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281 results for “source code”
2023_ Datasets and R source code of "Effect of physiological hyperthermia on mitochondrial fuel selection in skeletal muscle of birds and mammals"
<p>GENERAL INFORMATION</p> <p>Title of Dataset: 2023_ Datasets and R source code of "Effect of physiological hyperthermia on mitochondrial fuel selection in skeletal muscle of birds and mammals" </p> <p>METHODOLOGICAL INFORMATION</p> <p>Datasets contain mitochondrial bioenergetic data of our comparative study from the skeletal muscle, of 8 pigeons and 8 rats with similar body mass.<br> Methodology: mitochondrial isolation, respiration (oxygen consumption measurements with assay temperature and substrate effects)</p> <p>## Description of the Data <br> First dataset "RatPigeon_Oxy_Flux"<br> ### Individual: subject number (1-8 for pigeons and 11-18 for rats)<br> ### Species: Rat or Pigeon<br> ### Temperature : assay temperature for the mitochondrial respiration(37°C, 40°C, 43°C)<br> ### Substrate: available substrate utilization, Pyruvate/Malate (PM) or PalmitoylCarnitine/Malate (PCM)<br> ### OXPHOS: phosphorylating respiration <br> ### LEAK: basal non-phosphorylating respiration rate <br> ### Coupling: control efficiency, flux control of ADP on substrate oxidation</p> <p>Second dataset "RatPigeon_Oxy_Ratio"<br> ### Individual: subject number (1-8 for pigeons and 11-18 for rats)<br> ### Species: Rat or Pigeon<br> ### Temperature : assay temperature for the mitochondrial respiration(37°C, 40°C, 43°C)<br> ### PCM.PM: fuel selection index (OXPHOSPCM/OXPHOSPM ratio). </p> <p>R Source code "code RatPigeon(Oxy).R". Complete analysis as one single R script. All analyses were performed in R version 4.2.1 (R Core Team 2022) using Linear Mixed Effect Model and Effect sizes.</p>
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1) - MONICA model source code and data
<p>Zip file consisting of the data used in the manuscript "Evaluation and optimisation of the soil carbon turnover routine in the MONICA model".<br> The data consists of 11 German long term experimenting field sites, formatted in MONICA readable input files. Each consisting of one dataset for weather information (.met), and three .json files describing the management, site and soil properties of each treatment. The validation datasets consist of soil temperature and soil moisture measurement and are distinguishable by the .vals file type/format.</p> <p>For further information please refer to the manuscript.</p>
Open source code for Brain-inspired bodily self-perception model for robot rubber hand illusion
<p><a href="https://github.com/Brain-Cog-Lab/RHI#rhi">RHI</a></p> <p><a href="https://github.com/Brain-Cog-Lab/RHI#rhi_matlab">RHI_Matlab</a></p> <p>This file is the open-source code for 'Brain-inspired bodily self-perception model for robot rubber hand illusion', mainly used in simulation environments, and can reproduce various rubber hand illusion experiments.</p> <p><a href="https://github.com/Brain-Cog-Lab/RHI#rhi_braincog">RHI_BrainCog</a></p> <p>We are building an open source spiking neural network based brain-inspired cognitive intelligence engine for Brain-inspired Artificial Intelligence and brain simulation. Therefore, we also implemented the core Proprioceptive drift experiment of the rubber hand illusion experiment using Braincog.</p> <p><a href="https://github.com/BrainCog-X/Brain-Cog/tree/main/examples/Embodied_Cognition/RHI">The open source code built by BrainCog</a></p> <p>BrainCog provides essential and fundamental components to model biological and artificial intelligence. The current version of BrainCog contains at least 18 functional spiking neural network algorithms (including but not limited to perception and learning, decision making, knowledge representation and reasoning, motor control, social cognition, etc.) built based on BrainCog infrastructures, and BrainCog also provide brain simulations to drosophila, rodent, monkey, and human brains at multiple scales based on spiking neural networks at multiple scales.</p>
Dataset of "Supersonic: Learning to Generate Source Code Optimizations in C/C++"
<p>This is the dataset of "<a href="https://arxiv.org/abs/2309.14846">Supersonic: Learning to Generate Source Code Optimizations in C/C++</a>".</p>
Non-coding regions are the main source of tumor-specific antigens [human]
GEO Series GSE113972. Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [CUT&RUN histone modifications in S2 cells]
GEO Series GSE247152. Drosophila melanogaster. 25 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
NASA open-source code projects with A.I.-generated tags
A JSON that is used to build the content on code.nasa.gov. This JSON contains names, descriptions, links, and keyword tags for all NASA open-sourced code projects released through the SRA (Software Release Authority) and available on code.nasa.gov. It was updated on August, 2019.
