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523 results for “cell migration”
Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics
<p>Full-resolution representative data sufficient to repeat analyses for the work of: AE Wolf, MA Heinrich, IB Breinyn, TJ Zajdel, and DJ Cohen in "Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics".</p> <p>Please see the _README2.0.0.txt file for explanations on contents in this Zenodo repository.</p> <p>Relevant codes used in our analyses are available on Github (github.com/CohenLabPrinceton/ElectrotaxisSupracellularMemory).</p>
Logical model for Molecular Pathways Enabling Tumour Cell Invasion and Migration
<p>Understanding the etiology of metastasis is very important in clinical perspective, since it is estimated that metastasis accounts for 90% of cancer patient mortality. Metastasis results from a sequence of multiple steps including invasion and migration. The early stages of metastasis are tightly controlled in normal cells and can be drastically affected by malignant mutations; therefore, they might constitute the principal determinants of the overall metastatic rate even if the later stages take long to occur. To elucidate the role of individual mutations or their combinations affecting the metastatic development, a logical model has been constructed that recapitulates published experimental results of known gene perturbations on local invasion and migration processes, and predict the effect of not yet experimentally assessed mutations. The model has been validated using experimental data on transcriptome dynamics following TGF-β-dependent induction of Epithelial to Mesenchymal Transition in lung cancer cell lines. A method to associate gene expression profiles with different stable state solutions of the logical model has been developed for that purpose. In addition, we have systematically predicted alleviating (masking) and synergistic pairwise genetic interactions between the genes composing the model with respect to the probability of acquiring the metastatic phenotype. We focused on several unexpected synergistic genetic interactions leading to theoretically very high metastasis probability. Among them, the synergistic combination of Notch overexpression and p53 deletion shows one of the strongest effects, which is in agreement with a recent published experiment in a mouse model of gut cancer. The mathematical model can recapitulate experimental mutations in both cell line and mouse models. Furthermore, the model predicts new gene perturbations that affect the early steps of metastasis underlying potential intervention points for innovative therapeutic strategies in oncology.</p> <p> </p> <p>Included files:</p> <ul> <li>Master Model: the model includes detailed regulation of the major players involved in the crosstalks between Notch and p53 pathways</li> <li>Modular Model: the model is a reduction of the master model. To reduce the master model, we lumped together some entities that belonged to a module.</li> </ul>
Centripetal migration in Drosophila ovary IX: E-cadherin null clones pt2 & E-Cadherin germ cell RNAi pt 2
<p>Part of data supporting Figs 6, 7, S3, S6, S16 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”<br> DOI: 10.1242/dev.200492</p> <p><strong>Data file descriptions:</strong></p> <ul> <li><strong>“FRT G13 mitotic clones” 14.6 GB</strong></li> </ul> <p> Fixed sample image data for clones of cells with E-Cadherin mutant or control mitotic clones</p> <ul> <li><strong>“GC RNAi flipout timelapse data pt2” 28.92GB</strong></li> </ul> <p> Timelapse image data for clones of germ cells with E-Cadherin knockdown</p> <ul> <li><strong> “Image analysis of ring canals-fixed G13 control” 6 KB</strong></li> </ul> <p> Evaluation of fixed samples for ring canal position just prior to stage 11, nurse cell dumping, using</p> <ul> <li><strong>“Immuno Shg LOF clonal analysis” 98 KB</strong></li> </ul> <p> Preliminary evaluation of sample image with clones of cells with E-Cadherin mutant or control mitotic clones</p> <ul> <li><strong>“Live GC RNAi clonal data Prelim Eval” 25.2 MB</strong></li> </ul> <p> Preliminary evaluation of germ cell E-Cadherin knockdown samples</p> <p> </p>
Centripetal migration in Drosophila ovary X: E-Cadherin germ cell RNAi pt 1
<p>Part of data supporting Fig S16 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <p>Data description:</p> <ul> <li><strong>“GC RNAi flipout timelapse data pt1” 38 GB</strong></li> </ul> <p> Timelapse image data for clones of germ cells with E-Cadherin knockdown</p> <ul> <li><strong>“Live GC RNAi clonal data Prelim Eval” 25.2 MB</strong></li> </ul> <p> Preliminary evaluation of all germ cell E-Cadherin knockdown samples</p>
Centripetal migration in Drosophila ovary VII: E-cadherin RNAi clones in follicle cells timelapse
