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870 results for “Model development”
Development of a physiological insulin resistance model in human stem cell-derived adipocytes
GEO Series GSE201908. Homo sapiens. 21 samples. Type: Expression profiling by high throughput sequencing.
RNA-sequencing reveals novel molecular mechanisms of endometriosis lesion development in a mouse model
GEO Series GSE255418. Mus musculus. 36 samples. Type: Expression profiling by high throughput sequencing.
Development of potent antibody drug conjugates against ICAM1+ cancer cells in preclinical models of cholangiocarcinoma
GEO Series GSE233818. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Development and Characterization of Syngeneic Orthotopic Transplant Models of Obesity-Responsive Triple-Negative Breast Cancer in C57BL/6J Mice (in vivo)
GEO Series GSE272328. Mus musculus. 24 samples. Type: Expression profiling by array.
Human blastoids model blastocyst development and implantation [Bulk RNA-seq]
GEO Series GSE179040. Homo sapiens. 61 samples. Type: Expression profiling by high throughput sequencing.
Stem cell-derived trophoblast organoids model human placental development and susceptibility to emerging pathogens
GEO Series GSE172241. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Model code and data for "Mitigation of the double ITCZ syndrome in BCC-CSM2-MR through improving parameterizations of boundary-layer turbulence and shallow convection" by Lu et al., submitted to Geoscientific Model Development, https://doi.org/10.5194/gmd-2020-40, in review, 2020.
<p>Description of the files:</p> <p>“BCC_CSM2_MR.code.tar” contains the codes and run scripts for the medium-resolution Beijing Climate Center Climate System Model version 2 (BCC-CSM2-MR). Detailed description of the model refers to the paper “The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6” by Wu et al., Geosci. Model Dev., 12, 1573–1600, https://doi.org/10.5194/gmd-12-1573-2019, 2019.</p> <p>“BCC_CSM2_MR.inputdata.tar” contains the input data needed to run the model.</p> <p>“REF_amip.rar” contains the output data from the REF_amip experiment.</p> <p>“NEW_amip.rar” contains the output data from the NEW_amip experiment.</p> <p>“REF_cmip.rar” contains the output data from the REF_cmip experiment.</p> <p>“NEW_cmip.rar” contains the output data from the NEW_cmip experiment.</p> <p>“UWMT_amip.rar” contains the output data from the UWMT_amip experiment.</p> <p>“mHack_amip.rar” contains the output data from the mHack_amip experiment.</p>
Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests
<p>The .xlsx dataset includes all patients used for training, internal-external and external validation: these can be distinguished by looking at the ID (first column) in the dataset: those in format Axxxx-<Date> are the data used for the training, those in the format 20xx are the data used for the internal-external validation, while the remaining data were used for external validation.</p> <p>As regards the features: for the Target feature the value 1 stands for "Positive to COVID-19" while the value 0 stands for "Negative to COVID-19"; while for the Sex feature the value 1 stands for "Male" while the value 0 stands for "Female".</p> <p>The full article is available at: https://www.degruyter.com/view/journals/cclm/ahead-of-print/article-10.1515-cclm-2020-1294/article-10.1515-cclm-2020-1294.xml.</p> <p>A pre-print version of the article is also available on MedrXiv: https://www.medrxiv.org/content/10.1101/2020.10.02.20205070v1</p> <p><strong>ABSTRACT</strong></p> <p><strong>Background</strong> The rRT-PCR test, the current gold standard for the detection of coronavirus disease (COVID-19), presents with known shortcomings, such as long turnaround time, potential shortage of reagents, false-negative rates around 15–20%, and expensive equipment. The hematochemical values of routine blood exams could represent a faster and less expensive alternative. </p> <p><strong>Methods</strong> Three different training data set of hematochemical values from 1,624 patients (52% COVID-19 positive), admitted at San Raphael Hospital (OSR) from February to May 2020, were used for developing machine learning (ML) models: the complete OSR dataset (72 features: complete blood count (CBC), biochemical, coagulation, hemogasanalysis and CO-Oxymetry values, age, sex and specific symptoms at triage) and two sub datasets (COVID-specific and CBC dataset, 32 and 21 features respectively). 