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7,404 results for “receptors”
Supplemental Information - Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling
<p>This folder contains</p> <p>1) maps of plasmids</p> <p>2) files of phylogenetic analysis </p> <p>3) Replication information</p> <p>4) Image cropping information</p> <p>5) Gene IDs and protein sequences</p> <p>that are part of the manuscript "Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling"</p>
Dataset Activation of Lactate Receptor HCAR1 Down-modulates Neuronal Activity in Rodent and Human Brain Tissue
<p>This dataset is related to the study: </p> <p>Briquet M, Rocher AB, Alessandri M, Rosenberg N, de Castro Abrantes H, Wellbourne-Wood J, Schmuziger C, Ginet V, Puyal J, Pralong E, Daniel RT, Offermanns S, Chatton JY. Activation of lactate receptor HCAR1 down-modulates neuronal activity in rodent and human brain tissue. J Cereb Blood Flow Metab. 2022 Mar 3:271678X221080324. doi: 10.1177/0271678X221080324. Epub ahead of print. PMID: 35240875.</p>
Minute-timescale free-energy calculations reveal a pseudo-active state in the adenosine A2A receptor activation mechanism
<p>Dataset of the paper "Minute-timescale free-energy calculations reveal a pseudo-active state in the adenosine A2A receptor activation mechanism" accepted for publication on ACS Chem journal.</p>
Data_text section_ 11βHSD1_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data from kinetic characterization (Km and vmaxapp) described in text section 3.1 of 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains values from kinetic characterization (Km and vmaxapp) described in text section (Kinetic values_11βHSD1.PNG) corresponding to raw data obtained from LC-MS/MS analysis provided as three files in CSV format (31003A-179400_DATE_KB_27Oxysterol_4_6_1-3). All further experiment related information and subsequent data analysis provided as two meta-data-files (31003A-179400_DATE_KB_27Oxysterol_4_6_M_1-2) as TXT format and PDF format.</p>
SIRAH-CoV2 initiative: S1 Receptor Binding Domain in complex with human antibody CR3022 (PDBid: 6W41)
<p>This dataset contains the trajectory of a 12 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV-2 receptor binding domain in complex with a human antibody CR3022 (PDB id: 6W41). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00006">Machado et al. JCTC 2019</a>, adding 150 mM NaCl according to <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.9b00953">Machado & Pantano JCTC 2020</a>. Glycans have been removed from the structures.</p> <p>The file 6W41_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using <a href="https://academic.oup.com/bioinformatics/article/32/10/1568/1743152">SirahTools</a> can be found at www.sirahff.com.</p> <p>Additionally, the file 6W41_SIRAHcg_12us_prot.tar contains only the protein coordinates, while 6W41_SIRAHcg_12us_prot_skip10ns.tar contains one frame every 10ns.</p> <p>To take a quick look at the trajectory:</p> <p>1- Untar the file 6W41_SIRAHcg_12us_prot_skip10ns.tar</p> <p>2- Open the trajectory on VMD using the command line:</p> <p>vmd 6w41_SIRAHcg_prot.prmtop 6w41_SIRAHcg_prot.ncrst 6w41_SIRAHcg_prot_12us_skip10ns.nc -e sirah_vmdtk.tcl</p> <p>Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. </p> <p>This dataset is part of the SIRAH-CoV2 initiative.</p> <p>For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).</p>
All-atom 500-nano seconds Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 nano-seconds (ns) production run was performed for the simulation.</p>
Dataset related to article "Lipoprotein receptor loss in forebrain radial glia results in neurological deficits and severe seizures"
