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1,663 results for “BIAS”
Risk of bias assessments for the Cochrane review 'SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19'
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19.</p>
Dataset for "On Closure Phase and Systematic Bias in Multilooked SAR Interferometry"
<ul> <li>Datasets of the Barstow-Bristol Trough area -- unwrapped interferograms of con-1 through con-10, and con-20 and their associated correlation, connected components.</li> <li>Jupyter notebook tutorial can be found in https://github.com/insarlab/MintPy-tutorial/tree/main/applications</li> </ul>
Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: Janus kinase inhibitors for the treatment of COVID-19
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: Janus kinase inhibitors for the treatment of COVID-19.</p>
Risk of bias assessments for version 5 of the Cochrane review 'Convalescent plasma for people with COVID-19'
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Living Systematic Review: Convalescent plasma for people with COVID-19 (Version 5). </p>
Understanding Sampling Bias in the Global Heat Flow Compilation
<p>Geothermal heat flow measurements, including calculated weights and geological, tectonic and topographic settings.</p> <p>Paper in review (July 14th, 2022)</p>
Seasonal but not sex-biased gene expression of the carotenoid ketolase, CYP2J19, in the sexually dichromatic southern red bishop (Euplectes orix)
<p>Intense red colors in birds are often due to ketocarotenoids (KCs). In many land birds, KCs are oxidized from dietary yellow precursors, presumably by the avian carotenoid ketolase CYP2J19, the regulation and constraints of which have important implications for condition-dependence and honest signaling of carotenoid color displays. Here we investigate hepatic CYP2J19 gene expression in the seasonally and sexually dichromatic southern red bishop (Euplectes orix) in relation to season, sex, progression of the prenuptial moult, testis size, body condition, reflectance-based redness (hue), and circulating sex steroids. A coloration function of CYP2J19 is supported by seasonal upregulation prior to and during the carotenoid-depositing stage of the male prenuptial moult. However, upregulation was similar in females (which do not moult prenuptially), and remained high in males after moult, suggesting additional or alternative functions of hepatic CYP2J19 or its products, such as detoxification or antioxidants, respectively. In males, the CYP2J19 upregulation preceded and was unrelated to the rise in plasma testosterone, but was correlated with androstenedione, likely of adrenal origin and compatible with luteinizing hormone-induced and (in females) estrogen-suppressed moult. Finally, contrary to ideas that carotenoid ketolation rate mediates honest signaling, CYP2J19 expression was not related to male body condition or plumage redness.</p>
Vibrio cholerae codon biased genes list
<p>Files called top25: For each codon, 25% of genes with highest differential codon usage are listed. </p> <p>Files called top: For each codon, top genes with highest differential codon usage are listed, as indicated by violin plots in pdf files. </p> <p>Excel sheet with assigned codon usage for each codon and each gene.</p> <p>Whole genome of Vibrio cholerae N16961</p>
Molecular dynamics trajectories obtained from simulations of mechanically-controlled break-junctions and associated zero-bias conductance.
<p>This data set contains structural information and the associated zero-bias conductance of mechanically-controlled break-junction experiments. It contains:</p> <ul> <li>Six (multi) xyz files (trajectory_0X.xyz), which contain different trajectories produced by molecular dynamic simulations (using <a href="https://www.lammps.org/">LAMMPS</a> and <a href="https://docs.lammps.org/Packages_details.html#pkg-reaxff">reactive force fields</a>) of a mechanically-controlled break-junction. These simulations start from a gold wire with attached molecules. One side of the wire is slowly pulled away, until the gold wire is broken apart and a molecular junction is formed. The outermost six layers of the goldwire are frozen in the simulation. The temperature of the simulation was set to 300K.</li> <li>Six files (transmission_0X.dat) with the calculated zero-bias conductance (G/G<sub>0</sub>). Each entry corresponds to the zero-bias conductance of the corresponding structure from the xyz files. The zero-bias conductance was calculated using non-scc DFTB+, as, e.g., described <a href="https://dftbplus-recipes.readthedocs.io/en/latest/transport/carbon2d-trans.html">here</a>.</li> </ul> <p>For more information see dx.doi.org/XXXXXXX.</p>
Developmental bias in the evolution and plasticity of beetle horn shape
<p>The degree to which developmental systems bias the phenotypic effects of environmental and genetic variation, and how these biases affect evolution, is subject to much debate. Here, we assess whether developmental variability in horn shape aligns with the phenotypic effects of plasticity and evolutionary divergence, yielding three salient results. First, we find that most pathways previously shown to regulate horn length also affect shape. Second, we find that the phenotypic effects of manipulating divergent developmental pathways are correlated with each other as well as multivariate fluctuating asymmetry – a measure of developmental variability. Third, these effects further aligned with thermal plasticity, population differences, and macroevolutionary divergence between sister taxa and more distantly related species. Collectively, our results support the hypothesis that changes in horn shape —whether brought about by environmentally plastic responses, functional manipulations, or evolutionary divergences— converge along 'developmental lines of least resistance', i.e., are biased by the developmental system underpinning horn shape.</p>
Spontaneous biases enhance generalisation in the neonate brain
<p>data paper "<span>Spontaneous biases enhance generalisation in the neonate brain" by Shuge Wang, Vera Vasas, Laura Freeland, Daniel C. Osorio, Versace<br></span></p>
Data from: Female-biased population sex ratios caused by genetic rather than ecological mechanisms in dwarf willow (Salix herbacea L.)
