Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4,566
datasets available to search
ShareScore release 0.9.0
Dataset results
4,566 results for “marker”
Data and script for Andrews et al. 'A marker of biological ageing predicts risk preference in European starlings, Sturnus vulgaris'
<p>Data and script for Andrews et al. 'A marker of biological ageing predicts risk preference in European starlings, Sturnus vulgaris'. Consists: One R script and three data .csv files.</p>
Data for "The ipsilateral silent period: an early diagnostic marker of callosal disconnection in ALS"
<p>We studied the copus callosum in ALS patients using using TMS and diffusion tensor imaging</p>
Figure 1 in Enzymatic activity of bone markers on Lithobates catesbeianus (Shaw, 1802) growth during the ossification process
Figure 1. Effect of pH on p NPPase activity of alkaline phosphatase released by PIPLC present in the SPIPLC fraction of tadpole epiphysis and diaphysis and frog epiphysis. T.E.= Tadpole Epiphysis; T.D. = Tadpole Diaphysis; F.E. = Frog Epiphysis.
Dataset: Marker Therapeutics, Inc. (MRKR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 1 in The Dynamics Of Genetic Structure Of Round G O B Y N E O G O B I U S M E L A N O S T O M U S (Pa L L A S) Groupings In The Odessa Bay Of The Black Sea Utilizing Biochemical Marker Loci
Fig. 1. Frequencies of S-alleles by polymorphic locus Es2 in round goby groupings from different parts of the Odessa Bay. * – significant deviation of allele frequencies in round goby groupings from the south and the north part of the Odessa Bay (Р = 0,05); # – significant deviation of allele frequencies in round goby groupings in the south part of the Odessa Bay in 2015-2016 in comparison to 2013-2014 (Р = 0,05).
Fig. 2 in The Dynamics Of Genetic Structure Of Round G O B Y N E O G O B I U S M E L A N O S T O M U S (Pa L L A S) Groupings In The Odessa Bay Of The Black Sea Utilizing Biochemical Marker Loci
Fig. 2. Frequencies of S-alleles by polymorphic locus of myogene 3 in round goby groupings from different parts of the Odessa Bay * – significant deviation of allele frequencies in round goby groupings from the south and the north part of the Odessa Bay in 2013 and 2014 (Р = 0,05); # – significant deviation of allele frequencies in round goby groupings from the south part of the Odessa Bay in 2013-2014 in comparison to 2015 (Р = 0,05).
Fig. 1 in Grouping and genetic diversity of different watermelon ecotypes based on agro-morphological traits and ISSR marker
Fig. 1. Grouping the watermelon ecotypes based on agro-morphological traits using UPGMA method. The symbols for the ecotypes are presented in Table 1.
Figure 5 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 5. The cloned nucleotide information by Sanger-sequencing.A. The sequences of clone M9-21 with 514bp [The GenBank accession number: MZ417502]. B. The sequences of clone M19-45 with 795bp [The GenBank accession number: MZ484089]. C. The sequences of clone N1-12 with 761bp [The GenBank accession number: MZ417504]. D. The sequences of clone N2-11 with 718bp [The GenBank accession number: MZ417505].
Figure 4 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 4. Clone identification of clones M9-21 (A), M19-45 (B), N1-12 & N2-11 (C) by without (lanes 1) or with (lanes 2) EcoRI digestion. The black arrows represent desired PCR product or specific insert bands in different clones. Lane M indicates the DNA molecular weight marker DL2000 with the fragment size (bp).
Figure 3 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 3. Identification of positive clone M19-45, M9-21 (A), and N1-12, N2-11 (B) by PCR amplification with vector T7/sp6 primers.
Figure 2 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 2. Improved RAPD amplification from DNA samples of D.nobile (listed in Table 1) using different RAPD primers. A. primers M9, M9-21; B. primers M19, M19-45; C. primers N1, N1-12; D. primers N2, N2-11.
Figure 1 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 1. The localities of samples D. nobile cultivars from different regions in China. Spots in black indicate cities and lines in light blue indicate the Yellow River (up) and the Yangtze River (down).
Figure 6 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 6. Development of stable RAPD-SCAR markers for M19-45 (A), M9-21 (B), N1-12 (C), N2-11 (D). Lane 1-10 is D. nobile, 11-21 is D. officinale Kimura et Migo,Lycium barbarum L.,Litchi chinensis Sonn., Ginkgo biloba L., Canarium album (Lour.) Raeusch., Lonicera japonica Thunb., Mentha haplocalyx Briq., Penthorum chinense Pursh, Angelica sinensis, Gardenia jasminoides, Ganoderma lucidum (Leyss. ex Fr.) Karst.. Lane M indicates the DNA molecular weight marker DL2000.
Figure 4 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 4. UPGMA dendrogram prepared from the genetic distances (Nei and Li, 1979) of the pitahaya populations.
Figure 3 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 3. Population genetic structure of Pitahaya for each sample analyzed, estimated using the Structure software.
Figure 2. Delta K in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 2. Delta K values obtained from Harvester Structure, calculated as the mean of the probability of K divided by the standard deviation of the probability of K.
