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Dataset results
453 results for “Dynamic dataset”
Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 3]
GEO Series GSE213908. Homo sapiens. 22 samples. Type: Other.
snRNA-seq dataset for "Morphine regulates astrocyte transcriptional dynamics by stimulation of glucocorticoid signaling"
GEO Series GSE308304. Rattus norvegicus. 14 samples. Type: Expression profiling by high throughput sequencing.
Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 4]
GEO Series GSE214123. Homo sapiens. 42 samples. Type: Other.
Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 1]
GEO Series GSE213295. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Dataset for "Characterization of stream, hyperconcentrated and debris flows from seismic signal: Insights into sediment transport mechanisms and flow dynamics"
<p>Yang et al. (2023) Dataset for "Characterization of stream, hyperconcentrated and debris flows from seismic signal: Insights into sediment transport mechanisms and flow dynamics", Journal of Geophysical Research-Earth Surface</p>
Dataset of Outlining a Novel Psychometric Model of Mental Flexibility and Affect Dynamics
<p>Theoretically, affective states have always been conceived as complex phenomena enabling individuals to respond flexibly and dynamically to environmental demands. Methodologically, the novel field of Affect Dynamics has started to analyze affective states as inherently dynamic and interdependent phenomena by focusing on how and why they fluctuate over time. Fluctuations of affective states can also be conceived as a function of individuals' ability to flexibly modulate their responses according to environmental demands. However, this ability has been sparsely investigated in different disciplines and domains, thus, engendering a plethora of terms and models. In this conceptual analysis, we first aimed to disentangle the puzzle of flexibility by outlining the distinctive cross-domain features of this concept, thus providing a novel comprehensive operationalization. We termed this novel unitary concept "mental flexibility," the general ability to variably adapt to environmental demands. Then, we outlined the interplay between individuals' mental flexibility and affect dynamics by proposing a novel psychometric model of affect dynamics, using Markovian chain</p>
ChemProp2 Dataset: Investigating potential biotransformations with a panel of 45 Drugs on Synthetic Community (Com20) to elucidate Drug-Microbiome-Host Dynamics
<p>This dataset contains the examination of each of the 45 drugs on the synthetic community Com20, conducted at two distinct timepoints: initially (time 0) and after a 2-hour interval.<br>List of drugs: Ethopropazine, Methotrexate, Felodipine, Miconazole, Floxuridine, Nalidixic acid, Fluconazole, Niclosamide, Ketoconazole, Omeprazole, Lacidipine, Pentamidine isothionate, DMSO, Promethazine, Lansoprazole, Protriptyline, Loratadine, Sertindole, Loxapine, Simvastatin, L-Thyroxine, Streptozotocin, Metformin, Tamoxifen, Tazobactam, Doxorubicin, Telmisartan, Ofloxacin, Terfenadine, Oxolinic acid, Thioguanosine, Tobramycin, Tiratricol, Vancomycin, Water, Rivaroxoban, Metronidazole, Tolfenamic acid, Clarithromycin, Tribenoside, Norfloxacin, Zafirlukast, Montelukast, Sertraline, Fluoxetine, Clomipramin, Novobiocin</p>
ChemProp2 Dataset: Investigating potential biotransformations with a panel of 23 Drugs on Synthetic Community (Com20) to elucidate Drug-Microbiome-Host Dynamics
<p>Tested 23 drugs against Synthetic community (Com20) at two different timepoints (t=0, t= 2 hrs) to look for potential biotransformations<br><br>List of drugs tested:<br>Acarbose, Clemizole, Amlodipine, Clindamycin, Amoxicillin, Clomifen, Aprepitant, Clotrimazole, Avermectin B1, Diacerein, Azithromycin, Dicumarol, Control, Dienestrol, Benzbromarone, Dienogest, Ceterizin, Doxycycline hyclate, Chlorpromazine, Duloxetin, Chlorprothixene, Erythromycin, Cilnidipine, Ethinylestradiol<br><br>Samples were measured (in March 18/19, 2023) using an UHPLC-Q Exactive HF Orbitrap mass spectrometer, equipped with a C18 column, following the LC-MS/MS method.</p>
Urban monthly land dynamics Sentinel-2 benchmark dataset