58 cases (50% COVID-19 positive) from another hospital, and 54 negative patients collected in 2018 at OSR, were used for internal-external and external validation.</p> <p><strong>Results</strong> We developed five ML models: for the complete OSR dataset, the area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.83 to 0.90; for the COVID-specific dataset from 0.83 15 to 0.87; and for the CBC dataset from 0.74 to 0.86. The validations also achieved good results: respectively, AUC 16 from 0.75 to 0.78; and specificity from 0.92 to 0.96. </p> <p><strong>Conclusions</strong> ML can be applied to blood tests as both an adjunct and alternative method to rRT-PCR for the fast and cost-effective identification of COVID-19-positive patients. This is especially useful in developing countries, or in countries facing an increase in contagions.</p>
Integration of Activity Specification into DEVS Modeling & Simulation Development Environment
<p>We propose an integrative environment for the modeling and simulation of activity specification. The devised approach relies on the DEVS (Discrete Event System Specification) formalism for the foundational semantics of the essential activity elements. The code generation takes place afterward, targeting specific DEVS-compliant modeling and simulation (M&S) environments such as DEVS-Suite and MS4 Me. The modelers can set parameters or modify the code to satisfy specific needs. The simulation can then be conducted with behavior monitoring and visualization. We demonstrate the approach with observations about performance evaluation and tracking. Such environments have the potential to facilitate computational model development for System of Systems via full-scale simulation support.</p>
S1_raw_images paper "Use of dual-flow bioreactor to develop a simplified model of nervous-cardiovascular systems crosstalk: a preliminary assessment
<p>Original uncropped and unadjusted images underlying all blot or gel results reported in a submission’s figures and Supporting Information files.</p>
Data from: Models of knot and stem development in black spruce trees indicate a shift in allocation priority to branches when growth is limited
The branch autonomy principle, which states that the growth of individual branches can be predicted from their morphology and position in the forest canopy irrespective of the characteristics of the tree, has been used to simplify models of branch growth in trees. However, observed changes in allocation priority within trees towards branches growing in light-favoured conditions, referred to as 'Milton's Law of resource availability and allocation,' have raised questions about the applicability of the branch autonomy principle. We present models linking knot ontogeny to the secondary growth of the main stem in black spruce (Picea mariana (Mill.) B.S.P.), which were used to assess the patterns of assimilate allocation over time, both within and between trees. Data describing the annual radial growth of 445 stem rings and the three-dimensional shape of 5,377 knots were extracted from optical scans and X-ray computed tomography images taken along the stems of 10 trees. Total knot to stem area increment ratios (KSR) were calculated for each year of growth, and statistical models were developed to describe the annual development of knot diameter and curvature as a function of stem radial increment, total tree height, stem diameter, and the position of knots along an annual growth unit. KSR varied as a function of tree age and of the height to diameter ratio of the stem, a variable indicative of the competitive status of the tree. Simulations of the development of an individual knot showed that an increase in the stem radial growth rate was associated with an increase in the initial growth of the knot, but also with a shorter lifespan. Our results provide support for 'Milton's Law,' since they indicate that allocation priority is given to locations where the potential return is the highest. The developed models provided realistic simulations of knot morphology within trees, which could be integrated into a functional-structural model of tree growth and above-ground resource partitioning.
