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1,663 results for “BIAS”
Insights into transcriptional characteristics and homoeolog expression bias of embryo and endosperm in developing grain through mRNA-Seq and Iso-Seq
GEO Series GSE118474. Triticum aestivum. 12 samples. Type: Expression profiling by high throughput sequencing.
EGR2 biases the differentiation of liver infiltrating monocytes into hLAMs.
GEO Series GSE263970. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Male mice lacking Teshl lncRNA exhibit inactivation of Y chromosomal multicopy genes and female distortion-biased sex ratio change in offspring
GEO Series GSE162652. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
The female-biased factor VGLL3 drives cutaneous and systemic autoimmunity: RNA-seq analysis of the K5-Vgll3 transgenic mouse model of cutaneous and systemic lupus
GEO Series GSE128453. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
Loss of epigenetic modifications on the inactive X chromosome and sex-biased gene expression profiles in B cells from NZB/W F1 mice with lupus-like disease
GEO Series GSE140277. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Endogenous fluctuations of OCT4 and SOX2 bias pluripotent cell fate decisions
GEO Series GSE126554. Mus musculus. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Effect of performing SLAM-seq chemistry in methanol fixed cells versus standard tube processing on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE253370. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Sex bias in autoimmunity is driven by androgen regulation of T cell-intrinsic mechanisms
GEO Series GSE234134. Mus musculus. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE229506. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Sex-biased gene expression in Drosophila melanogaster larvae
GEO Series GSE31722. Drosophila melanogaster. 8 samples. Type: Expression profiling by array.
Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias and copy number variation
GEO Series GSE24546. Homo sapiens. 40 samples. Type: Methylation profiling by genome tiling array; Methylation profiling by high throughput sequencing; Genome variation profiling by SNP array.
Low-cost, low-bias and low-input RNA-seq with High Experimental Verifiability based on Semiconductor Sequencing
GEO Series GSE87660. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅳ
<p>A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region.</p> <p><strong>Note: For Wind in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (Matlab): Wind(Wind==2333)=nan;</strong></p> <p>More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.</p>
Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅲ
<p>A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region.</p> <p><strong>Note: For precipitation in historical periods, the value "2333" refers to no data. Set them to NaN before using, for example (in Matlab):<br> Pr(Pr==2333)=nan;</strong></p> <p>More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.</p>
A Multidimensional Dataset for Analyzing and Detecting News Bias based on Crowdsourcing
<p>We provide a large data set consisting of <strong>2,057 sentences</strong> from 90 news articles and annotations of crowdworkers with respect to <strong>bias itself</strong> and the following <strong>bias dimensions</strong>:</p> <ol> <li><strong>hidden assumptions</strong></li> <li><strong>subjectivity</strong></li> <li><strong>representation tendencies</strong></li> </ol> <p>Our data set contains <strong>44,547 labels in total</strong> (43,197 sentence labels and 1,350 article labels).</p> <p>The news articles deal with the <strong>Ukraine crisis</strong>. They were published in 33 countries in total and were selected based on the data set of Cremisini et al. (Cremisini, A., Aguilar, D., & Finlayson, M. A. <em>A Challenging Dataset for Bias Detection: The Case of the Crisis in the Ukraine</em>, Proc. of SBP-BRiMS'19, pp. 173-183, 2019).</p> <p>Each sentence was annotated by 5 crowdworkers. In total, we spent $ 3,335 for the crowdworkers annotations.</p> <p>More information can be found in our <a href="https://github.com/michaelfaerber/ukraine-news-bias">GitHub repository</a>. A description of the used file format is given in the codebook attached to the dataset.</p> <p>Please cite our data set as follows:</p> <pre><code>@unpublished{Faerber2020Bias, author = {Michael F{\"{a}}rber and Victoria Burkard and Adam Jatowt and Sora Lim}, title = {{A Multidimensional Dataset for Analyzing and Detecting News Bias based on Crowdsourcing}}, year = {2020} }</code></pre>
Signal, bias, and the role of transcriptome assembly quality in phylogenomic inference
<p>Transcriptome assemblies of liver RNA-seq from 38 craniate taxa. Each taxon has two assemblies from the same read sets, one of high quality and one of low-quality according to overall TransRate score.</p>
