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14,965 results for “evolution”
Research data for "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy"
<p>This is the dataset supporting the publication "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy", published by the authors in Electrochimica Acta (2024), 144626 under <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.electacta.2024.144626" target="_blank" rel="noreferrer noopener">doi.org/10.1016/j.electacta.2024.144626</a>.</p> <p>The data is ordered according to Figure numbers in the main manuscript and the electronic supplementary information.</p>
SOTorrent: Reconstructing and Analyzing the Evolution of Stack Overflow Posts — Supplementary Material
<p>Stack Overflow is the most popular question-and-answer website for software developers, providing a large amount of code snippets and free-form text on a wide variety of topics. Like other software artifacts, questions and answers on Stack Overflow evolve over time, for example when bugs in code snippets are fixed, code is updated to work with a more recent library version, or text surrounding a code snippet is edited for clarity. To be able to analyze how content on Stack Overflow evolves, we built <em>SOTorrent</em>, an open dataset based on the official Stack Exchange data dump. <em>SOTorrent </em>provides access to the version history of Stack Overflow content at the level of whole posts and individual text or code blocks.</p> <p>This dataset has been retrieved from <em>SOTorrent </em>using the following scripts:</p> <p><a href="https://doi.org/10.5281/zenodo.1201679">https://doi.org/10.5281/zenodo.1201679</a></p> <p>For the MSR 2018 paper about SOTorrent, we used the following scripts to analyze the data:</p> <p><a href="https://doi.org/10.5281/zenodo.1201706">https://doi.org/10.5281/zenodo.1201706</a></p> <p>The files <em>sample_before_10.ods</em> and <em>sample_after_10.ods</em> contain our qualitative analysis of 50 comments that were made up to 10 minutes before/after an edit.</p>
Science ready spectra of star clusters and their best-fitting models described in the research paper "Using Star Clusters as Tracers of Star Formation and Chemical Evolution: the Chemical Enrichment History of the Large Magellanic Cloud" by Chilingarian & Asa'd
<p>Science ready spectra of star clusters in the Large Magellanic Cloud and their best-fitting templates (alpha-enhanced MILES based simple stellar population models) obtained using the NBursts full spectrum fitting code. Each spectrum is presented as a binary FITS table, which contains a spectrum (wavelength, flux, uncertainties), best-fitting template, best-fitting parameters (radial velocity, age, metallicity), and a pixel mask used in the fitting procedure. For each cluster, 5 spectra are provided, which correspond to [alpha/Fe] values from 0.0 to 0.4 dex with a step of 0.1 dex. The only exception is NGC2249, for which only 3 models are provided. The alpha-enhancement value of a model grid used in the fitting procedure is given in the FITS keyword MGFEGRID.</p>
Supplementary data and scripts for Willemsen and Bravo 2019 "Origin and evolution of papillomavirus (onco)genes and genomes"
<p>Supplementary data for Willemsen and Bravo 2019 "Origin and evolution of papillomavirus (onco)genes and genomes". The data set consists of two folders: “Bali-Phy” and “RandomPermutationTests”. The “Bali-Phy” folder contains the final results and convergence diagnostics of the Common Ancestry tests obtained by using the Bali-Phy software. The “RandomPermutationTests” folder contains all the data and scripts to repeat the random permutation tests described in the manuscript. Please see the corresponding README files for more information.</p>
Evolution of FDA Guidelines on Control of Nitrosamine Impurities in Human Drugs – A Comparative Analysis of September 2024 Revisions
<p>Nitrosamine impurities have become a significant concern in the pharmaceutical industry due to their carcinogenic potential. In response, the U.S. Food and Drug Administration (FDA) has continuously updated its guidelines to ensure the safety and efficacy of drug products. This review article provides a comprehensive analysis of the evolution of FDA guidelines on the control of nitrosamine impurities, with a particular focus on the September 2024 revisions. By comparing the latest guidance with previous versions, this article highlights key changes, including the expanded focus on Nitrosamine Drug Substance-Related Impurities (NDSRIs), updated risk assessment strategies, and the introduction of new Acceptable Intake (AI) limits. The analysis underscores the FDA's commitment to enhancing drug safety through rigorous control measures and global harmonization efforts.</p>
