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1,434 results for “subtypes”
The supplemental files of 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'
<p>Our upload is the suplemental files which have been cited in the manuscript 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'</p>
Molecular dynamics simulation of Conus textile conotoxin Txd13 in complex with a3b2, a3b4, a6b2 or a6b4 nAChR subtypes.
<p>This folder contains the coordinate and parameter files used to run molecular dynamics simulations of the toxin Txd13 (sequence GCCSNPPCIANPMC) in complex with four nicotinic acetylcholine receptor (nAChR) subtypes: a3b2, a3b4, a6b2 and a6b4 nAChRs. For each system several files are provided:</p> <p>1) an homology model that was used as a starting conformation is provided (eg 'a3b2_txd13.B99990023.pdb'),<br> 2) an Amber Parm7 topology file (eg 'a3b2_txd13_0023.prmtop'),<br> 3) a trajectory files containig 1250 frames extracted from a 100 ns molecular dynamics simulation (eg 'a3b2_txd13_0023_md_smaller.nc') created using pmemd from the Amber 18 package,<br> 4) the log file of this simulations (eg 'a3b2_txd13_0023_md.log'), and<br> 5) the coordinate file representing the minimized verion of the centroid frame of each simulation (with water and ions removed for conveniance) (eg 'a3b2_txd13_0023_md_centroid_min_nowat.pdb')</p> <p>The parameters used for the molecular dynamics simulations are provided in the 'md.in' file.</p> <p>All the text files have been compressed in the 'xz' format</p>
Diagnostic Accuracy of Adrenal Imaging for Subtype Diagnosis in Primary Aldosteronism: Systematic Review and Meta-Analysis
<p>Objectives: Accurate subtype classification in primary aldosteronism (PA) is critical in assessing the optimal treatment options. This study aimed to evaluate the diagnostic accuracy of adrenal imaging for unilateral PA classification.</p> <p>Methods: Systematic searches of PubMed, EMBASE, and the Cochrane databases were performed from January 1, 2000, to February 1, 2020, for all studies that used computed tomography (CT) or magnetic resonance imaging (MRI) in determining unilateral PA and validated the results against invasive adrenal vein sampling (AVS). Summary diagnostic accuracies were assessed using a bivariate random-effects model. Subgroup analyses, meta-regression and sensitivity analysis were performed to explore the possible sources of heterogeneity.</p> <p>Result: A total of 25 studies, involving a total of 4669 subjects, were identified. The overall analysis revealed a pooled sensitivity of 68% (95% confidence interval [CI]: 61 to 74) and specificity of 57% (95% CI: 50 to 65) for CT/MRI in identifying unilateral PA. Sensitivity was higher in the contrast-enhanced (CT) group versus the traditional CT group [77% (95% CI: 66 to 85) vs. 58% (95% CI: 50 to 66)]. Subgroup analysis stratified by screening test for PA showed that the sensitivity of the aldosterone-to-renin ratio (ARR) group was higher than that of the non-ARR group [78% (95% CI: 69 to 84) vs. 66% (95% CI: 58 to 72)]. The diagnostic accuracy of PA patients aged ≤40 years was reported in 4 studies, and the overall sensitivity was 71%, with 79% specificity. Meta-regression revealed a significant impact of sample size on sensitivity and of age and study quality on specificity.</p> <p>Conclusion: CT/MRI is not a reliable alternative to invasive AVS without excellent sensitivity or specificity for correctly identifying unilateral PA. Even in young patients (≤40 years), 21% of patients would have undergone unnecessary adrenalectomy based on imaging results alone.</p>
Data from: Identification of combinatorial host-specific signatures with a potential to affect host adaptation in influenza A H1N1 and H3N2 subtypes
Background: The underlying strategies used by influenza A viruses (IAVs) to adapt to new hosts while crossing the species barrier are complex and yet to be understood completely. Several studies have been published identifying singular genomic signatures that indicate such a host switch. The complexity of the problem suggested that in addition to the singular signatures, there might be a combinatorial use of such genomic features, in nature, defining adaptation to hosts. Results: We used computational rule-based modeling to identify combinatorial sets of interacting amino acid (aa) residues in 12 proteins of IAVs of H1N1 and H3N2 subtypes. We built highly accurate rule-based models for each protein that could differentiate between viral aa sequences coming from avian and human hosts. We found 68 host-specific combinations of aa residues, potentially associated to host adaptation on HA, M1, M2, NP, NS1, NEP, PA, PA-X, PB1 and PB2 proteins of the H1N1 subtype and 24 on M1, M2, NEP, PB1 and PB2 proteins of the H3N2 subtypes. In addition to these combinations, we found 132 novel singular aa signatures distributed among all proteins, including the newly discovered PA-X protein, of both subtypes. We showed that HA, NA, NP, NS1, NEP, PA-X and PA proteins of the H1N1 subtype carry H1N1-specific and HA, NA, PA-X, PA, PB1-F2 and PB1 of the H3N2 subtype carry H3N2-specific signatures. M1, M2, PB1-F2, PB1 and PB2 of H1N1 subtype, in addition to H1N1 signatures, also carry H3N2 signatures. Similarly M1, M2, NP, NS1, NEP and PB2 of H3N2 subtype were shown to carry both H3N2 and H1N1 host-specific signatures (HSSs). Conclusions: To sum it up, we computationally constructed simple IF-THEN rule-based models that could distinguish between aa sequences of avian and human IAVs. From the rules we identified HSSs having a potential to affect the adaptation to specific hosts. The identification of combinatorial HSSs suggests that the process of adaptation of IAVs to a new host is more complex than previously suggested. The present study provides a basis for further detailed studies with the aim to elucidate the molecular mechanisms providing the foundation for the adaptation process.
