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Dataset results
278 results for “metabolic modeling”
single-cell RNAseq data (data set 8) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset8) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor6 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p> </p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a></p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 7) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset7) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor5 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p> </p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a></p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 19) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset19) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from Liver cancer set 2 samples downloaded from the GEO website (GSE125449)<strong>. </strong></p> <p> </p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a></p> <p>For more information, version updates of the scFASTCORMICS. </p>
Discretized bulk data by the discretization step of rFASTCORMICS used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>Bulk data RNAseq data were downloaded from GEO, GTEX, and other sources (see below) and discretized by the discretization step of rFASTCORMICS (Pacheco et al, 2019) used in the optimization step in scFASTCORMICS:</p> <p>CRC bulk RNAseq data were obtained from Lee et al(2020) <br> CRC control (NM) was downloaded from GSE81861 (GTEX, Healthy colon from)</p> <p>Pancreatic Human islet bulk RNAseq data was downloaded from EBI Expression Atlas (Pancreatic islet cells)</p> <p>Immune cells in pancreatic carcinoma bulk data were obtained from GEO (GSE156278)</p> <p>liver and breast cancer bulk RNAseq data were obtained from the TCGA (GSE62944)</p> <p> </p> <p>rFASTCORMICS and tutorial on rFASTCORMICS can be found: https://github.com/sysbiolux</p> <p> </p> <p> </p> <p> </p> <p><br> </p>
single-cell RNAseq data (data set 5) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset5) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor3 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 15) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset15) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from CD8 T-cells in PACA samples downloaded from the GEO website (GSE156728)<strong>. </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 4) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset4) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor2 downloaded from the GEO website (<strong>GSE114297). </strong></p> <p> </p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
single-cell RNAseq data (data set 3) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset3) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from normal Pancreas donor1 downloaded from the GEO website (GSE114297)<strong>. </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p> <pre> </pre>
Development and validation of metabolic models for predicting survival and immune status of hepatocellular carcinoma patients
<p>Supplementary materials for the article titled “Development and validation of metabolic models for predicting survival and immune status of hepatocellular carcinoma patients”</p>
Assembling the anaerobic gamma-butyrobetaine to TMA metabolic pathway in Escherichia fergusonii and confirming its role in TMA production from dietary L-carnitine in murine models
<p>GraphPad Prism files containing source data for figures included in the manuscript "Assembling the anaerobic gamma-butyrobetaine to TMA metabolic pathway in Escherichia fergusonii and confirming its role in TMA production from dietary L-carnitine in murine models", by Dwidar et al., published in mBio.</p>
Designing a Synthetic Microbial Community through Genome Metabolic Modeling to enhance Plant-Microbe Interaction
<p>Supplementary data 1 - <strong>Reconstructed genome-scale metabolic networks from MAGs and Hosts</strong></p> <p>Supplementary data 2 - P<strong>lant growth-promoting traits among members of the minimal community</strong></p> <p> </p> <p>Manipulating the rhizosphere microbial community through beneficial microorganism inoculation has gained interest in improving crop productivity and stress resistance. Synthetic microbial communities, known as SynCom, mimic natural microbial compositions while reducing the number of components. However, achieving this goal requires a comprehensive understanding of natural microbial communities and a careful selection of compatible microorganisms with colonization traits, which still pose challenges. In this study, we employed an <em>in-silico</em> approach using genome metabolic modeling to design a synthetic microbial community aimed at improving the yield of important crop plants. We used a targeted approach to select a minimal community (MinCom) encompassing essential compounds for microbial metabolism and compounds relevant to plant interactions. This resulted in a reduction of the initial community size by approximately 4.5-fold. Notably, the MinCom retained crucial genes associated with essential plant growth-promoting traits, such as iron acquisition, EPS production, potassium solubilization, nitrogen fixation, GABA production, and IAA-related tryptophan metabolism. Furthermore, our selection process for the SymCom, based on a comprehensive understanding of microbe-microbe-plant interactions, yielded a set of six hub species that displayed notable taxonomic novelty, including members of the Eremiobacterota and Verrucomicrobiota phyla. Our study contributes to the growing body of research on synthetic microbial communities and their potential to enhance agricultural practices. The insights gained from our in-silico approach and the selection of hub species pave the way for further investigations into the development of tailored microbial communities that can optimize crop productivity and improve stress resilience in agricultural systems.</p>
Data from Genome scale metabolic network modelling for metabolic profile predictions
<p>Data used to produce figures 4, 5 and 6 in the paper Genome scale metabolic network modelling for metabolic profile predictions.</p>
Coronary Imaging and Metabolic Indicators-Based Risk Prediction Model for Coronary Artery Disease(CMI-RiskCAD)
ClinicalTrials.gov study NCT07353762. IPD Sharing: NO. Countries: 1. Publications: 1.
