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175 results for “Membrane protein”

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geo24/100

The major patterns of changes in gene expression in mouse B cells in response to the latent membrane protein 1 (LMP1) of Epstein-Barr virus (EBV) in B cells gene expression

GEO Series GSE93966. Mus musculus. 6 samples. Type: Expression profiling by array.

openGEO-OpenAug 2018View details →
geo24/100

Comparative transcriptional analysis of bacillus subtilis cells overproducing either secreted proteins, lipoproteins or membrane proteins

GEO Series GSE34505. Bacillus subtilis. 29 samples. Type: Expression profiling by array.

openGEO-OpenMay 2012View details →
geo24/100

ATAD3A has a scaffolding role regulating mitochondria inner membrane structure and protein assembly

GEO Series GSE186409. Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenDec 2021View details →
geo24/100

The Membrane Stress Response Buffers Lethal Effects of Lipid Disequilibrium by Reprogramming the Protein Homeostasis Network

GEO Series GSE39419. Saccharomyces cerevisiae. 16 samples. Type: Expression profiling by array.

openGEO-OpenSep 2012View details →
geo24/100

The ER membrane protein complex interacts cotranslationally to enable biogenesis of multipass membrane proteins

GEO Series GSE112891. Homo sapiens; Saccharomyces cerevisiae. 13 samples. Type: Other.

openGEO-OpenMay 2018View details →
geo24/100

Beyond the plasma membrane disruption: Novel antifungal mechanism of Neosartorya (Aspergillus) fischeri antifungal protein 2 in Candida albicans

GEO Series GSE290357. Candida albicans. 12 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenMar 2025View details →
geo24/100

Repression of DERL3 via DNA methylation by Epstein-Barr virus latent membrane protein 1 in nasopharyngeal carcinoma [RNA-seq]

GEO Series GSE198335. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenFeb 2023View details →
geo24/100

The Effect of Milk Fat Globule Membrane-Containing Protein Powder on C. elegans Gene Expression

GEO Series GSE270138. Caenorhabditis elegans. 6 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2024View details →
geo24/100

The EBV latent membrane protein 1 (LMP1) induces cellular microRNA-146a, a modulator of lymphocyte signaling pathways

GEO Series GSE10107. Homo sapiens. 9 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.

openGEO-OpenJan 2008View details →
geo24/100

Cardiolipin is required for membrane docking of mitochondrial ribosomes and protein synthesis

GEO Series GSE148178. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJul 2020View details →
geo24/100

An inner membrane complex protein IMC1g in Plasmodium berghei plays an essential role in asexual erythrocytic proliferation and transmission

GEO Series GSE269994. Plasmodium berghei. 4 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2024View details →
geo24/100

Genetic analysis of the role of the conserved inner membrane protein CvpA in EHEC resistance to deoxycholate

GEO Series GSE162346. Escherichia coli O157:H7 str. EDL933. 6 samples. Type: Other.

openGEO-OpenDec 2020View details →
zenodo24/100

Small membranes crowded with proteins at different temperatures

<p>Simulation data for crowded coarse-grained (Martini) membranes with 4 proteins per system. Nomenclature follows that in the paper (CITATION TO BE ADDED), where also all simulation details are found.&nbsp;Simulations are performed at 4 temperatures (300, 315, 330, and 345 K), and there are a total of 400 lipids in the systems. The topology and index files are common for all simulations. The simulation parameters follow DOI:10.5281/zenodo.846428, and the required topologies can also be obtained from that upload. Larger simulations of the same system are uploaded to DOI:10.5281/zenodo.3604289 and DOI:10.5281/zenodo.3604293</p> <p>.</p>

opencc-by-4.0Jan 2020View details →
zenodo24/100

Coarse-grained simulations of protein partitioning in membranes with varying levels of SDPE