<p>The public data set of the paper "<strong>Time-series land cover change detection using deep learning-based temporal semantic segmentation</strong>" uses monthly synthesized Sentinel-2 for time series semantic change detection. A total of 32894 samples were collected. Each timestamp has a land cover type annotation. Anyone can use this data set to conduct further research. We will add more areas in the future. </p> <p><strong>Data description:</strong></p> <ol> <li>The time series length of the sample is 48, 48 months.</li> <li>Label mapping: 0 is water body, 1 is woodland, 2 is grassland, 3 is bare soil, 4 is impervious surface, 5 is cropland.</li> <li>For any implementation details, you can refer to the paper or github.</li> </ol> <p><strong>Paper citations:</strong></p> <p>He H, Yan J, Liang D, Sun Z, Li J, Wang L. Time-series land cover change detection using deep learning-based temporal semantic segmentation. Remote Sensing of Environment. 2024, 305:114101.</p>
Selective endocytosis controls slit diaphragm maintenance and dynamics - Supplementary Dataset
<p>Supplementary Dataset to Lang et al. "<strong>Selective endocytosis controls slit diaphragm maintenance and dynamics in <em>Drosophila</em> nephrocytes."</strong></p> <p>https://www.biorxiv.org/content/10.1101/2022.03.01.482547v1.full</p> <p>Contains unprocessed image files that were used to generate the main figures. </p>
Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in southern Siberia - dataset
<p>1. Dates_input: Result dates from U-series dating. Results are formatted for input into Copra (age modelling software) including depth from top (of stalagmite sb_pk7497-1 in mm), years (BP) and error. </p> <p>2. D13C Input: Result d13C from isotope ratio mass spectrometry. Results are formatted for input into Copra (age modelling software) including depth from top (of stalagmite sb_pk7497-1 in mm) and corrected (for minerology, see All_mid-resolution sheet) d13C results. </p> <p>3. Lev input: Result levoglucosan values from solid phase extraction analysis. Results are formatted for input into Copra (age modelling software) including depth from top (of stalagmite sb_pk7497-1 in mm). </p> <p>4. Lig SV input: Result SV values calculated from solid phase extraction analysis. Results are formatted for input into Copra (age modelling software) including depth from top (of stalagmite sb_pk7497-1 in mm). </p> <p>5. Lig CV input: Result CV values calculated from solid phase extraction analysis. Results are formatted for input into Copra (age modelling software) including depth from top (of stalagmite sb_pk7497-1 in mm). </p> <p>6. D13C output: All output files from copra age modelling of d13C results (see sheet 2). Results include age modelled dates in ka BP and years BP, d13C median values, 2.5% and 97.5% confidence intervals for d13C, and 2.5% and 97.5% confidence intervals for age, and depth from top. </p> <p>7. Lev output: All output files from copra age modelling of Lev results (see sheet 3). Results include age modelled dates in ka BP and years BP, Lev median values, 2.5% and 97.5% confidence intervals for Lev, and 2.5% and 97.5% confidence intervals for age, and depth from top. </p> <p>8. Lig output: All output files from copra age modelling of SV and CV results (see sheet 4 and 5). Results include age modelled dates in ka BP and years BP, SV and CV median values, 2.5% and 97.5% confidence intervals for SV and CV, and 2.5% and 97.5% confidence intervals for age, and depth from top. </p> <p>9. All mid-resolution: All oxygen and carbon isotope results from sb_pk7497-1 and corrections calculated from raman maps. </p>
Dataset The MLL1 trimeric catalytic complex is a dynamic conformational ensemble stabilized by multiple weak interactions and is susceptible to pharmacological disruption
<p>This dataset is related to <strong>"</strong>MLL1 minimal catalytic complex is a dynamic conformational ensemble susceptible to pharmacological allosteric disruption<strong>" </strong>(Lilia Kaustov, Alexander Lemak, Hong Wu, Marco Faini, Lixin Fan, Xianyang Fang, Hong Zeng, Shili Duan, Abdellah Allali-Hassani, Yong Wei, Masoud Vedadi, Ruedi Aebersold, Yunxing Wang, Scott Houliston, Cheryl H. Arrowsmith) . </p> <p>The repository contains the data used in the modeling of WDR5-RbBP5-MLL1 trimeric complex, the optimal ensemble of models, and the representative models for major and minor populations. The modeling is performed based on saxs and cross-link MS data, crystallographic structures, and comparative models using coarse-grained MD simulations and Sparse Ensemble Selection method (SES) for optimal ensemble selection.</p>
Molecular dynamics simulation dataset