<p>This dataset is related to the article entitled: Lipoprotein receptor loss in forebrain radial glia results in neurological deficits and severe seizures. This article is published in the Journal GLIA.</p> <p>Bres EE et al.<br> Lipoprotein receptor loss in forebrain radial glia results in<br> neurological deficits and severe seizures. Glia. 2020;1–33.</p>
Activin A receptor, type I (ACVR1); A Target Enabling Package
<p>Germline gain of function mutations in the gene <em>ACVR1</em> encoding the BMP receptor ALK2 lead to the rare congenital syndrome FOP in which aberrant signalling through the BMP signalling pathway leads to progressive heterotopic ossification in muscle and connective tissue. Identical somatic mutations have been identified in 25% of cases of the childhood brain tumour DIPG. Both conditions affect young children and have no approved therapies. Highly selective ALK2 kinase inhibitors are therefore desirable to achieve chronic treatment of children with safety. We prepared recombinant ALK2 kinase domain and solved structures of ALK2 in complex with new ATP-competitive inhibitors. We identified a novel allosteric pocket in the ALK2 kinase domain and took advantage of these structures to perform crystallographic fragment screening (XChem) using both a standard poised fragment library and a new mini-fragment library. This work identified a poised fragment for development as an allosteric ALK2 inhibitor, as well as mini-fragments exploiting new areas of the ATP and substrate binding pockets. <em>In vitro</em> and cellular assays are available to advance these compounds for drug development in collaboration with patient groups.</p>
Discovery of South African plant-based biomarkers as potential flagships for SARS- CoV-2 receptor
<h1><span>Table S1: </span><span>Distinguished metabolites in the extracts of <em><span>Artemisia annua </span></em><span>and <em>Artemisia afra </em></span>using UPLC-MS/MS set in positive ionization mode.</span></h1> <h1><span>Table S2: Identified and docked compound-based biomarkers from <em><span>Artemisia annua </span></em><span>and <em>Artemisia afra </em></span>(ESI+ scan).</span></h1>
Dataset for the Sphingosine 1-phosphate receptor 1 (S1PR1) antibody screening study
<p><strong><span>This antibody characterization dataset is related to the F1000 research article openly available at F1000Research.</span></strong></p> <p><em>This project contains the following underlying data included in a study aimed at characterizing nine commercial antibodies against Sphingosine 1-phosphate receptor 1 (S1PR1) protein, encoded by S1PR1 gene. The study is available on Zenodo (<a href="https://doi.org/10.5281/zenodo.10819189">https://doi.org/10.5281/zenodo.10819189</a>).</em></p> <p><em>The Dataset is in the format of a zip file. Once downloaded, please expand the zip file to access the folders containing the underlying data for Western blot (Wb), immunoprecipitation (IP) and immunofluorescence (IF).</em></p>
Data supporting: "Calcium-driven In Silico Inactivation of a Human Olfactory Receptor"
<p>In this repository we deposited trajectories and input files for the paper "Calcium-driven In Silico Inactivation of a Human Olfactory Receptor".</p> <p>The data is organised as follow:</p> <p> </p> <p>DATA:</p> <p>CA / NA / NO_IONS / NEUTRAL</p> <ul> <li>centroid.pdb # centroid calculated with GMX</li> <li>step5_input.gro # input file from CHARMM GUI</li> <li>topol.top # topol file from CHARMM GUI</li> <li>MDPs # folder containing mdp files from CHARMM GUI</li> <li>toppar # folder containing topology files from CHARMM GUI </li> </ul> <p> </p> <p>TRJs:</p> <p>CA / NA / NO_IONS / NEUTRAL</p> <ul> <li>ref.pdb # reference pdb file</li> <li>trj1.xtc # trajectory from replica 1</li> <li>trj2.xtc # trajectory from replica 2</li> <li>trj3.xtc # trajectory from replica 3</li> <li>trj4.xtc # trajectory from replica 4</li> <li>trj5.xtc # trajectory from replica 5</li> <li>trj6.xtc # trajectory from replica 6 (NEUTRAL only)</li> </ul>