The development of unlike induced association-site models to study the phase behaviour of aqueous mixtures comprising acetone, alkanes and alkyl carboxylic acids with the SAFT-g Mie group contribution methodology
<p>All computational data presented in the figures.</p>
The grid-level fixed asset model developed for China from 1951 to 2020
<p>This dataset was created by our submitted manuscript (with the same title as this dataset), in which the provincial-level and grid level fixed assets for China from 1951 to 2020 were developed.</p>
Outputs of the "Passenger demand mobility model" developed for South Asia
<p>This dataset comprises outputs and intermediate calculations of the passenger mobility demand model developed for South Asian regions. The dataset includes the following: </p> <ul> <li>'Total_PDT.zip' folder contains files of the type <em><strong>total_pdt_scename_j_m.csv</strong></em>: <ul> <li> These CSV files are the model output that contain passenger distance travelled (PDT) by mode in each area type and distance category for daily travel; and PDT by mode for long distance travel in different scenarios (scen_name), type of urbanisation (j), and mode share trajectory (m).</li> <li><strong>scename</strong>- This refers to the scenarios considered which are as follows - 'Base', 'NP', 'BP', 'TOD and 'TECH'</li> <li><strong>j</strong>- This refers to the type of urbanisation trajectories considered and are defined as follows: <ul> <li>1 - <a href="../api/records/10303828/draft/files/Urbanisation_type_trajectory_1.csv/content">Urbanisation_type_trajectory_1.csv</a></li> <li>2 - <a href="../api/records/10303828/draft/files/Urbanisation_type_trajectory_2.csv/content">Urbanisation_type_trajectory_2.csv</a></li> </ul> </li> <li><strong>m</strong>- This refers to the mode share trajectories considered in this study and are defined as follows: <ul> <li>1- Business as Usual (BaU)</li> <li>2- Car-oriented future (COF)</li> <li>3- Sustainable future (SF)</li> </ul> </li> </ul> </li> </ul> <ul> <li>Trip rates calculated for SSP 2- <a href="../api/records/10303828/draft/files/trip_rate_2.csv/content">trip_rate_2.csv</a></li> </ul> <p> </p>
Sea ice model outputs developed in "Modelling Antarctic sea ice variability using a brittle rheology"
<p>Output files from the BBM, mEVP and mEVP+ runs developed in the paper entlited "Modelling Antarctic sea ice variability using a brittle rheology". </p> <p>Paper abstract:</p> <p>Sea ice is a composite solid material that sustains large fracture features at scales from metres to kilometres which can play an important role in coupled atmosphere-ocean processes. To model these features, brittle sea ice physics, via the Brittle-Bingham-Maxwell (BBM) rheology, has been implemented in the Lagrangian neXt generation Sea Ice Model (neXtSIM). In Arctic-only simulations the BBM rheology has shown a capacity to represent observationally consistent sea ice fracture patterns and breakup across a wide range of time and length scales. Still, it has not been tested whether this approach is suitable for the modelling of Antarctic sea ice. Here, we introduce a new 50-km grid-spacing Antarctic configuration of neXtSIM, neXtSIM-Ant, using the BBM rheology. We evaluate this simulation against observations of sea ice extent, drift, and thickness and compare it with identically-forced neXtSIM simulations that use the standard modified Elastic-Visco-Plastic (mEVP) rheology. In general, using BBM results in thicker sea ice and an improved representation of sea ice drift than mEVP. We suggest that this is related to short-duration breakup events caused by Antarctic storms that are not captured in the viscous-plastic model. </p>
Figure 6 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 6 Linearity of the developed RP-HPLC D_5d stability indicating method.
Figure 2 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 2 Chromatogram of standard solution of the analyzed hydrazone D-5d (tR = 6.110).
Figure 1 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 1 Structure of the selected model compound.
Data generated by our developed theoretical asperity contact creep model
<p>The uploaded data was generated by our developed theoretical asperity contact creep model of interfacial friction for Geomaterials, including excel-style data and origin-style data.</p>
Dataset related to article: "Development of a nanocarrier-based approach for the blood-brain barrier passage in a murine model of amyotrophic lateral sclerosis"
<p>Raw data figures 3, 4, 5, 6</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.