<p>This dataset contains Molecular Dynamics trajectories of 9 endecapeptides, positioned in the pore construct. One trajectory is done in absence of any transolcating peptide.</p> <p>.xtc files correspond to the trajectories and the .gro files contain the corresponding structures, they can be viewed, for example, with VMD.</p> <p>Every trajectory is the concatenation of 8 trajectories, of 125 ns each, which differ for the orientation of the centrai side-chain with respect to the frame of the pore. The following name parts indicate the central residue. The 73-80 files correspond to the construct alone, taken as a reference. </p> <p>1-8 trp; 9-16 tyr; 17-24 arg; 25-32 his; 33-40 glu; 41-48 gln; 49-56 ser; 57-64 ile; 65-72 gly; 73-80 no peptide.</p>
"Basal conditions of Denman Glacier from glacier hydrology and ice dynamics modeling" datasets
<p>Data for hydrology and inversions in "Basal conditions of Denman Glacier from glacier hydrology and ice dynamics modeling"</p> <p>Denman_hydrology.mat - hydrology outputs from GlaDS.</p> <p>SchoofNoiseX.mat - stressbalance models with perturbed meshes, Schoof friction law, and GlaDS effective pressure extrapolated to the ISSM domain</p> <p>SchoofCapX.mat - stressbalance models with Schoof friction law, and GlaDS effective pressure extrapolated to the ISSM domain capped at X% of overburden</p> <p>SchoofPrescribed.mat - stressbalance model with Schoof friction law and prescribed effective pressure</p> <p>BuddPrescribed.mat - stressbalance model with Budd friction law and prescribed effective pressure</p> <p>SchoofPrescribedExtrapolation.mat - stressbalance model with Schoof friction law, GlaDS effective pressure for the GlaDS domain and prescribed effective pressure for the rest of the grounded domain</p> <p>BuddPrescribedRigidity.mat - stressbalance model with Budd friction law and prescribed effective pressure, ice rigidity is inverted for after the Budd friction coefficient</p> <p>SchoofPrescribedRigidity.mat - stressbalance model with Schoof friction law and prescribed effective pressure, ice rigidity is inverted for after the Schoof friction coefficient</p> <p>BuddMain - The main stressbalance model with Budd friction law and inverted rigidity used in the paper</p> <p>SchoofMain - The main stressbalance model with Schoof friction law and inverted rigidity used in the paper</p> <p>Buddm3 - stressbalance model with Budd friction law m=1/3 and GlaDS effective pressure</p> <p>Buddm3Prescribed - stressbalance model with Budd friction law m=1/3 and prescribed effective pressure</p> <p>SchoofCmax0X - stressbalance model with Schoof friction law C_max=0.X and GlaDS effective pressure</p> <p>SchoofCmax0XPrescribed - stressbalance model with Schoof friction law C_max=0.X and GlaDS effective pressure</p> <p> </p>
Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 2]
GEO Series GSE213386. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Dataset related to article "Spatial resolution of cellular senescence dynamics in human colorectal liver metastasis"
<p>Dataset related to article "Spatial resolution of cellular senescence dynamics in human colorectal liver metastasis"</p><p><strong>Abstract</strong></p><p>Hepatic metastasis is a clinical challenge for colorectal cancer (CRC). Senescent cancer cells accumulate in CRC favoring tumor dissemination. Whether this mechanism progresses also in metastasis is unexplored. Here, we integrated spatial transcriptomics, 3D-microscopy, and multicellular transcriptomics to study the role of cellular senescence in human colorectal liver metastasis (CRLM). We discovered two distinct senescent metastatic cancer cell (SMCC) subtypes, transcriptionally located at the opposite pole of epithelial (e) to mesenchymal (m) transition. SMCCs differ in chemotherapy susceptibility, biological program, and prognostic roles. Mechanistically, epithelial (e)SMCC initiation relies on nucleolar stress, whereby c- myc dependent oncogene hyperactivation induces ribosomal RPL11 accumulation and DNA damage response. In a 2D pre-clinical model, we demonstrated that RPL11 co-localized with HDM2, a p53-specific ubiquitin ligase, leading to senescence activation in (e)SMCCs. On the contrary, mesenchymal (m)SMCCs undergo TGFβ paracrine activation of NOX4-p15 effectors. SMCCs display opposing effects also in the immune regulation of neighboring cells, establishing an immunosuppressive environment or leading to an active immune workflow. Both SMCC signatures are predictive biomarkers whose unbalanced ratio determined the clinical outcome in CRLM and CRC patients. Altogether, we provide a comprehensive new understanding of the role of SMCCs in CRLM and highlight their potential as new therapeutic targets to limit CRLM progression.</p><p> </p>