Dataset for the Prolow-density lipoprotein receptor-related protein1 (LRP-1) antibody screening study
<p>This project contains the following underlying data included in a study aimed at characterizing ten commercial antibodies against Prolow-density lipoprotein receptor-related protein 1 (LRP-1) protein, encoded by <em>LRP1 </em>gene. The study is available on Zenodo (DOI:10.5281/zenodo.7971951).</p>
G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations
<p>Data and Python scripts used for generation and analysis of RAMD dissociation trajectories for several GPCR complexes (including example showing generation of the Protein-Ligand Interaction Fingerprints, IFP, for several representative RAMD trajectories),</p> <p>reported in the manuscript</p> <p>"G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tRAMD Simulations" "G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations"</p> <p>by Daria B. Kokh, Rebecca C. Wade</p> <p>submitted to the Journal of Chemical Theory and Computation</p> <p> </p> <p>1. <strong>README.txt </strong>- instruction for script usage</p> <p>2. <strong>PDBs.zip</strong> - PDB structures of complexes in water box used in the analysis, ligand PDB and mol2 structures</p> <p>3. <strong>tauRAMD_v2.py </strong>- Python sctipt for estimation relative residence times from Gromacs-RAMD output </p> <p>4. <strong>IFP_preprocess_Gromacs.py</strong> and <strong>IFP_SL-B2AR-WB-EX.py - </strong>Python scripts for preprocessing of RAMD trajectories and generation of IFPs</p> <p>5. <strong>Scripts.zip</strong> - additional python functions </p> <p>6. <strong>IXO-CHL.zip, IXO-ALO-CHL.zip, ACh-CHL.zip, b2AR.zip</strong> - Protein-Ligand Interaction Fingerprints (PL IFPs) generated from RAMD trajectories for <em>mAChR M2 with iperoxo</em>, <em>mAChR M2 </em><em> with iperoxo and PAM, mAChR M2 with ACh, and </em>β<em>2AR with alprenolol </em><em>.</em> </p> <p>7. <strong>Topology.zip</strong> - Gromacs topology, index.ndx, and coordinate gro files for all four systems</p> <p>8. <strong>Example_b2AR-alprenolol.zip </strong>- a set of data for a test example showing how IFP can be generated from RAMD trajectories (including several representative trajectories)</p> <p>9. <strong>Example_b2AR-alprenolol.tar </strong>- almost the same set of data as above (compressed in Windows) but for Linux users. The only difference between tar and zip archive: a short equilibration trajectory that is missing in the zip set but is included in the tar archive.</p> <p>10.<strong> Gromacs-IFP-GPCR.ipynb</strong> - Jupyter Notebook for analysis of trajectories using generated IFP data</p> <p>11. <strong>Auxi-Plots-GPCR.ipynb - </strong>Jupyter Notebook for generation additional plots from the paper</p> <p>12. <strong>Waters.zip</strong> - number of water molecules in the binding pocket in dissociation trajectories of the <em> </em>β<em>2AR - alprenolol system</em></p> <p>13. <strong>GPCR.yml</strong> - JN environment file</p> <p> </p>
Control T-cell receptor (TCR) alpha and beta chain nucleotide and amino acid sequences from human and mouse
<p>A dataset of pooled T-cell receptor (TCR) sequences for TCR alpha and beta chains of human and mouse.</p> <p>Sequences are obtained from various samples of healthy individuals/mice using our conventional protocols: see for example [Britanova et al "Dynamics of individual T cell repertoires: from cord blood to centenarians" The Journal of Immunology 2016] and [Izraelson et al. "Comparative analysis of murine T‐cell receptor repertoires." Immunology 2018].</p> <p>The sequences are stored as gzipped clonotype tables in VDJtools format, see [https://vdjtools-doc.readthedocs.io/en/master/input.html#vdjtools-format].