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162 results for “invariability”

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geo24/100

The maternal transcriptome of the crustacean Parhyale hawaiensis is inherited asymmetrically to invariant cell lineages of the ectoderm and mesoderm

GEO Series GSE41888. Parhyale hawaiensis. 21 samples. Type: Expression profiling by array.

openGEO-OpenNov 2012View details →
geo24/100

Dual regulatory role of invariant natural killer T cells in the development and progression of hepatocellular carcinoma

GEO Series GSE279202. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2025View details →
geo24/100

Genome-wide analysis between murine invariant NKT cells and CD4+ T cells

GEO Series GSE103190. Mus musculus. 2 samples. Type: Expression profiling by array.

openGEO-OpenAug 2017View details →
geo24/100

Generation of Allogeneic Hematopoietic Stem Cell-Engineered Invariant Natural Killer T cells for Off-the-Shelf Immunotherapy [RNA-seq]

GEO Series GSE164425. Homo sapiens. 25 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenDec 2021View details →
geo24/100

Critical role for very-long chain sphingolipids in invariant natural killer T cell development and homeostasis

GEO Series GSE104205. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenOct 2017View details →
geo24/100

Global epigenetic stability of liver-resident invariant natural killer T cells in response to cues capable of inducing transcriptional re-programming

GEO Series GSE250192. Mus musculus. 24 samples. Type: Methylation profiling by high throughput sequencing; Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenOct 2024View details →
geo24/100

Mucosal-Associated Invariant T Cell Effector Function Is an Intrinsic Cell Property That Can Be Augmented by the Metabolic Cofactor α-Ketoglutarate

GEO Series GSE164740. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2021View details →
geo24/100

The human fetal thymus generates effector invariant γδ T cells in a Lin28b-dependent manner

GEO Series GSE128163. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2019View details →
geo24/100

Invariant Natural Killer T Cell Subsets Have Diverse Graft-Versus-Host-Disease-Preventing and Anti-Tumor Effects

GEO Series GSE172169. Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenApr 2021View details →
geo24/100

Comparative gene expression profile of canine and human invariant Natural Killer T (iNKT) cells at single cell level [scRNA-seq]

GEO Series GSE229457. Canis lupus familiaris; Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenSep 2023View details →
zenodo24/100

Benchmark datasets used in "Classification of Periodic Variables with Cyclic-Permutation Invariant Neural Networks"

<p>To aid the reproducibility of the results in the paper&nbsp;&ldquo;Classification of Periodic Variables with Cyclic-Permutation&nbsp;Invariant Neural Networks,&rdquo; we make our aggregation of the following&nbsp;data available. Code used to load the data and generate the results can be found at&nbsp;<a href="https://github.com/kmzzhang/periodicnetwork">https://github.com/kmzzhang/periodicnetwork</a>.&nbsp;These datasets have been constructed from publicly available data sources. If you use these&nbsp;datasets, please cite the original papers [1, 2, 3], in addition to ours [TBD].&nbsp;Others might find this data useful for testing time-series inference techniques.</p> <p>[1]&nbsp;Jayasinghe, T.&nbsp;et al.&nbsp;The ASAS-SN catalogue of variable stars I: The Serendipitous Survey.&nbsp;Monthly Notices of the Royal Astronomical Society&nbsp;477, 3145&ndash;3163 (2018). URL&nbsp;<a href="https://academic.oup.com/mnras/article/477/3/3145/4961151">https://academic.oup.com/mnras/article/477/3/3145/4961151</a>.<br> [2]&nbsp;Alcock, C.&nbsp;et al.&nbsp;The MACHO Project LMC Variable Star Inventory.II.LMC RR Lyrae Stars- Pulsational Characteristics and Indications of a Global Youth of the LMC.&nbsp;The Astronomical Journal&nbsp;111, 1146 (1996). URL&nbsp;<a href="http://adsabs.harvard.edu/abs/">http://adsabs.harvard.edu/abs/</a>1996AJ....111.1146A.<br> [3]&nbsp;Udalski, A. The Optical Gravitational Lensing Experiment. Real Time Data Analysis Systems in the OGLE-III Survey.&nbsp;Acta Astronomica&nbsp;53, 291&ndash;305 (2003). URL&nbsp;http: <a href="https://bloomlab-berkeley.slack.com//adsabs.harvard.edu/abs/2003AcA....53..291U">//adsabs.harvard.edu/abs/2003AcA....53..291U</a>.</p>

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

Domain-invariant features for mechanism of action prediction in a multi-cell-line drug screen

<p><strong>Motivation: </strong>As a proxy for diseased cells, a cell line cannot be thought of as a perfect model. Many diseases feature an important molecular heterogeneity. Consequently, a drug may be effective against one molecular subtype of a disease, but less so against another. To characterise drugs with respect to their effect not only on one cell line but on a consensus of several is therefore a promising strategy to streamline the drug discovery process.</p> <p><strong>Results: </strong>The contribution of this paper is twofold. First, we investigate whether we can predict MOA at the molecular level without optimisation of the MOA classes to the screen specificities. To this end, we benchmark a set of algorithms within a conventional pipeline, and evaluate their MOA prediction performance according to a statistically rigorous framework. Second, we extend this conventional pipeline to the simultaneous analysis of multiple cell lines, each with potentially different morphological baselines. For this, we propose multitask autoencoders, including a domain-adaptive model used to construct domain-invariant feature representations across cell lines. We apply these methods to a pilot screen of two triple negative breast cancer cell lines as models for two different molecular subtypes of the disease.</p>

opencc-by-4.0May 2019View details →
ClinicalTrials.gov24/100

Mucosal-Associated Invariant T Cells in Cases of Miscarriage

ClinicalTrials.gov study NCT04492098. IPD Sharing: Not stated. Countries: 1. Publications: 0.

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

Class II Invariant Chain HCV Vaccine Study

ClinicalTrials.gov study NCT03688061. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

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

Validation of Edema-invariant Multi-shell High Angular Resolution Diffusion Imaging (msHARDI)-Based Tractography With Intra-operative Cortical Stimulation

ClinicalTrials.gov study NCT02559401. IPD Sharing: Not stated. Countries: 1. Publications: 0.

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

Study of Neonatal IgG Fc Receptor Expression in Natural Killer T Cells Expressing an Invariant T Receptor : Implication in the Pathophysiology of Systemic Lupus

ClinicalTrials.gov study NCT05859191. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

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

Mucosal Associated Invariant T Cell During Viral Pneumonia and Acute Respiratory Distress Syndrome

ClinicalTrials.gov study NCT06720818. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

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

Identification of Time-invariant EEG Signals for Brain-Computer Interface

ClinicalTrials.gov study NCT02787200. IPD Sharing: Not stated. Countries: 1. Publications: 0.

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

In Vitro Expanded Autologous Invariant Natural Killer Cells in Cancer

ClinicalTrials.gov study NCT00631072. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
geo24/100

Single-cell Transcriptomics Reveal Different Maturation Stages and Sublineages Commitment of Human Thymic Invariant Natural Killer T Cells

GEO Series GSE210956. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenSep 2022View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
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.

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

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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