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2,129 results for “scores”
Supplemental data for: Development and validation of a polygenic risk score for stroke in the Chinese population
<div class="WordSection1"> <div class="WordSection1"> <strong>Objective</strong>: To construct a polygenic risk score (PRS) for stroke and evaluate its utility in risk stratification and primary prevention for stroke.</div> <div class="WordSection1"> </div> <div class="WordSection1"> <strong>Methods</strong>: Using meta-analytic approach and large genome-wide association results for stroke and stroke-related traits in East Asians, we generated a combined PRS (metaPRS) by incorporating 534 genetic variants in a training set of 2,872 patients with stroke and 2,494 controls. We then validated its association with incident stroke using Cox regression models in large Chinese population-based prospective cohorts comprising 41,006 individuals.</div> <div class="WordSection1"> </div> <div class="WordSection1"> <strong>Results</strong>: During a total of 367,750 person-years (mean follow-up 9.0 years), 1,227 participants developed stroke before age of 80 years. Individuals with high polygenic risk had an about 2-fold higher risk of incident stroke compared with those with low polygenic risk (HR: 1.99, 95% CI: 1.66-2.38), with the lifetime risk of stroke being 25.2% (95% CI: 22.5%-27.7%) and 13.6% (95% CI: 11.6%-15.5%), respectively. Individuals with both high polygenic risk and family history displayed the lifetime risk as high as 41.1% (95% CI: 31.4%-49.5%). Moreover, individuals with high polygenic risk achieved greater benefits in terms of absolute risk reductions from adherence to ideal fasting blood glucose and total cholesterol than those with low polygenic risk. Maintaining favorable cardiovascular health (CVH) profile could substantially mitigate the increased risk conferred by high polygenic risk to the level of the low polygenic risk (from 34.6 % to 13.2%).</div> <div class="WordSection1"> </div> <div class="WordSection1"> <strong>Conclusions</strong>: Our metaPRS has great potential for risk stratification of stroke and identification of individuals who may benefit more from maintaining ideal CVH. </div> <div class="WordSection1"> </div> <div class="WordSection1"> <strong>Classification of Evidence</strong>: This study provides Class I evidence that a meta-polygenic risk score is predictive of stroke risk.</div> <p> </p> </div>
Dataset - No Reference Image Quality assessment Scores for Humanities Online Repositories
<p>The dataset contains data on No-Reference Image Quality Assessment (NR-IQA) scores for online repositories in the humanities.</p>
SCORE output data
<p>This repository is linked to the following article:</p> <ul> <li>Schaber, T., Ekholm, T., Merikanto, J. <em>et al.</em> Prudent carbon dioxide removal strategies hedge against high climate sensitivity. <em>Commun Earth Environ</em> <strong>5</strong>, 285 (2024). https://doi.org/10.1038/s43247-024-01456-x</li> </ul> <p>This repository includes the data underlying the analysis in the manuscript.</p>
Docking scores
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Allele scores and frequencies of 66 microsatellite locus loci in Solenopsis geminata
<p>Allele scores and frequencies of 66 microsatellite loci in <em>Solenopsis geminata</em> samples were analyzed from 18 populations and 131 individuals.</p> <p>Eighteen populations were collected from South Korea, Laos, Myanmar, Thailand, and the United States.</p>
PPR score of all STRING genes to canonical pathways
<p>PPR score of all genes in the STRING network (edge score>0.7) to canonical pathways.</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>
(simulated Data:) Detecting interactions in high dimensional data using Cross Leverage Scores
<p>We upload the data according to the paper "Detecting interactions in high dimensional data using Cross Leverage Scores" (Teschke et al., 2024) which we submitted at the Biometrical Journal. The data is also being uploaded on behalf of the paper's co-authors, Katja Ickstadt and Alexander Munteanu.</p> <p>Furthermore we upload some Intermediate results, because calculations takes very long time and need lots of memory. You can therefore use them for further insights.</p> <p>For details of the simulation, we refer to Teschke et al. (2024).</p>
Supplementary material 4 from: Hagen BL, Kumschick S (2018) The relevance of using various scoring schemes revealed by an impact assessment of feral mammals. NeoBiota 38: 37-75. https://doi.org/10.3897/neobiota.38.23509
Detailed SEICAT assessments (Table S4) : Explanation note: A summary of the impact assessment using the Socio-Economic Impact Classification for Alien Taxa (SEICAT). Impact scores, from highest to lowest are Massive (MV), Major (MR), Moderate (MO), Minor (MN) and Minimal Concern (MC). Full reference details are given in Appendix 2. Region indicates whether the impact was found on islands or the mainland.
Supplementary material 2 from: Hagen BL, Kumschick S (2018) The relevance of using various scoring schemes revealed by an impact assessment of feral mammals. NeoBiota 38: 37-75. https://doi.org/10.3897/neobiota.38.23509
Detailed GISS assessments (Table S2) : Explanation note: Details of the environmental and socio-economic impact assessment using the Generic Impact Scoring System (GISS). Full reference details are given in Appendix 2. Region indicates whether the impact was found on islands or the mainland.