</p> <p>This control dataset can be used as a proxy for a generative VDJ rearrangement model to estimate the expected frequency distribution of TCRs and check for enrichment of rare TCR clonotypes and groups of similar TCR sequences. For the implementation of the enrichment analysis, please see CalcDegreeStats routine from VDJtools software, see [https://vdjtools-doc.readthedocs.io/en/master/annotate.html#calcdegreestats].</p> <p>Files named "human.tra.strict.txt.gz", etc are pools of random/naive TCR clonotypes containing unique V/J/CDR3 nucleotide sequence combinations observed in data. The pools.zip file is used for TCR motif inference in VDJdb database [https://github.com/antigenomics/vdjdb-motifs], it contains human.tra.aa.txt, etc files that contain random/naive TCR clonotypes grouped by CDR3 amino acid sequence with the most frequent representative V and J.</p>
Intermolecular interactions in G protein-coupled receptor allosteric sites at the membrane interface from molecular dynamics simulations and quantum chemical calculations
<p>Allosteric modulators are called to be promising candidates in G protein-coupled receptor (GPCR) drug development by displaying target selectivity and fewer side effects. Among the allosteric sites known to date, extrahelical cavities represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability; the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze the dynamics and interactions in the PAR2, C5aR1, and GCGR receptors unbound and bound to allosteric modulators at the receptor-lipid interface using molecular dynamics simulations in three lipid compositions. In addition, we performed quantum chemical calculations to further explore electrostatic interactions and the strength of atom pairwise contacts in the stabilization of the ligand-receptor complexes. We show that besides classical hydrogen bonds weak polar interactions such as O-HC, O-Br, and S-HC contacts and aromatic interactions contribute to the binding of allosteric modulators at the extrahelical sites in the middle of the membrane. The allosteric cavities are open and detectable in various membrane compositions but not always predicted as druggable. The availability of polar atoms for interactions in such cavities can be assessed by water molecules from the simulations. Although ligand-lipid interactions are weak, the lipid tails play a role in sizing and shaping the large part of the allosteric cavity. </p> <p>You will find the following files:</p> <ul> <li>Input files of the equilibration and production protocols of MD simulations (MD_simulations_inputs.zip)</li> <li>Input files and coordinate files of F-SAPT and NCIPLOT calculations (quantum_chemical_coordiates_inputs.zip)</li> </ul>
Genome-wide identification of cell-surface and intracellular immune receptors in 350 plant species
<p>Here we identified cell-surface (LRR-RLKs, LRR-RLPs, LysM-RLKs and LysM-RLPs) and intracellular immune receptors (NB-ARCs) from the genomes of 350 plant species. </p> <p> </p> <p>Zip file contains:</p> <p>Folder 'Immune_receptor_sequences' - FASTA files of the identified LRR-RLPs, Lys-RLKs, LysM-RLPs and NB-ARCs.</p> <p>Folder 'RLK_sequences' - FASTA files of the identified LRR-RLKs (all and 20 individual subgroups).</p> <p>Folder 'RLK_trees' - Phylogenetic TREE files of the identified LRR-RLKs (all and 20 individual subgroups); classified according to their kinase domains.</p> <p>238.species - Phylogenetic tree of the 238 plant species used in the analyses (taken from <a href="https://doi.org/10.1093/jpe/rtv047">https://doi.org/10.1093/jpe/rtv047</a>).</p> <p>350.species - Phylogenetic tree of the 350 plant species used in the analyses.</p> <p>simple.to.original.ids- Translator file for the original ID of each gene. </p> <p> </p>
Code for: MHC Heterozygosity Prunes the Numbers of Different T Cell Receptors Expressed in CD4 T Cells
