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1,073 results for “comparative expression”
Gene expression changes in Cenococcum geophilum 1.58-Pinus sylvestris ectomycorrhizal roots, sclerotia and extramatrical mycelium compared to Cenococcum geophilum free-living mycelium
GEO Series GSE108866. Pinus sylvestris; Cenococcum geophilum 1.58. 12 samples. Type: Expression profiling by high throughput sequencing.
[LS2N_IPI_DisFER] Comparing the Robustness of Humans and Deep Neural Networks on Facial Expression Recognition
<h2>DisFER</h2> <p>Distorted-FER (DisFER), a new facial expression recognition (FER) dataset composed of a wide number of distorted images of faces.</p> <p> </p> <h2>Materials and Methods</h2> <h4>Dataset</h4> <div>The source images used in our experiment come from the Facial Expression Recognition 2013 (FER-2013) dataset [1]. This dataset was firstly introduced in 2013 at the International Conference on Machine Learning, and has been used in a large number of research works since then, as it encompasses naturalistic conditions and challenges. This dataset consists of 35,887 images of faces in 48 × 48 format, collected thanks to a Google search. Human accuracy on FER-2013 was estimated by its authors around 65.5% [1].</div> <div>To build the Distorted-FER (DisFER) dataset, we randomly selected, from FER-2013, twelve images per basic emotion, as defined by Ekman [2] (i.e., anger, disgust, fear, happiness, neutral, sadness, and surprise). This yields a total of 84 source images. Each original stimulus was then distorted using three different types of distortions, i.e., Gaussian blur (GB), Gaussian noise (GN), and salt-and-pepper noise (SP). Each distortion was applied at distinct levels: three standard deviation values were tested for GB, i.e., 0.8, 1.1, and 1.4; similarly for GN with standard deviation values equal to 10, 20, and 30; while probability levels of 0.02, 0.04, and 0.06 were chosen for SP; corresponding to low, medium, and high distortions, respectively. </div> <div> </div> <div> <h4>Crowdsourcing Experiment</h4> <div>In order to collect as many votes as possible on our dataset, and because rating 840 images is time-consuming and can be extremely tiring for a single participant, we decided to set up a crowdsourcing experiment. Such experiments indeed allow the conduct of large-scale subjective tests with reduced costs and efforts.</div> <div>The DisFER dataset was therefore split into twenty-one playlists of forty images each, with a view to keep the tests as fast as possible—as crowdsourcing experiments should not last more than ten minutes or so. Playlists were carefully designed to contain the same numbers of images of a given configuration (i.e., emotion, distortion types, and distortion levels). Among a playlist, images were randomly displayed to participants.</div> <div>Each participant was asked to choose which emotion (i.e., anger, disgust, fear, happiness, neutral, sadness, or surprise) they recognized in the displayed image. No time constraint was imposed on participants to fulfill the task.</div> <div> </div> <div>A total of 1051 participants (including 50% of females) were recruited using the Prolific platform [3]. Prolific takes into consideration researchers’ needs by maintaining a subject recruitment process that is similar to that of a laboratory experiment. Indeed, participants are fully informed that they are being recruited for a research study. Consequently, this platform allows researchers to eliminate ethical concerns, and it further improves the reliability of collected data.</div> <div> </div> Participants were aged between 19 and 75 years old (with a mean of 30±8.53 -- note that three participants did not wish to respond). Twenty playlists out of twenty-one were entirely watched and rated by fifty distinct participants, whereas one playlist was watched and evaluated by fifty-one participants.</div> <div> </div> <div> <h2>References</h2> </div> <div>[1] Goodfellow, I.J.; Erhan, D.; Carrier, P.L.; Courville, A. Challenges in Representation Learning: A Report on Three Machine Learning Contests. In Proceedings of the Neural Information Processing, Daegu, South Korea, 3–7 November 2013; Springer: Berlin/Heidelberg, Germany, 2013; pp. 117–124</div> <div>[2] Ekman, P. An argument for basic emotions. Cogn. Emot. <strong>1992</strong>, 6, 169–200</div> <div>[3] https://www.prolific.com/</div> <div> </div>
A Study to Compare the Efficacy of Nivolumab and Relatlimab Plus Chemotherapy vs Pembrolizumab Plus Chemotherapy for Stage IV/Recurrent Non-squamous Non-small Cell Lung Cancer With PD-L1 Expression ≥
ClinicalTrials.gov study NCT06561386. IPD Sharing: YES. Countries: 30. Publications: 0.