Dataset related to the article "Feasibility and Accuracy of the Automated Software for Dynamic Quantification of Left Ventricular and Atrial Volumes and Function in a Large Unselected Population"
<p>This record contains raw data related to the article “Feasibility and Accuracy of the Automated Software for Dynamic Quantification of Left Ventricular and Atrial Volumes and Function in a Large Unselected Population”</p> <p>Abstract</p> <p>We aimed to evaluate the feasibility and accuracy of machine learning-based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes in an unselected population. We enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV, and LA volumes were obtained from 2D images; 3D images were analyzed using dynamic heart model (DHM) software (Philips) resulting in LV and LA volume-time curves. A subgroup of 140 patients also underwent cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded, and results were compared between 2DTTE, DHM, and CMR. The use of DHM was feasible in 522/600 cases (87%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n = 38) or minor (n = 149) border corrections were needed. The overall time required for DHM datasets was approximately 40 seconds. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173 ± 64 vs. 142 ± 58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55% ± 12 vs. 56% ± 14; LA volume 89 ± 36 vs. 89 ± 38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r = 0.70 and r = 0.82, <em>p</em> < 0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r = 0.82, <em>p</em> < 0.001) and LA volumes. The DHM software is feasible, accurate, and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation.</p>
Dataset related to article "Chemotherapy after PD-1 inhibitors in relapsed/refractory Hodgkin lymphoma: Outcomes and clonal evolution dynamics"
<p>This record contains raw data related to article "Chemotherapy after PD-1 inhibitors in relapsed/refractory Hodgkin lymphoma: Outcomes and clonal evolution dynamics"</p> <p>Checkpoint inhibitors (CPIs) are routinely employed in relapsed/refractory classical Hodgkin lymphoma. Nonetheless, persistent long-term responses are uncommon, and one-third of patients are refractory. Several reports have suggested that treatment with CPIs may re-sensitize patients to chemotherapy, however there is no consensus on the optimal chemotherapy regimen and subsequent consolidation strategy. In this retrospective study we analysed the response to rechallenge with chemotherapy after CPI failure. Furthermore, we exploratively characterized the clonal evolution profile of a small sample of patients (n = 5) by employing the CALDER approach. Among the 28 patients included in the study, 17 (71%) were primary refractory and 26 (92%) were refractory to the last chemotherapy prior to CPIs. Following rechallenge with chemotherapy, response was recorded in 23 (82%) patients experiencing complete remission and 3 (11%) patients experiencing partial remission. The tumour evolution of the patients inferred by CALDER seemingly occurred prior to the first cycle of therapy and was characterized either by linear or branching evolution patterns.Twenty-five patients proceeded to allogeneic stem cell transplantation. At a median follow-up of 21 months, median PFS and OS were not reached. In conclusion, patients who fail CPIs can be effectively rescued by salvage chemotherapy and bridged to allo-SCT/ auto-SCT.</p>
Experimental dataset: TEMPERATURE DEPENDENCE ON STOCHATIC DYNAMIC DIFFUSION COEFFICIENTS OF HEATED ELECTROSPRAY IONIZATION AND ATMOSPHERIC PRESSURE CHEMICAL IONIZATION MASS SPECTROMETRIC INTENSITIES OF ANALYTE IONS OF CONFIGURATIONALLY LOCKED POLYENES – THEORY AND EXPERIMENT
<p>Experimental dataset of heated electrospray ionization and atmospheric pressure chemical ionization mass spectra of configurationally locked polyenes. The dataset is empirical proof of the validity of our new model equation connecting among the stochatic dynamic diffusion parameter, the temperature and the mass spectrometric measurable variable 'intensity' of an observable peak of analyte ion.</p>
Dataset for "Global dominance of seasonality in shaping lake surface extent dynamics" (in review)
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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.