre for Research Data, a joint institution of the University Library and the Computing Centre. If you are interested in publishing your data here, please have a look at our user guide and get in touch with us. Detailed information on heiDATA can be found in our service description.
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1 to 10 of 5,360 Results
Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]
Sep 21, 2023 - Division of Infectious Disease and Tropical Medicine
FIND, Geneva, Switzerland, 2023, "Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]", https://doi.org/10.11588/data/CYYNBA, heiDATA, V1
The current four symptom screen recommended by the WHO is widely used as screen to initiate diagnostic testing for active pulmonary tuberculosis (TB), yet the performance is poor especially when TB prevalence is low. In contrast, more sensitive molecular tests are less suitable f...
MSD_SAMPLES_Clinical_data_2020-01-24_final_public.xlsx
Sep 21, 2023 - Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]
MS Excel Spreadsheet - 185.7 KB - MD5: 1b9a87245edb6a6ddbdb7dec4adeb7a8
Accurate classification of major brain cell types using in vivo imaging and neural network processing
Sep 18, 2023 - Functional Neuroanatomy
Johannes Knabbe, 2023, "Accurate classification of major brain cell types using in vivo imaging and neural network processing", https://doi.org/10.11588/data/L3PITA, heiDATA, V1, UNF:6:j36lvBMAVhENUbq1px2P/Q== [fileUNF]
This dataset accompanies the article of the same title in the journal Plos Biology. It includes a) Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation (StardistTraining.tar.gz) b) The trained Stardist nucleus segmentation model (Stardi...
CelltypeClassificationExcInhNeurons.tar.gz
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Gzip Archive - 29.7 GB - MD5: 035e2486a24db6861eed153177632154
Raw and segmented data for training of the cell type classification of inhibitory and excitatory neurons
CelltypeClassification.tar.gz
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Gzip Archive - 74.1 GB - MD5: f2527438cbf5d761725af2f1bbb104b1
Raw and segmented data for training of the cell type classification
ClassificationTrainingDataSet.tab
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Tabular Data - 173 B - 3 Variables, 7 Observations - UNF:6:j36lvBMAVhENUbq1px2P/Q==
Ground truth data for the training of all classifiers
RawdataResults.tar.gz
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Gzip Archive - 31.4 GB - MD5: 4da0d9034783ab20bf15ee229ddebd85
Raw and segmented data for the results section of the paper
StardistModel.tar.gz
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Gzip Archive - 13.5 MB - MD5: 8e8d3adfb58a869f3309a41af92cfffd
Trained Stardist nucleus segmentation model
StardistTraining.tar.gz
Sep 18, 2023 - Accurate classification of major brain cell types using in vivo imaging and neural network processing
Gzip Archive - 137.2 MB - MD5: a4f518a9fed49359c4a9680320c00395
Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation
High‑status individuals are held to higher ethical standards [Dataset]
High‑status individuals are held to higher ethical standards [Dataset]
Sep 18, 2023 - AWI Experimental Economics
Trautmann, Stefan T.; Wang, Xianghong; Wang, Yijie; Xu, Yilong, 2023, "High‑status individuals are held to higher ethical standards [Dataset]", https://doi.org/10.11588/data/6IDG5V, heiDATA, V1, UNF:6:d4StHYIKqO6F0tAqF0pfUA== [fileUNF]
Although there is evidence for the generosity of high‑status individuals, there seems to be a strong perception that the elites are selfish and contribute little to others’ welfare, and even less so than poorer people. We argue that this perception may derive from a gap between n...
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