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123
datasets available to search
ShareScore release 0.9.0
Dataset results
123 results for “Target detection”
Detecting non-canonically-targeted SpCas9 generated DSBs in human cells by LAM-HTGTS
GEO Series GSE192459. Homo sapiens. 24 samples. Type: Other.
Enzymatic or in vivo installation of propargyl groups in combination with click chemistry enables enrichment and detection of methyltransferase target sites in RNA
GEO Series GSE109298. Homo sapiens; synthetic construct. 19 samples. Type: Other.
Non-invasive detection of neuroendocrine prostate cancer through targeted cell-free DNA methylation
GEO Series GSE245745. Homo sapiens. 210 samples. Type: Methylation profiling by high throughput sequencing.
Detection and characterization of microRNA expression profiling and its target genes in response to canine parvovirus in Crandell Reese Feline Kidney cells
GEO Series GSE135948. Felis catus. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Machine learning-optimized targeted detection of alternative splicing
GEO Series GSE246294. Homo sapiens. 21 samples. Type: Other.
Detection of revertant mosaicism in epidermolysis bullosa through Cas9-targeted long read sequencing
GEO Series GSE186002. Escherichia coli; Homo sapiens. 53 samples. Type: Other.
PARCLIP analysis of YBX1, ELAVL1 and ALYREF to detect their binding targets
GEO Series GSE133620. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Targeting mitochondrial metabolism for detection and treatment of doxorubicin-induced heart failure
GEO Series GSE154603. Rattus norvegicus. 16 samples. Type: Expression profiling by high throughput sequencing.
Active garment recognition and target grasping point detection using deep learning
<p>Data used in the experiments of the research paper</p> <p>E. Corona, G. Alenyà, T. Gabas, and C. Torras, “Active garment recognition and target grasping point detection using deep learning,” Pattern Recognition, vol. 74, pp. 629–641, 2018. </p>
Data from: Camouflage, detection and identification of moving targets
Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.
Data from: The effect of mood state on visual search times for detecting a target in noise: an application of smartphone technology
The study of visual perception has largely been completed without regard to the influence that an individual's emotional status may have on their performance in visual tasks. However, there is a growing body of evidence to suggest that mood may affect not only creative abilities and interpersonal skills but also the capacity to perform low-level cognitive tasks. Here, we sought to determine whether rudimentary visual search processes are similarly affected by emotion. Specifically, we examined whether an individual's perceived happiness level affects their ability to detect a target in noise. To do so, we employed pop-out and serial visual search paradigms, implemented using a novel smartphone application that allowed search times and self-rated levels of happiness to be recorded throughout each twenty-four-hour period for two weeks. This experience sampling protocol circumvented the need to alter mood artificially with laboratory-based induction methods. Using our smartphone application, we were able to replicate the classic visual search findings, whereby pop-out search times remained largely unaffected by the number of distractors whereas serial search times increased with increasing number of distractors. While pop-out search times were unaffected by happiness level, serial search times with the maximum numbers of distractors (n = 30) were significantly faster for high happiness levels than low happiness levels (p = 0.02). Our results demonstrate the utility of smartphone applications in assessing ecologically valid measures of human visual performance. We discuss the significance of our findings for the assessment of basic visual functions using search time measures, and for our ability to search effectively for targets in real world settings.
PSMA-Targeted 18F-DCFPyL PET/MRI for the Detection of Prostate Cancer
ClinicalTrials.gov study NCT04910425. IPD Sharing: Not stated. Countries: 1. Publications: 0.
TMTP1 Targeting Micro-metastasis LN in Laparoscopic SLN Detection in Cervical Cancer
ClinicalTrials.gov study NCT03549195. IPD Sharing: NO. Countries: 1. Publications: 0.
Targeted Biopsy or Standard Biopsy for Clinical Significant Prostate Cancer Detection
ClinicalTrials.gov study NCT03572946. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Clinical Validation of ColonAiQ (a Blood-based Assay Targeting ctDNA Methylation) for Colorectal Cancer Detection
ClinicalTrials.gov study NCT06347887. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Multimodality Imaging Combined With Multiple Targets Pathological Examination for Detecting of Biological Borders of Gliomas: a Clinical Application Study
ClinicalTrials.gov study NCT02941302. IPD Sharing: NO. Countries: 1. Publications: 0.
Improved Detection of Neonatal Sepsis Using a Targeted Biomarker Assay
ClinicalTrials.gov study NCT01120678. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Detection of an Endovascular Treatment Target in Patients With an Acute, Spontaneous Intracerebral Hemorrhage
ClinicalTrials.gov study NCT05504941. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Molecularly Targeted Theranostic Approach for the Detection and Treatment of Metastatic Carcinomas
ClinicalTrials.gov study NCT06389123. IPD Sharing: NO. Countries: 1. Publications: 0.
The Target Urine VOCs Biosensor for Genitourinary Malignancy Detection
ClinicalTrials.gov study NCT06211010. IPD Sharing: NO. Countries: 1. Publications: 0.
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.