<p>Biased sex ratios among reproductive individuals are common in plants, but the underlying mechanisms, as well as the evolutionary consequences, are not well understood. The classical theory of Düsing and Fisher predicts an equal primary sex ratio at seed production, based on the selective advantage of the rare sex. Biased sex ratios among reproductive plants can arise from sexual dimorphism in survival and flowering. Sex ratio biases can also be present from the seed stage; in these cases, assumptions of Düsing's and Fisher's theory, for example, random mating or demographic equilibrium, are thought to be violated.</p> <p>We investigated mechanisms leading to female-biased sex ratios in the arctic-alpine dwarf willow <em>Salix herbacea</em> L. We studied sex ratios in three natural populations over three years as well as in 29 crosses (full-sib families) under controlled conditions over four growth periods. We tested whether sex ratio was associated with habitat parameters (elevation and snowmelt time), or with germination, survival or flowering, and whether females and males differed in size or flowering that may cause observation bias.</p> <p>We detected a strong and consistent female bias, both in natural populations (sex ratio [proportion of females]: 0.71-0.82) and in our controlled experiment (overall sex ratio: 0.70-0-72). Female bias became more pronounced with increasing elevation. Our data did not support sexual dimorphism in size or flowering. Family sex ratios varied largely (from 0.25 to 1), including many female-biased families, unbiased families and two male-biased families. Families with lower germination, seedling establishment, survival or flowering did not have stronger female bias, indicating that intrinsically higher survival or flowering in females does not explain overall female bias. </p> <p>Synthesis: Our results suggest that sex ratio bias in <em>S. herbacea</em> is already present in seeds and does not arise through intrinsic differences between sexes. Candidate mechanisms that can lead to both overall female bias and variation in sex ratio among families are meiotic drive or cyto-nuclear interactions. The pioneer habit of <em>Salix</em> may lead to non-equilibrium population dynamics that allow for the long-term persistence of variable genetic sex ratio distortion systems that arise from genetic conflict.</p>
Supplementary to "Quantifying the wind-induced bias of rainfall measurements for the Thies optical disdrometer"
<p>Supplementary material for the paper "Quantifying the wind-induced bias of rainfall measurements for the Thies optical disdrometer" submitted to the journal Water Resources Research</p>
BD Behavioral biases and personal indebtedness
<p>Research database: "Behavioral biases and personal indebtedness: a systematic literature review"</p>
Figure 3 in Addressing biases in replacement series: the importance of reference density selection for interpretation of competition outcomes
Figure 3. Aboveground biomass (g m−2) across densities (plants m−2) for maize and Setorio foberi. Vertical arrows indicate the maize (black numbers) and S. foberi (gray numbers) densities at which S. foberi reaches inflection point and 90% of maximum biomass. Horizontal arrows indicate S. foberi biomass at inflection point and 90% of maximum biomass.
Figure 4 in Addressing biases in replacement series: the importance of reference density selection for interpretation of competition outcomes
Figure 4. Relative biomass of Amoronthus hybridus:maize replacement series from experiment 1 (left) and experiment 2 (right) with densities based in inflection point (A and B), maximum biomass (C and D), and equal N uptake (E and F). Black circles represent maize relative biomass,white circles represent A. hybridus relative biomass,and gray diamonds represent relative yield total biomass (RYT). Dotted line represents a relative biomass of 1 for all the proportions. The points and error bars represent data means and standard errors.