<p>The free energies of transfer between liquid ordered (Lo) and liquid disordered (Ld) domains was calculated for three proteins (Adenosine A2 receptor, A2AR; dopamine D2 receptor, D2R; and glucose transporter (GLUT)) using coarse-grained molecular dynamics simulations together with free energy perturbation. Each of these proteins was embedded in a Lo membrane consisting of DSPC, cholesterol, and varying levels (0&ndash;16 mol%) of SDPE. First, the lipids were allowed to reorganize during a 10 microsecond simulations. Then, for each protein and for each SDPE concentration, the DSPC lipids were mutated into DOPC ones and the free energy of this change was calculated. This process was repeated in the absence of the proteins for each SDPE concentration. By substracting the corresponding values for the protein-containing and protein-free cases, the free energy of transfer between Lo and Ld domains was calculated for each of the proteins as a function of SDPE concentration. All simulations were performed using the Martini force field [1] and the GROMACS simulation package [2]. For more details of the setup and the simulations, please see the related paper at DOI: 10.1371/journal.pcbi.1007033.</p> <p>The original equilibration simulations (10 microseconds in the presence of the protein and SDPE and shorter in the absence of either SDPE or the protein). The run input files for these simulations are provided as X_PUFAY_EQ.tpr and the trajectories as X_PUFAY_EQ.xtc, where X stands for the protein (or says &#39;NOPROT&#39; for the case without protein) and Y for the SDPE concentration.</p> <p>The run input files for the free energy of transfer simulations are provided as the tar files; one tar for each protein and one for the protein-free case. Each of these tars contains a folder for each used SDPE concentration, including the more realistic membrane compositions (with a suffix &#39;REAL&#39;). For each SDPE concentration, the run input files (tpr) and the simulation input parameter files (mdp) for each window in the free energy perturbation are provided. Here, the windows are numbered from 0 to 26, where 0 corresponds to DSPC and 26 to DOPC. Also, for each SDPE concentration, common topology (top), index (ndx) and start configuration (gro) are provided. The molecule definitions (itp) are provided in the TOP.tar archive.</p> <p>[1] <strong>DOI: </strong>10.1021/jp071097f ; <strong>DOI: </strong>10.1021/ct700324x ; <strong>DOI: </strong>10.1021/ct300646g</p> <p>[2] <strong>DOI:&nbsp;</strong>10.1016/j.softx.2015.06.001</p>

opencc-by-4.0Apr 2019View details →
zenodo24/100

Confocal microscopy data associated with "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity"

<p><strong>Confocal microscopy data as described in "The conserved aphid saliva chemosensory protein effector Mp10 targets plant AMSH deubiquitinases at cellular membranes to suppress pattern-triggered immunity".</strong></p> <p>&nbsp;</p> <p>Data relate to Figure 2 (&ldquo;Mp10 interacts with AMSH deubiquitinases in yeast and plants&rdquo;) involving FLIM-FRET imaging data to determine the interaction between eGFP-tagged <em>Myzus persicae </em>Mp10 and mCherry-tagged <em>Nicotiana benthamiana </em>AMSH proteins in plant cells; and Figure 6 (&ldquo;Mp10 affects the abundance and localisation of cell-surface receptor-like kinases) involving confocal microscopy showing the effect of Mp10-expression on the localisation of the GFP-tagged FLS2 receptor-kinase protein, and it&rsquo;s colocalization with RFP-tagged markers of the plasma membrane and the tonoplast in plant cells.</p> <p>Constructs encoding fluorescent protein fusions were transformed into&nbsp;<em>Agrobacterium tumefaciens </em>GV3101, and mixed Agrobacterium cultures were infiltrated into mature leaves of <em>N. benthamiana </em>plants to co-express the desired combinations of proteins. All image data was gathered from lower epidermal leaf cells of infiltrated leaves 2-3 days post infiltration.</p> <p>&nbsp;</p> <p><strong>FLIM-FRET assays.</strong></p> <p>eGFP-tagged Mp10, or eGFP-alone, was co-expressed with mCherry-tagged AMSH proteins, or mCherry fused to aquaeorin in <em>N. benthamiana</em> via agroinfiltration as described above. Lower epidermal cells of leaf sections were imaged 2-3 days after infiltration using a Leica Stellaris 8. Images were captured detecting fluorescence from eGFP (WLL laser, ex.488 nm, em 509-534 nm.) mCherry (lWLL aser, ex. 587 nm em 603-625 nm.) and chlorophyll (WLL laser, ex 587 nm. em 687-712 nm.). Regions of cells showing expression of both eGFP- and mCherry- tagged proteins but lacking chlorophyll were selected for FLIM analysis to avoid bleed through of chlorophyll fluorescence into the eGFP chanel. Fluorescence lifetime data of EGFP were collected from these regions in FLIM mode (WLL laser ex. 488nm, em 525-530 nm.), data were collected at 128x128 resolution until 1000 photons per pixel were collected for the most intense regions of the image. Instrument response function was captured using erythrosine on each day of data collection. FLIM data were analysed using Leica LASX FLIM FCS software. Fluorescence lifetime decay curves of free eGFP control samples were modelled as a 2-component exponential function, and all samples from each experimental set were modelled against the fluorescence lifetime from the corresponding control samples to derive values for fluorescent lifetime and %FRET efficiency for each image collected. %FRET efficiency was mapped to the images and phasor plots were generated for regions with the highest and lowest FRET efficiency, showing that the FRET signal was associated with a clockwise shift on the phasor plot consistent with <em>bona-fide </em>FRET. Full experimental metadata for each image set are included within the .lif files.</p> <p>&nbsp;</p> <p><strong>FLS2-GFP localisation experiments.</strong></p> <p>Confocal microscopy analysis was performed on a Leica TCS SP8X confocal DM6 microscope with a 63x water-immersion objective, using Leica Application Suite X (LAS X) software (3.5.7.23225). eGFP and chlorophyll signals were excited by a 488&thinsp;nm Argon laser with emission, respectively, at 495&ndash;545&thinsp;nm and 690-710 nm. RFP signal was excited by a 590&thinsp;nm white light laser (WLL) with emission at 605&ndash;650&thinsp;nm. Full experimental metadata for each image set are included within the .lif files.</p> <p>&nbsp;</p> <p>Leica Image Files (.lif) that contain multiple images including metadata associated with image acquisition and processing.</p> <p>&nbsp;</p> <p>FLIM030823.lif</p> <p>FLIM130724.lif</p> <p>FLIM140623.lif</p> <p>FLIM160623.lif</p> <p>FLIM240523.lif</p> <p>FLIM250523.lif</p> <p>Files include FLIM-FRET data as shown in Figure 2 parts D-L.</p> <p>FLIM-data-files.xlsx includes a description of the individual image filenames, and the combinations of fluorophore imaged in each.</p> <p>&nbsp;</p> <p>Fig6cSlFLS2-gfp_Mp10-RFP.lif</p> <p>Fig6c-SlFLS2-GFP_EV-RFP.lif</p> <p>Correspond to Figure 6 C showing co-expression of RFP-tagged Mp10 (or free RFP control) co-expressed with GFP-tagged FLS2</p> <p>&nbsp;</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-1x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-3-3-3x.lif</p> <p>20230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP-4-2-3x.lif</p> <p>0230828_SlFLS2-GFP_Flag-Mp10_Flag-alone_Remorin-RFP4-2-1x.lif</p> <p>Correspond to Figure 6 D showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged plasma membrane marker Remorin</p> <p>&nbsp;</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-14-5-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1-1x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1a-3x.lif</p> <p>20230911_SlFLS2-GFP_Flag-Mp10_Flag-alone_StSUC4-RFP-16-1b-1x.lif</p> <p>Correspond to Figure 6 E showing co-expression of FLAG-tagged Mp10 (or free FLAG control) co-expressed with GFP-tagged FLS2 together with RFP-tagged tonoplast marker SUC4.</p> <p>&nbsp;</p> <p>We are grateful to the John Innes Centre (JIC) Bioimaging Platform for training and technical support</p> <p>This work was funded by UK Research and Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC) grants to SAH (BB/V008544/1 and BB/N009169/1), Additional Support was provided by the BBSRC Institute Strategy Programmes (BBS/E/J/000PR9797 and BBS/E/JI/230001B) awarded to the John Innes Centre (JIC). The JIC is grant-aided by the John Innes Foundation.</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2024View details →
dryad24/100