Blood Gene Expression Signature in Patients Diagnosed With Probable Alzheimer's Disease Compared to Patients Suffering From Other Types of Dementia
ClinicalTrials.gov study NCT00880347. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Follow-up of Actual Patient Care Site Two Months After Hospitalisation Compared With Their Expressed Choice Regarding Subsequent Care Site (RESPECT)
ClinicalTrials.gov study NCT04628234. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparative Expression of ER,PR and HER2/Neu in Initial and Recurrent Breast Cancer.
ClinicalTrials.gov study NCT07056205. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Non-comparative Evaluation of Facial Expressions Following Lower Face Correction Using Emervel Classic and Emervel Deep
ClinicalTrials.gov study NCT02672644. IPD Sharing: NO. Countries: 1. Publications: 0.
Study to Determine Possible Effects of Apalutamide, Compared to Placebo, on EGFR Expression in Patients With Non-muscle Invasive Bladder Cancer
ClinicalTrials.gov study NCT05521698. IPD Sharing: YES. Countries: 1. Publications: 0.
Investigation of Cannabinoid 2-receptor Expression in the Brain and Spine of ALS-patients Compared to Healthy Controls With PET (18F-RoSMALS)
ClinicalTrials.gov study NCT05880563. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparing the Reliability of Expressed Prostatic Secretion (EPS) and Post Massage Urine (PMU) for the Prediction of Prostate Cancer Biopsy Outcome
ClinicalTrials.gov study NCT01441687. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prognostic Value of (DHODH) Expression in (HGSOC): A Comparative Study Between Neoadjuvant and Adjuvant Chemotherapy Settings
ClinicalTrials.gov study NCT07366242. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparative gene expression profiling of human PGP1 iPS, lymphocyte, donor fibroblasts
GEO Series GSE54733. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Comparative gene expression analyses using E4.0 cloned blastocysts
GEO Series GSE49172. Mus musculus. 14 samples. Type: Expression profiling by array.
Transcriptome-wide expression analysis of pooled brain samples of patients with Alzheimer's disease compared to controls
GEO Series GSE138214. Homo sapiens. 28 samples. Type: Expression profiling by genome tiling array.
Comparative analysis of gene expression in HepG2-NTCP_HA:HBc upon treatment with CAM-A or CAM-E
GEO Series GSE263292. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
miRNA expression profile in aortas from LysM-Cre/Dicerflox/flox/Apoe–/– mice compared with LysM-Cre/Dicerwt/wt/Apoe–/– mice fed with high-fat diet for 12 weeks
GEO Series GSE87719. Mus musculus. 6 samples. Type: Expression profiling by RT-PCR.
Comparative gene expression analysis of planktonic Porphyromonas gingivalis ATCC 33277 in the presence of a growing biofilm versus planktonic cells
GEO Series GSE122623. Porphyromonas gingivalis; Porphyromonas gingivalis ATCC 33277. 6 samples. Type: Expression profiling by array.
Gene expression profiling of CLL cells with hyperactivated Notch1 compared to control CLL cells [RNA-seq]
GEO Series GSE147836. Mus musculus. 13 samples. Type: Expression profiling by high throughput sequencing.
High Expression Levels of Keratinocyte Antimicrobial Proteins in Psoriasis Compared with Atopic Dermatitis.
GEO Series GSE6601. Homo sapiens. 6 samples. Type: Expression profiling by array.
Genome-wide analysis of gene expression in jnk1-/-jnk2-/- immortalized mouse embryonic fibroblasts compared to wildtype counterparts co-cultivated with differentiating keratinocytes
GEO Series GSE48612. Mus musculus. 18 samples. Type: Expression profiling by array.
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.