River metabolism in the contiguous United States: Random forest model code, inputs and outputs
Open the record for dataset details and reuse information.
Metabolic profiles of melanoma patients and PDX models
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Data from: Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model
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Evaluating transcriptomic integration for cyanobacterial constraint-based metabolic modelling
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Dataset - Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies
<p>Models developed for the manuscript “Large-scale kinetic metabolic models of<em> Pseudomonas putida</em> for consistent design of metabolic engineering strategies" by M. Tokic, V. Hatzimanikatis, and L. Miskovic.</p> <ul> <li>Thermodynamically curated and gap-filled genome-scale model of <em>P. putida</em> iJN1411, iJN1411cur. <ul> <li>CuratediJN1411GEM.mat</li> </ul> </li> <li>Three systematically reduced stoichiometric models of <em>P. putida</em>: <ul> <li>D1 model, RedModelD1SminP2.mat</li> <li>D2 model, RedModelD2SminP2.mat - used for the studies performed in the manuscript</li> <li>D3 model, RedModelD3SminP2.mat</li> </ul> </li> </ul> <p> </p>
Dataset for Metabolic Cost Calculations of Gait using Musculoskeletal Energy Models, a Comparison Study
<p>This data set contains raw and processed data of gait analysis experiments of level and inclined walking at two speeds for 12 participants. The slopes were uphill and downhill with 8% incline. The raw data contains the output of the force plates and marker data, as well as raw measurements from an K4B2 system. Mat files are processed data: measured metabolic rate, and measured and calculated metabolic cost, as well as kinetic and kinematic data of an averaged gait cycle: joint angles, velocities and moments, ground reaction forces, muscle activation, contractile element length and stimulation, and the duration of the gait cycle.</p>
Age-dependent modulation of bone metabolism in zebrafish scales as new model of male osteoporosis in lower vertebrates
<p>After middle age, in human bone, the resorption usually exceeds formation resulting in bone loss and increased risk of fractures in the aged population. Only few in vivo models in higher vertebrates are available for pathogenic and therapeutic studies about bone aging. Among these, male Danio rerio (zebrafish) can be successfully used as low vertebrate model to study degenerative alterations that affect the skeleton during aging, reducing the role of sex hormones.In this paper, we investigated the early bone aging mechanisms in male zebrafish (3, 6, 9 months old) scales evaluating the physiological changes and the effects of prednisolone, a pro-osteoporotic drug.The results evidentiated an age-dependent reduction of the mineralization rate in the fish scales, as highlighted by growing circle measurements. Indeed, the osteoblastic ALP activity at the matrix deposition site was found progressively downregulated.The higher TRAP activity was found in 63% of 9-month-old fish scales associated with resorption lacunae along the scale border. Gene expression analysis evidentiated that an increase of the tnfrsf1b (homolog of human rank) in aging scales may be responsible for resorption stimulation.Interestingly, prednisolone inhibited the physiological growth of the scale and induced in aged scales a more significant bone resorption compared with untreated fish (3.8% vs 1.02%). Bone markers analysis shown a significant reduction of ALP/TRAP ratio due to a prednisolone-dependent stimulation of tnfsf11 (homolog of human rankl) in scales of older fish.The results evidentiated for the first time the presence of a senile male osteoporosis in lower vertebrate. This new model could be helpful to identify the early mechanisms of bone aging and new therapeutic strategies to prevent age-related bone alterations in humans.</p>
ScienceDex guides
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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.