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65 results for “protein-protein interactions”
A human IgSF cell-surface interactome reveals a complex network of protein-protein interactions
<p>Cell-surface protein-protein interactions (PPIs) mediate cell-cell communication, recognition and responses. We executed an interactome screen of 564 human cell-surface and secreted proteins, most of which are immunoglobulin superfamily (IgSF) proteins, using a high-throughput, automated ELISA-based screening platform employing a pooled-protein strategy to test all 318,096 PPI combinations. Screen results, augmented by phylogenetic homology analysis, revealed ~380 previously unreported PPIs. We validated a subset using surface plasmon resonance and cell binding assays. Observed PPIs reveal a large and complex network of interactions both within and across biological systems. We identified new PPIs for receptors with well-characterized ligands, and binding partners for 'orphan' receptors. New PPIs include proteins expressed on multiple cell types, and involved in diverse processes including immune and nervous system development and function, differentiation/proliferation, metabolism, vascularization, and reproduction. These PPIs provide a resource for further biological investigation into their functional relevance, and may offer new therapeutic drug targets.</p>
Supplemental data: Interfering Peptides Targeting Protein-Protein Interactions in the Ethylene Plant Hormone Signaling Pathway as Tools to Delay Plant Senescence
<p>This dataset supplements the chapter "Interfering Peptides Targeting Protein-Protein Interactions in the Ethylene Plant Hormone Signaling Pathway as Tools to Delay Plant Senescence" published in Methods in Molecular Biology. It includes sample files that illustrate data collection and processing outlined in the article.</p>
STRING protein-protein interaction network (v11.5)
<p>STRING protein-protein interaction network was downloaded from the STRING website (https://string-db.org/cgi/download?sessionId=bIAz6gR8tk72).</p> <p>Version: 11.5</p>
Predicting the pro-longevity or anti-longevity effect of model organism genes with enhanced Gaussian noise augmentation-based contrastive learning on protein-protein interaction networks
<p>The datasets used to evaluate Enhanced Gaussian noise augmentation-based contrastive learning (EGsCL) against predicting the pro-longevity or anti-longevity effect of model organism gene. This repo also includes the pretrained encoders that obtained the best predictive performance for each organism (see Table 2).</p>
Predicted protein-protein interactions of the human tyrosine kinase Lck by AF2Complex
<p>Structural models and Supplementary data described in the publication:</p> <p>Predicting protein interactions of the kinase Lck critical to T cell modulation</p> <p>Structure (Cell Press), 2024</p> <p>Reference Authors: Mu Gao and Jeffrey Skolnick</p> <p><br>screening_results -- Virtual PPI screening results of the protein kinase Lck (SH3-SH2 domains as the bait).<br>predicted structural models.zip -- Compressed structural models described in the publication.<br>af2c_input_features -- Input features used to predict protein complex models with AF2Complex. </p>
Identification of protein-protein interaction bridges for multiple sclerosis
<p>Supplementary data for thesis "Identification of protein-protein interaction bridges for multiple sclerosis"</p>
CTCF protein-protein interactions
<p>A collection of all the interactions between CTCF and other proteins. Data from the literature, as well as the STRING database and the Integrated Interactions Database, were analyzed and merged.</p>
Fig. 2 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 2. Analysis of the protein–protein interaction using co-immunoprecipitation. Cytosolic (a) and microsomal fractions (b) were incubated with an anti-PtIGS antibody bound to the AminoLink Plus Coupling Resin. After elution with an acidic buffer, proteins were separated by SDS-PAGE using a 12.5% acrylamide gel for (a) and 10% for (b). After the samples corresponding to (a) 0.205 and (b) 0.057 g wet weight leaves were analyzed, total proteins were visualized with silver staining. As the control, PtIGS in the samples corresponding to 0.041 and 0.057 g wet weight leaves was also detected with western blotting using the anti-PtIGS antibody. C1–C6 and M1–M10 show the regions that were cut from gels and subjected to MS/MS analysis. The symbols "+" and "-" represent the use of AminoLink Plus Coupling Resins bound with anti-PtIGS antibody and without antibody, respectively.
Fig. 1 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 1. Chemical crosslinking assay in vitro and in vivo. Cytosolic (a) and microsomal (b) fractions and the protoplasts (c) were treated with chemical crosslinkers (BS3 and DSS, respectively). Treated samples were then subjected to SDS-PAGE using a 10% acrylamide gel for (a) and (b) and 7.5% for (c). Proteins that reacted against the anti-PtIGS antibody were detected by western blotting. "I" indicates PtIGS monomer. "II" denotes molecules larger than the monomer.
Fig. 5 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 5. The validation of the expression amount of candidates, which might relate to the indican biosynthesis pathway, by qRT-PCR. a, Indican synthase (PtIGS) and the degradation enzyme (PtBGL); b, indole synthesis-related proteins; c, proteins that might relate to the indole oxidation; d, UDP-glucose biosynthesis enzymes and transport proteins that might relate to the indican biosynthesis pathway. Each error bar shows the standard error. The detailed values of (a) and (b) are indicated in Supplementary Table 4S. Those values of (c) and (d) are showed in Tables 4 and 5, respectively.
A human IgSF cell-surface interactome reveals a complex network of protein-protein interactions
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Dataset accompanying "SECAT: Quantifying differential protein-protein interaction states by network-centric analysis"
<p>This repository contains input data, processing parameters and results associated with manuscript "SECAT: Quantifying differential protein-protein interaction states by network-centric analysis".</p> <p>Each archive contains a README.txt file that describes the contents.</p> <p>SECAT_scripts_data.tar.xz is an archive containing the scripts and data to generate the manuscript figures.</p>
SpatPPI: a geometric deep learning model for predicting protein-protein interactions involving intrinsically disordered regions
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Fig. 4 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 4. Scheme of the hypothesized indican biosynthetic pathway.
Data from: Determining the minimum number of protein-protein interactions required to support known protein complexes
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A Protein-Protein Interaction Underlies the Molecular Basis for Substrate Recognition by an Adenosine to Inosine RNA Editing Enzyme
GEO Series GSE112367. Caenorhabditis elegans. 12 samples. Type: Expression profiling by high throughput sequencing; Other.
Next-generation interaction screening to discover luciferase (construct #2) related protein-protein interactions regulating barley powdery mildew disease immunity and susceptibility
GEO Series GSE164762. Hordeum vulgare; Blumeria hordei. 4 samples. Type: Other.
In situ detection and amplification of protein-protein interactions can increase recombinant protein production
GEO Series GSE295486. Cricetulus griseus. 33 samples. Type: Expression profiling by high throughput sequencing.
SOX2 O-GlcNAcylation alters its protein-protein interactions and genomic occupancy to modulate gene expression in pluripotent cells
GEO Series GSE69594. Mus musculus. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by array.
Structure-function Analysis of Rice Immune Receptor BPH14 Reveals Planthopper-resistance Mediated through Protein-protein Interaction with WRKY46/72
GEO Series GSE93607. Oryza sativa. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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.