<p>Contains source data file and code for publication "MHC Heterozygosity Prunes the Numbers of Different T Cell Receptors Expressed in CD4 T Cells".<br>Associated FASTQ files are deposited on the NIH SRA under accession: PRJNA1106276</p>
Dataset for article: Pro-cognitive effects of dual tacrine derivatives acting as cholinesterase inhibitors and NMDA receptor antagonists
<p>Figure 1. Chemical structures of tacrine (<strong>a</strong>) and its derivatives created by introducing substituents on the aromatic core and/or altering the size of the cycloalkyl moiety attached to the aromatic region: 7-MEOTA (<strong>b</strong>), K1578 (7-chloro-1<em>H</em>,2<em>H</em>,3<em>H</em>-cyclopenta[<em>b</em>]quinolin-9-amine; <strong>c</strong>), K1592 (1-chloro-6<em>H</em>,7<em>H</em>,8<em>H</em>,9<em>H</em>,10<em>H</em>-cyclohepta[<em>b</em>]quinolin-11-amine; <strong>d</strong>), K1594 (6-methyl-1,2,3,4-tetrahydroacridin-9-amine; <strong>e</strong>), and K1599 (7-methoxy-1<em>H</em>,2<em>H</em>,3<em>H</em>-cyclopenta[<em>b</em>]quinolin-9-amine; <strong>f</strong>). Compounds in this study were used in the form of hydrochloride salts.</p> <p>Figure_2_values. Test results. Morris water maze: scopolamine-induced model of cognitive deficit in the acquisition and reversal phases. The graphs show the effects of K1578 (<strong>a</strong>), K1592 (<strong>b</strong>), K1594 (<strong>c</strong>), and K1599 (<strong>d</strong>) on escape latency during the acquisition phase, where none of the compounds ameliorated the deficit of spatial learning. The remaining graphs display the effects of K1578 (<strong>e</strong>), K1592 (<strong>f</strong>), K1594 (<strong>g</strong>), and K1599 (<strong>h</strong>) in the reversal phase, where K1578 (1 mg/kg) and K1599 (at both doses), and marginally K1592 (1 mg/kg; see in the text), mitigated the scopolamine-induced deficit of reversal learning. VEH – vehicle, the numbers in brackets denote the dose applied (mg/kg). Data are presented as the mean + SEM, * vs. VEH, * p < 0.05, ** p < 0.01, *** p < 0.001. <em>n</em> = 6–9 animals per group. Statistical significance was determined using two-way repeated measures ANOVA (a–d) or ANOVA (e, f, h) followed by Dunnett’s multiple comparisons tests.</p> <p>Figure-3_values. Test results. Morris water maze: MK-801-induced model of cognitive deficit in the acquisition phase. The graphs illustrate the effects of the compounds K1578 (<strong>a</strong>), K1592 (<strong>b</strong>), K1594 (<strong>c</strong>), and K1599 (<strong>d</strong>) on escape latency. Only K1599 (1 mg/kg) ameliorated the MK-801-induced deficit of spatial learning. VEH – vehicle, the numbers in brackets denote the dose (mg/kg). Data are presented as the mean + SEM, * vs. VEH, * p < 0.05, ** p < 0.01. <em>n</em> = 5–7 animals per group. Statistical significance was determined using two-way repeated measures ANOVA followed by Dunnett’s multiple comparisons tests.</p> <p>Figure_4_values. Open field test. The results demonstrate the effects of K1578 (<strong>a</strong>), K1592 (<strong>b</strong>), K1594 (<strong>c</strong>), and K1599 (<strong>d</strong>) on the distance moved by intact and MK-801-treated animals. VEH – vehicle, the numbers in brackets denote the dose (mg/kg). Data are presented as the mean + SEM, * vs. VEH group of the corresponding phenotype, * p < 0.05, ** p < 0.01, **** p < 0.0001. <em>n</em> = 6–14 animals per group. A significant effect of both factors (treatment and phenotype) was determined using two-way ANOVA, followed by Dunnett’s multiple comparisons tests.