Dataset for the publication "Superconducting gravimeter observations show that satellite-derived snow depth image improves the simulation of the snow water equivalent evolution in a high alpine site"
<p>This datasset contains data to reproduce the following figures of the paper <em>Superconducting gravimeter observations show that satellite-derived snow depth image improves the simulation of the snow water equivalent evolution in a high alpine site</em>:</p> <ul> <li> <p>Time series data of Figures 1c and 2</p> </li> <li> <p>Data (*.asc) used for plotting Figures 1d and 1e (as well as Figure S3 and S4)</p> </li> <li>Pléiades snow depth map (Figure S1)</li> <li> <p>Data used for plotting Figure S2</p> </li> </ul> <p> </p>
Stellar Evolution Models from "Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST"
<p>These data consist of all runs from the Modules for Experiments in Stellar Astrophysics (MESA; Paxton et al. 2011, 2013, 2015, 2018, 2019) code, used to construct radius priors for modeling supernova precursor emission in<em> <a href="https://arxiv.org/abs/2408.13314">Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST</a></em> (Gagliano+2024, submitted). </p> <p>The contents of the data files are detailed in the file <strong>ReadmeMESA.txt</strong>. Additional detail concerning the simulations can be found in Section 2.2 of the linked publication. </p>
PhasAGE Training School 1 -Overview of bioinformatics tools for the life sciences & Classification and evolution of non-globular proteins- LECTUREs
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
Evolution of the recombination regulator PRDM9 in minke whales
<p>This data repository contains data and protocols for the manuscript: Evolution of the recombination regulator PRDM9 in minke whales</p>
Dataset from the paper: "RR Lyrae From Binary Evolution: Abundant, Young and Metal-Rich"
<p>The two files contain the Tables presented in Appendix B of Bobrick & Iorio et al. (2024, MNRAS, 527, 12196–12218)<br>(https://ui.adsabs.harvard.edu/abs/2024MNRAS.52712196B/abstract) in CSV format.</p> <p># V3 updates</p> <p>- New columns added: GRRL, Gcomp, RRRL, Rcomp, and Teffcomp. These columns are not included in the published paper tables.<br>- The columns G and BP_RP were previously described as the Gaia G magnitude of the RRL, but they actually represent the G magnitude and BP–RP color of the entire system.<br>- The previous description of the columns was missing the PorbRRL entry.<br>- A new file, TableB2_SingleMadeBinaryRRL_V3.csv, has been added to replace the previous version, which had mismatched columns and some empty fields.<br>- The README now reports the format for both tables.</p> <p># Tables</p> <p>There are two tables included:</p> <p>## TableB1_BinaryMadeRRL_V3.csv</p> <p>This table contains the systems reported in Table B1 of the paper, with additional columns (marked with a +).</p> <p>### Columns:</p> <p>- **Age**: Age of the system since the zero-age main sequence [Myr]<br>- **GBin**: Galactic bin from the Galactic model (Table 1 in the paper)<br> - TD1: Thin Disc – Bin 1 <br> - TD2: Thin Disc – Bin 2 <br> - TD3: Thin Disc – Bin 3 <br> - TD4: Thin Disc – Bin 4 <br> - TD5: Thin Disc – Bin 5 <br> - TD6: Thin Disc – Bin 6 <br> - TD7: Thin Disc – Bin 7 <br> - B: Bulge <br> - TKD: Thick Disc <br> - H: Halo <br>- **Mproj**: Progenitor ZAMS mass of the RRL [Msun]<br>- **Mcomp**: Progenitor ZAMS mass of the RRL companion [Msun]<br>- **Porb_init**: Initial orbital period [days]<br>- **feh**: [Fe/H] metallicity<br>- **MRRL**: RRL mass [Msun]<br>- **McompRRL**: Mass of the RRL companion [Msun]<br>- **PorbRRL**: Current orbital period [days]<br>- **McRRL**: Core mass of the RRL [Msun]<br>- **LRRL**: Bolometric luminosity of the RRL [Lsun]<br>- **Teff**: Effective temperature of the RRL [K]<br>- **G**: Gaia G-band magnitude of the system as a whole [mag]<br>- **BP_RP**: Gaia BP–RP color of the system as a whole [mag]<br>- **GRRL**: Gaia G-band magnitude of the RRL [mag] +<br>- **Gcomp**: Gaia G-band magnitude of the companion [mag] +<br>- **RRRL**: Radius of the RRL [Rsun] +<br>- **Rcomp**: Radius of the companion [Rsun] +<br>- **Teffcomp**: Effective temperature of the companion [K] +</p> <p>---</p> <p>## TableB2_SingleMadeBinaryRRL_V3.csv</p> <p>This table contains the systems reported in Table B2 of the paper, with additional columns (marked with a +).