Figure 1. Dendrogram showing relationships among 70 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 1. Dendrogram showing relationships among 70 genotypes of Selenicereus megalanthus, according to the UPGMA analysis using eight ISSR markers.
Normalized and batch-corrected concentration of 43 immune markers from 248 subjects with stress-related mental disorders and 36 healthy controls
<h1>Abstract</h1> <p>In a subset of patients with mental disorders, such as depression, low-grade inflammation and altered immune marker concentrations are observed. However, these immune alterations are often assessed by only one data type and small markers panels. Here, we used a transdiagnostic approach and combined data from two cohorts to define subgroups of depression symptoms across the diagnostic spectrum through a large-scale multi-omics clustering approach in 237 individuals. The method incorporated age, body mass index (BMI), 43 plasma immune markers and RNA-seq data from peripheral mononuclear blood cells (PBMCs). Our initial clustering revealed four clusters, including two immune-related depression symptom clusters characterized by elevated BMI, higher depression severity and elevated levels of immune markers such as interleukin-1 receptor antagonist (IL-1RA), C-reactive protein (CRP) and C-C motif chemokine 2 (CCL2 or MCP-1). In contrast, the RNA-seq data mostly differentiated a cluster with low depression severity, enriched in brain related gene sets. This cluster was also distinguished by electrocardiography data, while structural imaging data revealed differences in ventricle volumes across the clusters. Incorporating predicted cell type proportions into the clustering resulted in three clusters, with one showing elevated immune marker concentrations. The cell type proportion and genes related to cell types were most pronounced in an intermediate depression symptoms cluster, suggesting that RNA-seq and immune markers measure different aspects of immune dysregulation. Lastly, we found a dysregulation of the SERPINF1/VEGF-A pathway that was specific to dendritic cells by integrating immune marker and RNA-seq data. This shows the advantages of combining different data modalities and highlights possible markers for further stratification research of depression symptoms.</p> <h1>Methods</h1> <p>The normalized and batch-corrected concentration of 43 immune markers from 237 subjects with stress-related mental disorders and 36 healthy controls was determined in plasma. This data was used in the initial analysis. Additionally, the same measurements are provided for 11 subjects with stress-related mental disorders used in a replication analysis.</p> <p>- blood was collected in the morning under fasted conditions and plasma stored at -80°C until further processing<br>- samples were randomized into 96 well plates<br>- immune marker concentration was measured with the Meso Scale Diagnostics V-PLEX Human Biomarker 54-Plex Kit and the MESO QuickPlex SQ 120 imager according to the manufacturer's instructions<br>- additionally, high-sensitivity C-reactive protein (Tecan Group Ltd.), cortisol (Tecan Group Ltd.), interleukin (IL)-6 (Thermo Fisher Scientific), IL-6 soluble receptor (Thermo Fisher Scientific) and IL-13 (Thermo Fisher Scientific) was measured via ELISA according to the manufacturer's instructions<br>- values below the detection limit in markers measured with ELISA were set to zero and values above the detection limit to the upper limit<br>- the data was quantile-normalized (values were ranked and mapped to the quantiles of a standard normal distribution)<br>- the normalized concentration was corrected for the biobank storage position (batch_variable) via a linear model and the residuals reported as the concentration</p> <p>The following markers were measured:<br>fibroblast growth factor 2 (FGF2 or bFGF), cortisol, C-C motif chemokine 11 (CCL11 or eotaxin), CCL26 (eotaxin-3), vascular endothelial growth factor receptor 1 (VEGFR1 or Flt-1), hsCRP, intercellular adhesion molecule (ICAM)-1, interferon (IFN)-gamma, IL-1alpha, IL-1 receptor antagonist (IL-1RA), IL-10, IL-12/IL-23p40, IL-12p70, IL-13, IL-15, IL-16, IL-17A, IL-17B, IL-2, IL-27, IL-31, IL-5, IL-6 high sensitivity (IL-6HS), IL-7, IL-8HS, C-X-C motif chemokine 10 (CXCL10 or IP-10), CCL2 (MCP-1), CCL13 (MCP-4), CCL22 (MDC), CCL3 (MIP-1alpha), CCL4 (MIP-1beta), placental growth factor (PlGF), serum amyloid A (SAA), sIL-6R, CCL17 (TARC), angiopoietin-1 receptor (Tie-2), tumor necrosis factor (TNF or TNF-alpha), lymphotoxin-alpha (LT-alpha or TNF-beta), thymic stromal lymphopoietin (TSLP), vascular cell adhesion protein 1 (VCAM-1), vascular endothelial growth factor (VEGF)-A-HS, VEGF-C, VEGF-D</p> <p>The data is provided as a tab separated file.</p>
Fig. 5. The Mantel test compares a in Application of allozyme markers for screening of turbot populations along Western Black Sea coast
Fig. 5. The Mantel test compares a genetic distance (Y matrix) with a geographical distance (X matrix) in kilometers to test correlation between genetics and geographical location.
Fig. 3 in Application of allozyme markers for screening of turbot populations along Western Black Sea coast
Fig. 3. Enzymograms of general unspecified esterases (EST) from muscle tissue of turbot (1) and haemoglobin (2), EST-2* and EST-3* - polymorphic loci, 0 – origin.
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.