</p> <p>Figure-5_values. Acetylcholinesterase activity. The results document the effect of the compounds (1 mg/kg ip) on AChE activity in the hippocampus (<strong>a</strong>), prefrontal cortex (<strong>b</strong>), striatum (<strong>c</strong>), and whole brain sample (<strong>d</strong>). K1578 and K1599 decreased AChE activity in the striatum. VEH – vehicle. Data are presented as the median with minimum to maximum range, * vs. VEH, *** p < 0.001, **** p < 0.0001. VEH samples AChE enzyme activities reached the following absolute values (a) 15.19 ± 3.09 U/mg protein, (b) 9.810 ± 1.54 U/mg protein, (c) 26.05 ± 3.27 U/mg protein, and (d) 27.38 ± 3.36 U/mg protein. Significance was determined by ANOVA (graphs c, d), followed by Dunnett’s multiple comparisons tests.</p> <p>Figure_6_values. Electrophysiology: Inhibition of GluN1/GluN2A receptors by K1599. Representative whole-cell patch-clamp recordings measured from HEK293 cells expressing the GluN1/GluN2A receptors held at a membrane voltage of −80 mV and +60 mV; 30 μM K1599 was applied as indicated. Results summarizing the relative inhibition induced by 30 µM K1599, measured at the indicated membrane potentials. <em>n</em> ≥ 5 cells per each condition.</p> <p>Table_1. The rats were pseudo-randomly assigned to one of the 18 treatment groups listed in. Each group received two injections: one containing the study compound and another containing either MK-801 or scopolamine, as indicated by the group name. The vehicle group (VEH) received the DMSO vehicle (2.5 mL/kg) and saline. The “scopolamine” and “MK-801” groups received scopolamine or MK-801, respectively, along with the DMSO vehicle (2.5 mL/kg).</p> <p>Table 2. Treatment groups and <em>n</em> in biochemical experiments - AChE activity assay.</p>
"The pathway of hyaluronic acid (HA) and its receptors (CD44, RHAMM) in the regulation of Rho GTPases and their effectors in an in vitro colorectal cancer model" ("Szlak kwasu hialuronowego (HA) i jego receptorów (CD44, RHAMM) w regulacji GTPaz Rho i ich efektorów w modelu raka jelita grubego in vitro"); NCN Miniatura 2022/06/X/NZ3/00848
<p>Results from Screening for "The pathway of hyaluronic acid (HA) and its receptors (CD44, RHAMM) in the regulation of Rho GTPases and their effectors in an in vitro colorectal cancer model" the project <strong>Miniatura</strong> (<strong>2022/06/X/NZ3/00848</strong>) funded by Polish <strong>National Science Centre (NCN)</strong></p> <p>Wyniki skriningu w projekcie "Szlak kwasu hialuronowego (HA) i jego receptorów (CD44, RHAMM) w regulacji GTPaz Rho i ich efektorów w modelu raka jelita grubego in vitro", <strong>Miniatura</strong> (<strong>2022/06/X/NZ3/00848</strong>) finansowanym przez <strong>Narodowe Centrum Nauki (NCN)</strong></p>
Data set of pup retrieval test in control and V1b vasopressin receptor knockout mice
<div> <div> <div> <p>This repository contains the images and code used in the paper "Computer vision analysis of mother-infant interaction identified efficient pup retrieval in V1b receptor knockout mice".</p> <p>For effective nursing, close contact between lactating mothers and their infants is necessary. However, evaluation of maternal motivation to retrieve pups is challenging, because multiple infants were randomly accessed multiple times in changing background. We applied computer vision and deep learning analysis in this process to precisely calculate maternal behavior. Object detection in an open filed test identified less entry into the center area and less moving distance in virgin female mice lacking V1b vasopressin receptor (V1bKO) than wild-type (WT) mice. Although this character was replicated in a V1bKO mother, a pup retrieval test showed that total distances among a V1bKO mother and infants come closer in a shorter time than with a WT mother. In the medial preoptic area, V1b receptor message was partly detected in galanin- and c-fos-positive neurons after the mother was stimulated by infants. Our deep learning analysis effectively evaluated mother-infant relationship in V1bKO mice.</p> </div> </div> </div>
ScienceDex guides
Understand access before you commit
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.