<p>Data supporting Figs. 5, S7, S8, S9, S10, S11, S12, S13, S14, S15 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <ul> <li><strong>“FC RNAi flipout timelapse data complete” 43.53GB</strong></li> </ul> <p> Timelapse image data for clones of follicle cells with E-Cadherin knockdown</p> <ul> <li><strong>“Live FC RNAi Clonal Data prelim evaluation” 22.1 MB</strong></li> </ul> <p> Preliminary evaluation of follicle cell E-Cadherin knockdown samples</p> <ul> <li><strong>“RNAi clone M2-M3-M5 quant” 12 KB</strong></li> </ul> <p> Quantitative data from specific milestones for clones of follicle cells with E-Cadherin knockdown</p>
ERK activity in migrating MDA-MB-231 cells (clover-ERK-KTR + sir-DNA)
<p>MDA-MB-231 or U2OS cells stably expressing clover-ERK-KTR were seeded on fibronectin-coated (1 µg /ml) Ibidi 8-well slides (Ibidi) 1 day before imaging. Four hours before imaging, the medium was supplemented with 250 nM sir-DNA (Cytoskeleton) and 25 mM HEPES (Sigma). Cells were then imaged live (37 °C, 5% CO<sub>2</sub>) using a Nikon Eclipse Ti2-E microscope (Nikon) equipped with an sCMOS Orca Flash4.0 camera (Hamamatsu) and controlled by the NIS-Elements software (Nikon, v 5.11.01). MDA-MB-231 cells were imaged using a 20× Nikon CFI Plan Apo Lambda objective (NA 0.75), either 1 frame per minute for 2 hours or 1 frame every 5 minutes for 17 hours. In these experiments, a camera binning of 2 × 2 was used. </p> <p>This dataset consists of 20 videos.</p>
Data_Figure 2_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 2 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1007_s00018-019-03227-w_CMLS_Fig2). Corresponding raw data obtained from a) Migration potential as four files in CSV format (31003A-179400_ date_examiner_17BHSD12_16_1_1-4. b) mRNA content analyzed by RT-PCR provided as ten files in CSV format (31003A-179400_date_examiner_17BHSD12_1_1-2_1-6) and proliferation investigation on xCELLigence provided as six files in CSV format (31003A-179400_date_examiner_17BHSD12_9_2_1-6). All further experiment related information and subsequent data analysis provided as four meta-data-files (31003A-179400_ date_examiner_17BHSD12_16/1/9_dataset_M_1) as TXT format.</p>
Data_Figure 6_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 6 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 6). Corresponding raw data obtained from a1/2) cellomics HTC array scan analysis provided as six files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_6_1-6), b1/2) oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) provided as 10 files in CSV format (31003A-179400_20190521_MT_17BHSD12_10_3-4_1-5); c 1/2 ), cellomics HTC array scan analysis provided as 12 files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_7-8_1-8). d) Western blot and densitometry provided as eight files in CSV format (31003A-179400_Date_examiner_17BHSD12_2_3-4_1-5). All further experiment related information protocols and subsequent data analysis provided as meta-data-files (31003A-179400_date_examiner_17BHSD12_8/10/2_dataset_M_1) as TXT format and (31003A-179400_date_examiner_17BHSD12_2_dataset_M_2-3) as PNG format.</p>
Data_Figure 7_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 7 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 7). Corresponding raw data obtained from a1/2) Western blot and densitometry provided as eight files in CSV format (31003A-179400_date_examiner_17BHSD12_2_5-6_1-6); b) mRNA content analyzed by RT-PCR provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_1_6_1-4); c 1/2) cellomics HTC array scan analysis provided as 11 files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_9-10_1-6); d1/2); Western blot and densitometry provided as eight files in CSV format (31003A-179400_date_examiner_17BHSD12_2_7-8_1-6). All further experiment related information protocols and subsequent data analysis provided as meta-data-files (31003A-179400_date_examiner_17BHSD12_2/1/8_dataset_M_1) as TXT format and (31003A-179400_date_examiner_17BHSD12_2_dataset_M_2-3) as PNG format.</p>
Data_Figure 5_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 5 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 5). Corresponding raw data obtained from oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) provided as 10 files in CSV format (31003A-179400_20190521_MT_17BHSD12_10_1-2_1-5). All further experiment related information and subsequent data analysis provided as two meta-data-file: (31003A-179400_20190521_MT_17BHSD12_10_1-2_1) as TXT format.</p>
Data_Figure 4_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 4 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 4). Corresponding raw data obtained from: a1/2) Migration potential as five files in CSV format (31003A-179400_date_examiner_17BHSD12_16_3_1-5); b 1/2) Migration potential as four files in CSV format (31003A-179400_date_examiner_17BHSD12_16_4_1-4); c1/2/3) mRNA content analyzed by RT-PCR provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_1_4_1-4); cellomics HTC array scan analysis provided as three files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_3-4_1-4); d) Migration potential as five files in CSV format (31003A-179400_ date_examiner_17BHSD12_16_5_1-5); e) mRNA content analyzed by RT-PCR provided as six files in CSV format (31003A-179400_date_examiner_17BHSD12_1_5_1-6); f) Migration potential as four files in CSV format (31003A-179400_date_examiner_17BHSD12_16_6_1-4), cellomics HTC array scan analysis provided as three files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_5_1-5); g) ELISA measurement provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_20_1_1-4). All further experiment related information protocols and subsequent data analysis provided as 10 meta-data-files (31003A-179400_date_examiner_17BHSD12_8/16/1/20_dataset_M_1) as TXT format.</p>