Data from: Subtype diversity and reassortment potential for co-circulating avian influenza viruses at a diversity hot spot
1. Biological diversity has long been used to measure ecological health. While evidence exists from many ecosystems that declines in host biodiversity may lead to greater risk of disease emergence, the role of pathogen diversity in the emergence process remains poorly understood. Particularly, because a more diverse pool of pathogen types provides more ways in which evolutionary innovations may arise, we suggest that host–pathogen systems with high pathogen diversity are more prone to disease emergence than systems with relatively homogeneous pathogen communities. We call this prediction the diversity-emergence hypothesis. 2. To show how this hypothesis could be tested, we studied a system comprised of North American shorebirds and their associated low-pathogenicity avian influenza (LPAI) viruses. These viruses are important as a potential source of genetic innovations in influenza. A theoretical contribution of this study is an expression predicting the rate of viral subtype reassortment to be proportional to both prevalence and Simpson's Index, a formula that has been used traditionally to quantify biodiversity. We then estimated prevalence and subtype diversity in host species at Delaware Bay, a North American AIV hotspot, and used our model to extrapolate from these data. 3. We estimated that 4 to 39 virus subtypes circulated at Delaware Bay each year between 2000 and 2008, and that surveillance coverage (percentage of co-circulating subtypes collected) at Delaware Bay is only about 63·0%. Simpson's Index in the same period varied more than fourfold from 0·22 to 0·93. These measurements together with the model provide an indirect, model-based estimate of the reassortment rate. A proper test of the diversity-emergence hypothesis would require these results to be joined to independent and reliable estimates of reassortment, perhaps obtained through molecular surveillance. 4. These results suggest both that subtype diversity (and therefore reassortment) varies from year to year and that several subtypes contributing to reassortment are going undetected. The similarity between these results and more detailed studies of one host, ruddy turnstone (Arenaria interpres), further suggests that this species may be the primary host for influenza reassortment at Delaware Bay. 5. Biological diversity has long been quantified using Simpson's Index. Our model links this formula to a mechanistic account of reassortment in multipathogen systems in the form of subtype diversity at Delaware Bay, USA. As a theory of how pathogen diversity may influence the evolution of novel pathogens, this work is a contribution to the larger project of understanding the connections between biodiversity and disease.