Supplementary material 1 from: Hagen BL, Kumschick S (2018) The relevance of using various scoring schemes revealed by an impact assessment of feral mammals. NeoBiota 38: 37-75. https://doi.org/10.3897/neobiota.38.23509
Differences between scoring schemes (Table S1) : Explanation note: Scoring differences for GISS, EICAT and SEICAT. This table was adapted from Kumschick et al. (2016) and Bacher et al. (2017). The numbers in the top column refer to the GISS scoring classifications, whereas the terms 'massive' to 'minimal concern' refer to EICAT and SEICAT scoring classifications.
Supplementary material 3 from: Hagen BL, Kumschick S (2018) The relevance of using various scoring schemes revealed by an impact assessment of feral mammals. NeoBiota 38: 37-75. https://doi.org/10.3897/neobiota.38.23509
Detailed EICAT assessments (Table S3) : Explanation note: A summary of the impact assessment using the Environmental Impact Classification for Alien Taxa (EICAT). Impact scores, from highest to lowest are Massive (MV), Major (MR), Moderate (MO), Minor (MN) and Minimal Concern (MC). Full reference details are given in Appendix 2. Region indicates whether the impact was found on islands or the mainland.
Supplementary material 2 from: Yazlık A, Pergl J, Pyšek P (2018) Impact of alien plants in Turkey assessed by the Generic Impact Scoring System. NeoBiota 39: 31-51. https://doi.org/10.3897/neobiota.39.23598
List of references : Explanation note: List of references used for scoring the impact of the studied species.
Supplementary material 1 from: Yazlık A, Pergl J, Pyšek P (2018) Impact of alien plants in Turkey assessed by the Generic Impact Scoring System. NeoBiota 39: 31-51. https://doi.org/10.3897/neobiota.39.23598
Distribution of alien species assessed in this study : Explanation note: Distribution in Turkey of the alien species studied using the grid system according to Davis (1965–1985, 1988).
Supplementary material 3 from: Yazlık A, Pergl J, Pyšek P (2018) Impact of alien plants in Turkey assessed by the Generic Impact Scoring System. NeoBiota 39: 31-51. https://doi.org/10.3897/neobiota.39.23598
Scoring of the impact : Explanation note: Scoring of environmental and socioeconomi impact. File contains values (Impact score) and categories in which these scores are assigned (Impact type), with source references.
Plant scoring trial: U.Nottm_2018_RIPR_leaf_nitrate_concentration
This study makes use of the Renewable Industrial Products from Rapeseed (RIPR) diversity population of inbred lines of Brassica napus genotypes Thomas et al., 2016. BMC Plant Biology 16, 214). A subset of 383 genotypes were selected, comprising 169 winter-, 123 spring-, and 11 semiwinter-oilseed rape (OSR), 27 swede, six fodder, three kale and 44 of unspecified growth types. All plant growth took place at the Sutton Bonington Campus of the University of Nottingham (52°49'58.9"N, 1°14'59.2"W) in compost in a designed experiment in a polytunnel Leaves were sampled from all plants at the rosette stage (typically 6-8 true leaves showing) approximately four months after sowing. Typically three leaves were taken from each plant and freeze dried for 48-60 hours. Leaves were then homogenised in liquid N2 using a pestle and mortar and stored at -80°C prior to analyses. Leaf NO3- concentration was measured by ion chromatography (IC). This work was supported by the Biotechnology and Biological Sciences Research Council [grant number BB/L002124/1], (BBSRC, United Kingdom), Renewable Industrial Products from Rapeseed (RIPR) Programme to Ian Bancroft.
HSPS_KOREAN_cut-off-scores
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Top 100 artigos com maior score altmétrico que disponibilizam os seus conjuntos de dados
<p>Dados brutos disponíveis em: https://altmetric.figshare.com/articles/dataset/Re-imagining_the_top_100_-_Top_100_2021_Feat_Subjects_/17075036?_gl=1*bqpucx*_ga*MjA1NjIwNDA1Ny4xNzA4NTQ1NTE3*_ga_CHDNWH4YDX*MTcyNDE3Mzk4Mi4xMy4wLjE3MjQxNzM5ODIuMC4wLjA.&file=31569431</p>
Dataset for paper: Prognostic Stratification by the Meet-URO Score in Real-World Older Patients With Metastatic Renal Cell Carcinoma (mRCC) Receiving Cabozantinib: A Subanalysis of the Prospective ZEBRA Study (Meet-URO 9)
<p>Dataset for paper: Prognostic Stratification by the Meet-URO Score in Real-World Older Patients With Metastatic Renal Cell Carcinoma (mRCC) Receiving Cabozantinib: A Subanalysis of the Prospective ZEBRA Study (Meet-URO 9)</p>
Clickbait scores of links from worldwide news websites 2016-2023
<p>This .7z file contains an SQLite DB with 451 million clickbait scores produced by a clickbait detector for links from a sample of news sites from the common crawl. Note that the scores were assigned by a program which does not perform at 100% accuracy all the time - some error is present.</p> <p>Columns are: id number, date, clickbait score (1.0 being likely to be clickbait).</p> <p>Note this does NOT include any hyperlink text or clickbait detector feature scores.</p>
ScienceDex guides
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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.