Aquaplanet experiment data for Webb, M. J., & Lock, A. P. (2020). Testing a physical hypothesis for the relationship between climate sen-sitivity and double-ITCZ bias in climate models.Journal of Advances in Modeling Earth Systems, 12,e2019MS001999.https://doi.org/10.1029/2019MS001999
<p><strong>Aquaplanet experiment data from Webb and Lock (2020)</strong></p> <p><br> Webb, M. J., & Lock, A. P. (2020). Testing a physical hypothesis for the relationship between climate sen-sitivity and double-ITCZ bias in climate models.Journal of Advances in Modeling Earth Systems, 12,e2019MS001999.https://doi.org/10.1029/2019MS001999</p> <p>CSV files containing data from Figs 1(b) and 2(a-d)</p> <p>Figure 2b:</p> <p>APEQ.Precipitation_mmperday.zonal.csv<br> APEQ_2LW_Cloud.Precipitation_mmperday.zonal.csv<br> APEQ_3LW_Cloud.Precipitation_mmperday.zonal.csv</p> <p>Figure 3a:</p> <p>APEQ.w700.zonal.csv<br> APEQ_3LW_Cloud.w700.zonal.csv<br> APEQ_2LW_Cloud.w700.zonal.csv</p> <p>Figure 3b:</p> <p>APEQ.Estimated_Inversion_Strength_K.zonal.csv<br> APEQ_2LW_Cloud.Estimated_Inversion_Strength_K.zonal.csv<br> APEQ_3LW_Cloud.Estimated_Inversion_Strength_K.zonal.csv</p> <p>Figure 3c:</p> <p>APEQ.Net_CRE_Wperm2.zonal.csv<br> APEQ_2LW_Cloud.Net_CRE_Wperm2.zonal.csv<br> APEQ_3LW_Cloud.Net_CRE_Wperm2.zonal.csv</p> <p>Figure 3d:</p> <p>APEQ4K-APEQ.Net_CRE_Feedback_Wperm2perK.zonal.csv<br> APEQ4K_2LW_Cloud-APEQ_2LW_Cloud.Net_CRE_Feedback_Wperm2perK.zonal.csv<br> APEQ4K_3LW_Cloud-APEQ_3LW_Cloud.Net_CRE_Feedback_Wperm2perK.zonal.csv</p> <p>Any queries please contact Mark Webb mark.webb@metoffice.gov.uk</p> <p> </p>
Gender-biased nectar targets different behavioural traits of flower visitors
<p>This dataset contains data used in the analyses performed in the article entitled "Gender-biased nectar targets different behavioural traits of flower visitors". The Excel file contains five sheets.</p> <p>1_‘Behavioural observations’ contains taxa, sex, number of visited flowers, duration of visits and reward sought of each insect visiting <em>Echium vulgare </em>flowers during behavioural observations.</p> <p>2_‘Insect checklist’ contains the list of all taxa recorded visiting the flowers.</p> <p>3_‘Patches’ contains the description of the fixed plant patches where flower visitor observations were performed.</p> <p>4_‘Nectar quality’ contains volume and concentration of sugars and amino acids measured in several nectar sample of <em>Echium vulgare</em>, belonging to three different flower stages.</p> <p>5_‘Nectar aminoacid diversity’ contains the concentration of specific amino acids found in nectar samples of two flower stages.</p>
Data from: Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias in outlier detection
Identifying local adaptation is crucial in conservation biology in order to define ecotypes and establish management guidelines. Local adaptation is often inferred from the detection of loci showing a high differentiation between populations, the so-called FST outliers. Methods of detection of loci under selection are reputed to be robust in most spatial population models. However, using simulations we showed that FST outlier tests provided a high rate of false positives (up to 60%) in fractal environments such as river networks. Surprisingly, the number of sampled demes was correlated with parameters of population genetic structure, such as the variance of FSTs, and hence strongly influenced the rate of outliers. This unappreciated property of river networks therefore needs to be accounted for in genetic studies on adaptation and conservation of river organisms.
Data from: The effect of DNA degradation bias in passive sampling devices on metabarcoding studies of arthropod communities and their associated microbiota
PCR amplification bias is a well-known problem in metagenomic analysis of arthropod communities. In contrast, variation of DNA degradation rates is a largely neglected source of bias. Differential degradation of DNA molecules could cause underrepresentation of taxa in a community sequencing sample. Arthropods are often collected by passive sampling devices, like malaise traps. Specimens in such a trap are exposed to varying periods of suboptimal storage and possibly different rates of DNA degradation. Degradation bias could thus be a significant issue, skewing diversity estimates. Here, we estimate the effect of differential DNA degradation on the recovery of community diversity of Hawaiian arthropods and their associated microbiota. We use a simple DNA size selection protocol to test for degradation bias in mock communities, as well as passively collected samples from actual Malaise traps. We compare the effect of DNA degradation to that of varying PCR conditions, including primer choice, annealing temperature and cycle number. Our results show that DNA degradation does indeed bias community analyses. However, the effect of this bias is of minor importance compared to that induced by changes in PCR conditions. Analyses of the macro and microbiome from passively collected arthropod samples are thus well worth pursuing.
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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.