Data from: The AAA protein Msp1 mediates clearance of excess tail-anchored proteins from the peroxisomal membrane

Msp1 is a conserved AAA ATPase in budding yeast localized to mitochondria where it prevents accumulation of mistargeted tail-anchored (TA) proteins, including the peroxisomal TA protein Pex15. Msp1 also resides on peroxisomes but it remains unknown how native TA proteins on mitochondria and peroxisomes evade Msp1 surveillance. We used live-cell quantitative cell microscopy tools and drug-inducible gene expression to dissect Msp1 function. We found that a small fraction of peroxisomal Pex15, exaggerated by overexpression, is turned over by Msp1. Kinetic measurements guided by theoretical modeling revealed that Pex15 molecules at mitochondria display age-independent Msp1 sensitivity. By contrast, Pex15 molecules at peroxisomes are rapidly converted from an initial Msp1-sensitive to an Msp1-resistant state. Lastly, we show that Pex15 interacts with the peroxisomal membrane protein Pex3, which shields Pex15 from Msp1-dependent turnover. In sum, our work argues that Msp1 selects its substrates on the basis of their solitary membrane existence.

opencc-zeroDec 2016View details →
zenodo24/100

Data belonging to "DNA-PAINT single-particle tracking (DNA-PAINT-SPT) enables extended single-molecule studies of membrane protein interactions"

<p>Source data for&nbsp;&quot;DNA-PAINT single-particle tracking (DNA-PAINT-SPT) enables extended single-molecule studies of membrane protein interactions&quot;</p>

opencc-by-4.0Nov 2022View details →
zenodo24/100

The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini

<p>The deposited data sets contain data for the supplementary figures of the manuscript &quot;The insertase YidC chaperones the polytopic membrane protein MelB inserting and folding simultaneously from both termini&quot; by Blaimschein et al. published in Structure (2023).</p>

opencc-by-4.0Sep 2023View details →
ClinicalTrials.gov24/100

A Safety and Immunogenicity Phase I Study of CryJ2-DNA-Lysosomal Associated Membrane Protein (CryJ2 -DNA-LAMP) Plasmid

ClinicalTrials.gov study NCT01707069. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

A Safety and Immunogenicity Phase IB Study of CryJ2-DNA-Lysosomal Associated Membrane Protein (CryJ2 -DNA-LAMP) Plasmid Assessing the Long Term Safety of Previously Treated Subjects

ClinicalTrials.gov study NCT01966224. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →

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dandi-nwb
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Last verified 2026-04-30Open record

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.

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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

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Last verified 2026-04-29Open record