Data from: Reassortment patterns of avian influenza virus internal segments among different subtypes
Background: The segmented RNA genome of avian Influenza viruses (AIV) allows genetic reassortment between co-infecting viruses, providing an evolutionary pathway to generate genetic innovation. The genetic diversity (16 haemagglutinin and 9 neuraminidase subtypes) of AIV indicates an extensive reservoir of influenza viruses exists in bird populations, but how frequently subtypes reassort with each other is still unknown. Here we quantify the reassortment patterns among subtypes in the Eurasian avian viral pool by reconstructing the ancestral states of the subtypes as discrete states on time-scaled phylogenies with respect to the internal protein coding segments. We further analyzed how host species, the inferred evolutionary rates and the dN/dS ratio varied among segments and between discrete subtypes, and whether these factors may be associated with inter-subtype reassortment rate. Results: The general patterns of reassortment are similar among five internal segments with the exception of segment 8, encoding the Non-Structural genes, which has a more divergent phylogeny. However, significant variation in rates between subtypes was observed. In particular, hemagglutinin-encoding segments of subtypes H5 to H9 reassort at a lower rate compared to those of H1 to H4, and Neuraminidase-encoding segments of subtypes N1 and N2 reassort less frequently than N3 to N9. Both host species and dN/dS ratio were significantly associated with reassortment rate, while evolutionary rate was not associated. The dN/dS ratio was negatively correlated with reassortment rate, as was the number of negatively selected sites for all segments. Conclusions: These results indicate that overall selective constraint and host species are both associated with reassortment rate. These results together identify the wild bird population as the major source of new reassortants, rather than domestic poultry. The lower reassortment rates observed for H5N1 and H9N2 may be explained by the large proportion of strains derived from domestic poultry populations. In contrast, the higher rates observed in the H1N1, H3N8 and H4N6 subtypes could be due to their primary origin as infections of wild birds with multiple low pathogenicity strains in the large avian reservoir.
Data from: Aldosterone reduction rate after saline infusion may be a novel clinical prediction of determining subtypes of primary aldosteronism
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective</b>Accurate assessment of the localization of aldosterone-producing adenomas (APAs) is essential for the treatment of primary aldosteronism (PA). Although adrenal venous sampling (AVS) is the standard method of reference for subtype diagnosis in PA, controversy exists concerning the criteria for interpretation. This study aimed to determine better indicators that can reliably predict subtypes of PA. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Method</b>Retrospective analysis in single-cohort including 209 patients with PA who were subjected to AVS. 82 patients whose plasma aldosterone concentrations (PAC) were normalized after surgery were histopathologically or genetically diagnosed with APA. The accuracy of image findings was compared to AVS results. Receiver operating characteristic (ROC) curve analysis between the operated and no apparent laterality groups was performed using AVS parameters and loading test for diagnosis of PA. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Result </b>The agreement between image findings and AVS results was 56.3%. ROC curve analysis revealed that lateralization index (LI) after ACTH stimulation cutoff value was 2.40, with 98.8% sensitivity and 97.1% specificity. The contralateral suppression index (CSI) cutoff value was 1.19, with 98.0% sensitivity and 93.9% specificity. All patients over the LI and CSI cutoff values exhibited unilateral subtypes. Among the loading test, <span><span>the best classification accuracy was achieved using the </span></span>PAC reduction rate after saline infusion<span><span>test (SIT) >33.8%, which yielded 87.2% sensitivity or PAC after SIT <87.9 pg/mL 86.2% specificity for predicting bilateral PA. </span></span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusion</b>The combined criterion of the PAC reduction rate and PAC after SIT may determine a subset of patients with APA who should be performed AVS for validation. </span></span></span></span></span></span></span></span></span></span></span></p> <p><br> </p>
Data for "Joint Clinical and Molecular Subtyping of COPD with Variational Autoencoders"
<p>Data for paper "Data for "Joint Clinical and Molecular Subtyping of COPD with Variational Autoencoders", Maiorino et al.</p> <p>The associated code repository is at<a href="https://github.com/reemagit/joint_subtyping_vae"> https://github.com/reemagit/joint_subtyping_vae</a></p>
Data for multi-dimensional characterization of cellular states in ovarian cancer reveals clinically relevant immunological subtypes and therapeutic vulnerabilities
<p>The data for figures</p>
Integrated analysis of "-omic" landscapes in breast cancer subtypes: Supplementary Dataset