Figure 2 in Addressing biases in replacement series: the importance of reference density selection for interpretation of competition outcomes
Figure 2. Aboveground biomass (g m−2) across densities (plants m−2) for maize and Amoronthus hybridus. Vertical arrows indicate the maize (black numbers) and A. hybridus (gray numbers) densities at which A. hybridus reaches inflection point and 90% of maximum biomass. Horizontal arrows indicate A. hybridus biomass at the inflection point and 90% of maximum biomass.
Figure 1 in Addressing biases in replacement series: the importance of reference density selection for interpretation of competition outcomes
Figure 1. Theoretical relationship between relative biomass and plant density ratios of (A) two species of the same size and (B) two species with species 1 being larger than species 2. Dashed lines represent the regression lines for both species, and solid lines represent theoretical line of parity (1:1) between species.
Figure 5 in Addressing biases in replacement series: the importance of reference density selection for interpretation of competition outcomes
Figure 5. Relative biomass of Setorio foberi:maize replacement series from experiment 1 (left) and experiment 2 (right) with densities based in inflection point (A and B), maximum biomass (C and D), and equal N uptake (E and F). Black circles represent maize relative biomass, white circles represent S. foberi relative biomass, and gray diamonds represent relative yield total biomass (RYT). Dotted line represents a relative biomass of 1 for all the proportions. The points and error bars represent data means and standard errors.
Data for 'Accounting for digestion enzyme bias in Casanovo' (Melendez et al., 2024)
<p>This upload contains two archives and an explanatory README.md that accompany <a href="https://doi.org/10.1101/2024.05.16.594602">Accounting for digestion enzyme bias in Casanovo (Melendez et al., 2024)</a>. The archive named 'mgf_data' contains all of the mgf files used in the paper. The archive named 'mztab_data' contains mztab formatted sequencing (and enzyme classification) predictions from all models trained in the paper. The README file describes the structure of each archive, the contents of each mgf and mztab file, and the sections of the paper that each mgf or mztab file relates to.</p>
carjgil/teacher-bias: Teacher Bias - Replication Package
<p>*Project: Teacher's Bias in Assessments</p> <p>*Code: Replication of data cleaning and preparation and analyses</p> <p>*Authors: Carlos J. Gil-Hernández, Irene Pañeda-Fernández, Leire Salazar, and Jonatan Castaño-Muñoz</p> <p>*Last Update: 04/07/2024</p> <p>*Software: STATA/MP 17</p> <p>Here you can find the replication dofile in STATA format in the "code" folder and the raw and working datasets (including the codebook) of the teacher's bias in assessment experiment in the "data" folder:</p> <p>1. "/replication files/code/datacleaning.do" contains all the data cleaning and preparation procedures from the raw anonymized Qualtrics data where we applied the survey experiment (see "data" folder .dta or .csv files named "raw_dataset_anonymized") to set a working dataset ready to be analyzed.</p> <p>2. The folder "/replication files/data" contains the data files named "raw_dataset_anonymized" and "cleandataset" in .dta (data/STATA) or .csv (data/CSV) format on the raw and working data, respectively, to replicate the findings of the teacher's bias in assessments project or run your own analyses. If you do not have access to STATA software, you can check the variables labels of the "cleandataset" in the "data/codebook_cleandataset" Excel file.</p> <blockquote> <p>Data Citation: Gil-Hernández, Carlos J., Leire Salazar, Jonatan Castaño Muñoz, and Irene Pañeda-Fernandez. 2023. "Teacher's Bias Dataset: A Factorial Survey Experiment." European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/f14f5209-f032-4218-a89a-4643143809af</p> </blockquote> <p>3. "datanalysis.do" reproduces all the tables and figures presented in the article and online appendix (if you want to reproduce the analyses from the pre-test pilot data, please get in contact with the corresponding author) using the data file named "cleandataset" in the "data" folder (in .dta or .csv format). The output from "datanalysis.do" will be printed in the "/replication files/output" subfolders for tables (main or appendix) or figures (main or appendix).</p>
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.