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [CUT&RUN in Drosophila species]
GEO Series GSE247153. Drosophila melanogaster; Drosophila yakuba; Drosophila simulans; Drosophila ananassae; Drosophila erecta. 30 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [RNA-seq]
GEO Series GSE247154. Drosophila melanogaster. 22 samples. Type: Expression profiling by high throughput sequencing.
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [sRNA-seq]
GEO Series GSE247155. Drosophila melanogaster. 17 samples. Type: Non-coding RNA profiling by high throughput sequencing.
SC20 VERITAS Source Code and Dataset
<p>This repository contains the dataset for the VERITAS work submitted for publication at SC20.</p>
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [ChIP-seq]
GEO Series GSE247334. Drosophila melanogaster. 25 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Dataset for Large-Scale Analysis of Modern Code Review Practices and Software Security in Open Source Software
Open the record for dataset details and reuse information.
A dual histone code specifies the binding of heterochromatin protein Rhino to a subset of piRNA source loci [CUT&RUN]
GEO Series GSE247150. Drosophila melanogaster. 9 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
MKAD (Open Sourced Code)
The Multiple Kernel Anomaly Detection (MKAD) algorithm is designed for anomaly detection over a set of files. It combines multiple kernels into a single optimization function using the One Class Support Vector Machine (OCSVM) framework. Any kernel function can be combined in the algorithm as long as it meets the Mercer conditions, however for the purposes of this code the data preformatting and kernel type is specific to the Flight Operations Quality Assurance (FOQA) data and has been integrated into the coding steps. For this domain, discrete binary switch sequences are used in the discrete kernel, and discretized continuous parameter features are used to form the continuous kernel. The OCSVM uses a training set of nominal examples (in this case flights) and evaluates test examples for anomaly detection to determine whether they are anomalous or not. After completing this analysis the algorithm reports the anomalous examples and determines whether there is a contribution from either or both continuous and discrete elements.
Source code and intermediate data for the tradeSeqDTU project
<p>Development: working folder for reproducing the results of the mock and performance benchmarks.</p> <p>Pancreas_case: intermediate data and code for the pancreas case study. The raw data is not yet included as this is still a project in progress, and the upload would be very large (15Gb)</p> <p>iPSC_case: intermediate data and code for the pancreas case study. The raw data is not yet included as this is still a project in progress, and the upload would be very large (32Gb)</p>
A source code of NICAM.19 for aerosol simulations with a global 14-km grid resolution
<p>The source code is able to calculate global aerosol distributions with a 14-km grid spacing and used in the simulations shown in the following manuscript:</p> <p>Goto, D., Seiki, T., Suzuki, K., Yashiro, H., Takemura, T.: Impacts of cloud microphysics schemes on aerosol fields in NICAM.19 with a global 14-km grid resolution, submitted to Geosci. Model Dev.</p>
Delft3D Source Code 5169
<p>Delft3D source code used in "The role of geological mouth islands on the morphodynamics of back-barrier tidal basins". Please upon request to the corresponding author.</p>
Aerosol 3-DVAR source code and Lidar data
<p>The code of this system can be obtained on request from the corresponding author</p>
Source code and data of CodeReviser in ASE2022
<p>The source code and datasets of CodeReviser in ASE2022.</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.