<p>This is a supplementary dataset with raw data, scripts, complete analysis files, and supplementary tables/figures for the manuscript entitled "Integrated analysis of “-omic” landscapes in breast cancer subtypes". It is uploaded as a single file archive with the following structure: </p> <ol> <li>The <strong>Data</strong> folder contains TCGA-BRCA omic (RNA-Seq, methylation, CNV, and SNV) processed data and multi-SOM pipeline scripts. </li> <li>The <strong>BRCA-TCGA-mlSOM</strong> folder contains data and scripts for multi-SOM downstream analysis including functional annotation of gene modules (spots), comparison of their levels in cancer subtypes with true normal tissue, regression analysis for assessment of the association between omic layers, survival, and clinical parameter analysis. </li> <li>The <strong>Supplementary data folder </strong>contains supplementary tables and figures cited in the text. </li> </ol>
Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics: fastq & bam files - Sample S5_Rec
<p>You can find here the fastq and bam files related to the datasets used in the publication: </p> <p>In this particular upload, you can find the fastq (version1) and bam (version2) files of the two replicates of sample S5_Rec (A121573)</p> <p><strong>Valdeolivas, A., Amberg, B., Giroud, N. <em>et al.</em> Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics. <em>npj Precis. Onc.</em> 8, 10 (2024). https://doi.org/10.1038/s41698-023-00488-4</strong></p> <p> </p> <p> </p>
Association of Peripheral Monocytic-Myeloid-Derived Suppressor Cells with Molecular Subtypes in Single Center Endometrial Cancer Patients Receiving Carboplatin + Paclitaxel/Avelumab (MITO END-3 Trial)
<p><span>The MITO-END3 trial compared carboplatin and paclitaxel (</span><span>CP</span><span>) with avelumab plus carboplatin and paclitaxel (</span><span>CPA)</span><span> as first-line treatment in endometrial cancer (EC) patients and </span><span>demonstrated a significant interaction between avelumab response and mismatch repair status. To investigate prognostic/predictive biomarker, </span><span>twenty-nine MITO-END3-EC patients were evaluated at pre-treatment (B1) and at the end of CP/CPA treatment (B2) for </span><span>peripheral Myeloid derived suppressor cells (MDSC) and Tregs. </span><span>At B2, <span>effector</span> Tregs frequency was significantly higher in patients treated with CPA as compared to CP (p=0.038). Both treatments (CP/CPA) induced significant decrease in peripheral M-MDSC (-5.41%) in TCGA 2-MSI-High as compared to TCGA-category 4 tumors (p=0.004). In accordance, both treatments induced M-MDSCs (+5.34%) in MSS patients as compared to MSI-High patients (p=0.001). Moreover, in a subgroup of patients, </span><span>primary tumors were highly infiltrated by M-MDSCs in MSS as compared to MSI-high ECs. </span><span>A post hoc analysis displayed higher frequeny of M-MDSCs (p=0.020) and lower frequency of CD4+ (p<0.005) at pretreatment in EC patients as compared to healthy donors. </span><span>In conclusion, </span><span>the</span><span> peripheral evaluation of MDSCs and Tregs correlated with molecular features in EC treated with CP/CPA and may add insights in identifying EC patients responder to first line chemo/chemo-immunotherapy. </span></p>
Data from: Clinical correlation of multiple sclerosis immunopathological subtypes
<p><b>Objective:</b> To compare clinical characteristics across immunopathological subtypes of patients with multiple sclerosis.</p> <p><b>Methods:</b> Immunopathological subtyping was performed on specimens from 547 patients with biopsy and/or autopsy confirmed CNS demyelination.</p> <p><b>Results: </b>The frequency of immunopathological subtypes were pattern I (23%), II (56%), and III (22%). Immunopatterns were similar in terms of age at autopsy/biopsy (median age 41 years, range 4-83 years, p=0.16) and proportion female (54%, p=0.71). Median follow-up after symptom onset was 2.3 years (range 0-38y). In addition to being overrepresented among autopsy cases (45% vs. 19% in biopsy cohort, p<0.001), index attack-related disability was higher in pattern III vs. pattern II (median EDSS 4 vs. 3, p=0.02). Monophasic clinical course was more common in patients with pattern III than pattern I or II (59% vs. 33% vs. 32%, p<0.001). Similarly, patients with pattern III pathology were likely to have progressive disease compared to patients with patterns I or II, when followed for ≥5 years (24% overall, p=0.49), with no differences in long-term survival, despite a more fulminant attack presentation.</p> <p><b>Conclusion:</b> All three immunopatterns can be detected in active lesions, although they are found less frequently later into the disease due to the lower number of active lesions. Pattern III is associated with a more fulminant initial attack than either pattern I or II. Biopsied patients appear to have similar long-term outcomes irrespective of their immunopatterns. Progressive disease is less associated with the initial immunopattern and suggests convergence into a final common pathway related to the chronically denuded axon.</p>
Data from: Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes
<div> <div> <div> <p><strong>Background</strong>: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data.</p> <p><strong>Methods</strong>: We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts.</p> <p><strong>Results</strong>: PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R2) of 24% (interquartile range=11-30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (OR=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 80th percentile of the PRS- CS distribution had significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P=2.4×10-12). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC=0.839 vs. AUC=0.895, P=6.8×10-9).</p> <p><strong>Conclusions</strong>: Genome-wide PRS has potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.</p> <p><strong>Citation</strong>: Nakase T, Guerra GA, Ostrom QT, et al. Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes. <em>Neuro-Oncology</em>. Published online June 25, 2024:noae112. doi:10.1093/neuonc/noae112</p> </div> </div> </div>
Alignment, ML and MCC trees of dataset A from "Reconstruction of the genetic history and the current spread of HIV-1 subtype A in Germany"
<p>-Alignment and phylogeographic MCC tree of 708 HIV subtype A1 sequences called dataset A in the manuscript "Reconstruction of the genetic history and the current spread of HIV-1 subtype A in Germany"</p> <p>-marked up MCC tree showing SDRM in dataset A</p> <p>-marked up ML tree showing transmission cluster selection in dataset A</p>
INDICATORS TO DISTINGUISH SYMPTOM ACCENTUATORS FROM SYMPTOM PRODUCERS IN INDIVIDUALS WITH A DIAGNOSED ADJUSTMENT DISORDER: A PILOT STUDY ON INCONSISTENCY SUBTYPES USING SIMS AND MMPI-2-RF
<p>In the context of legal damage evaluations, evaluees may exaggerate or simulate symptoms in an attempt to obtain greater economic compensation. To date, practitioners and researchers have focused on detecting malingering behavior as an exclusively unitary construct. However, we argue that there are two types of inconsistent behavior that speak to possible malingering—accentuating (i.e., exaggerating symptoms that are actually experienced) and simulating (i.e., fabricating symptoms entirely)—each with its own unique attributes; thus, it is necessary to distinguish between them. The aim of the present study was to identify objective indicators to differentiate symptom accentuators from symptom producers and consistent participants. </p>
Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation
<p>Fibroblast single-cell processed expression data and annotations used in the study "Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation"</p>
Memory reactivation in rat medial prefrontal cortex occurs in a subtype of cortical UP state during slow-wave sleep
Interaction between hippocampal sharp-wave ripples (SWRs) and UP states, possibly by coordinated reactivation of memory traces, is conjectured to play an important role in memory consolidation. Recently, it was reported that SWRs were differentiated into multiple subtypes. However, whether cortical UP states can also be classified into subtypes is not known. Here, we analysed neural ensemble activity from the medial prefrontal cortex from rats trained to run a spatial sequence-memory task. Application of the hidden Markov model (HMM) with three states to epochs of UP–DOWN oscillations identified DOWN states and two subtypes of UP state (UP-1 and UP-2). The two UP subtypes were distinguished by differences in duration, with UP-1 having a longer duration than UP-2, as well as differences in the speed of population vector (PV) decorrelation, with UP-1 decorrelating more slowly than UP-2. Reactivation of recent memory sequences predominantly occurred in UP-2. Short-duration reactivating UP states were dominated by UP-2 whereas long-duration ones exhibit transitions from UP-1 to UP-2. Thus, recent memory reactivation, if it occurred within long-duration UP states, typically was preceded by a period of slow PV evolution not related to recent experience, and which we speculate may be related to previously encoded information. If that is the case, then the transition from UP-1 to UP-2 subtypes may help gradual integration of recent experience with pre-existing cortical memories by interleaving the two in the same UP state. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.
HIV-1 Subtypes of HIV-1 patients with virologic failure in different voluntary counseling testing and treatment centers in Khartoum State, Sudan, 2020
<p><strong>Background</strong>: Various HIV subtypes have evolved and play significant roles in the pathogenesis, progression, and response to treating human immunodeficiency virus.</p> <p><strong>Method</strong>: One hundred and ten HIV-1 patients who attended different voluntary counseling testing and treatment centers in Khartoum state were included. Nested PCR was done for the <em>Pol</em> gene in plasma samples that showed virologic failure, and then successfully amplified samples were sequenced for HIV-1 subtype's identification.</p> <p><strong>Result</strong>: Out of the total, 20 (18.2%) samples showed virologic failure, of them only 9 (45%) were successfully amplified and sequenced; of them, 55.6% (5/9) belonged to subtype C, and only 11.1% (1/9) occurred at the frequency of each subtype A, D, G, and K.</p> <p><strong>Conclusion</strong>: No relationship between HIV-1 subtypes and increased viral load were detected, although HIV-1 subtypes are still a strong predictor of disease progression.</p>
Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis
<p>Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis</p>
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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.