Data_supplemental figure 2_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of supplemental figure 2 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF format (10.1194_jlr.M092908_Fig. S2). Corresponding raw data obtained from cellomics HTC array scan analysis provided as seven files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_11-12_1-4) All further experiment related information protocols as meta-data-files (31003A-179400_date_examiner_17BHSD12_8_11-12_M_1) as TXT format.</p>
Data for: Dysregulation of mTOR signaling mediates common neurite and migration defects in both idiopathic and 16p11.2 deletion autism neural precursor cells
<p>Autism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly, despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD subtypes and mTOR modulation rescued ASD phenotypes and reproduced autism NPC-associated phenotypes in control NPCs. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation.</p>
NEUBIAS TS7 - data used in the workflow deconstruction session on quantifying monolayer cell migration
<p>Training session details (including slides): https://github.com/miura/NEUBIAS_AnalystSchool2018/tree/master/Assaf</p> <p>Matlab source code: https://github.com/assafzar/MonolayerKymographs</p>
Megakaryocyte volume modulates bone marrow niche properties and cell migration dynamics
<p>Supplementary videos showing raw time and z-stacks as well a final, processed result for Neutrophil tracking in naive and platelet depleted mouse.</p> <p>Matlab scripts to run simulation of megakaryocytes, neutrophils and hematopoetic stem cell in a vessel environment.</p> <p>Ilastik training data set used in segmentation of bone and bone marrow.</p> <p> </p>
Simulation data for "Phylogenetic analysis of migration, differentiation, and class switching in B cells"
<p>Simulation data for https://doi.org/10.1101/2020.05.30.124446.</p> <p>Scripts available at: https://bitbucket.org/kleinstein/projects/src/master/Hoehn2020/</p> <p>data_twostate.tsv: AIRR TSV file of data used for simulations</p> <p>trees_twostate.RData: Tree topologies used to simulate migration</p> <p>simulations.tar.gz: Files used in simulation analyses. File names show:</p> <p><rate (r)>_<rate A to B (r_ab)>_<pi_A>_<repetition></p> <p>laddersims.tar.gz: Files used in ladder tree simulation analyses. File names show:</p> <p><rate (r)>_<rate A to B (r_ab)>_<pi_A>_<number of tips>_<number of trees>_<repetition></p> <p> </p>
Cancer cell migration followed with TrackMate
<p>Cancer cells migration followed with TrackMate.</p> <p>For more details see https://imagej.net/plugins/trackmate/trackmate-stardist</p> <p> </p>
Cell migration with ERK signalling
<p>Movie following cells expressing ERK and a nuclei staining, tracked with TrackMate and later analyzed with MATLAB.</p> <p>See https://imagej.net/plugins/trackmate/trackmate-stardist for more details.</p> <p> </p>
Tracking cell migration with the TrackMate threshold detector
<p>Migrating cells tracked with TrackMate, using the threshold detector.</p> <p>For more information see https://imagej.net/plugins/trackmate/trackmate-thresholding-detector</p> <p> </p>
TIRF imaging data of neutrophils migrating underneath endothelial cells
<p>This data is used in the publication "Endothelial Focal Adhesions Are Functional Obstacles for Leukocytes During Basolateral Crawling": https://www.frontiersin.org/articles/10.3389/fimmu.2021.667213/full</p> <p> </p> <p><strong>TIRF Microscopy</strong></p> <p>Lentiviral transduction was used to generate an endothelial cell line expressing mNeonGreen-Paxillin (derived from addgene plasmid # 129604). Cells were imaged with a Nikon Ti-E microscope equipped with a motorized TIRF Illuminator unit, a 60x TIRF objective (60x Plan Apo, Oil DIC N2, NA =1.49, WD = 120 um) and Perfect Focus System. Images were acquired with an Andor iXon 897 EMCCD camera and the Nikon NIS elements software. mNeonGreen was imaged using the 488 nm laser line and calcein red-orange was imaged using the 561 nm laser line. A quad split dichroic mirror (405 nm, 488 nm, 561 nm, 640 nm) was used in combination with dual band pass emission filter (515 to 545 nm, 600 to 650 nm). To achieve a larger field of view a 3 x 3 tile scans was acquired with 15% overlap stitching on the GFP channel. Time lapse images were taken every 10 s.</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.