</p> <p>### Columns:</p> <p>- **Age**: Age of the system since the zero-age main sequence [Myr]<br>- **GBin**: Galactic bin from the Galactic model (Table 1 in the paper)<br> - TD1: Thin Disc – Bin 1 <br> - TD2: Thin Disc – Bin 2 <br> - TD3: Thin Disc – Bin 3 <br> - TD4: Thin Disc – Bin 4 <br> - TD5: Thin Disc – Bin 5 <br> - TD6: Thin Disc – Bin 6 <br> - TD7: Thin Disc – Bin 7 <br> - B: Bulge <br> - TKD: Thick Disc <br> - H: Halo <br>- **Mproj**: Progenitor ZAMS mass of the RRL [Msun]<br>- **MRRL**: RRL mass [Msun]<br>- **McompRRL**: Mass of the RRL companion [Msun]<br>- **PorbRRL**: Current orbital period [days]<br>- **feh**: [Fe/H] metallicity<br>- **McRRL**: Core mass of the RRL [Msun]<br>- **LRRL**: Bolometric luminosity of the RRL [Lsun]<br>- **Teff**: Effective temperature of the RRL [K]</p>
Divergent evolution between sister species of European green lizards
<p>Annotation and variant calling files (VCFs, heffas) for <em>L. viridis </em>and<em> L. bilineata.</em> The variants have been called with <em>L. viridis</em> genome as reference.</p>
Data Release of Cosmic evolution of the incidence of Active Galactic Nuclei in massive clusters: Simulations versus observations
<p>Dataset of the paper "Cosmic evolution of the incidence of Active Galactic Nuclei in massive clusters: Simulations versus observations".</p> <p> </p> <p>All the necessary code to deal with these data can be found in: https://github.com/IvanMuro/agn_frac_data_release</p>
CLDF dataset accompanying Zariquiey et al.'s "Evolution of Body-Part Terminology in Pano" from 2022
<p>Cite the source of the dataset as:</p> <blockquote> <p>Zariquiey, Roberte; Vera, Javier; Greenhill, Simon; Valenzuela, Pilar; Gray, Russell; List, Johann-Mattis (2022): Untangling the evolution of body-part terminology in Pano: conservative vs. innovative traits in body-part lexicalization. Royal Society Interface Focus. DOI: https://doi.org/10.1098/rsfs.2022.0053</p> </blockquote>
Evolution of left-right asymmetry in the sensory system and foraging behavior during adaptation to food-sparse cave environments
<p>Laterality in relation to behavior and sensory systems is found commonly in a variety of animal taxa. Despite the advantages conferred by laterality (e.g., the startle response and complex motor activities), little is known about the evolution of laterality and its plasticity in response to ecological demands. In the present study, a comparative study model, the Mexican tetra (<em>Astyanax mexicanus</em>), composed of two morphotypes, i.e., riverine surface fish and cave-dwelling cavefish, was used to address the relationship between environment and laterality. The use of a machine learning-based fish posture detection system and sensory ablation revealed that the left cranial lateral line significantly supports one type of foraging behavior, i.e., vibration attraction behavior, in one cave population. Additionally, left-right asymmetric approaches toward a vibrating rod became symmetrical after fasting in one cave population but not in the other populations. Based on these findings, we propose a model explaining how the observed sensory laterality and behavioral shift could help adaptation in terms of the tradeoff in energy gain and loss during foraging according to differences in food availability among caves.</p> <p>This repository contains all of raw videos used in this study.</p> <p>Please let us know if you have any question on these videos</p>
Divergent Evolution of Earth and Venus—Transparent Version
<p>The theory of planetary heat pipes now tells us Venus and Earth may follow separate ways even though they shared a similar beginning. In the context of exoplanet studies, this means rocky planets with a hot surface—or with a thick atmosphere that acts like a blanket—may not exhibit plate tectonics. Also read: <a href="https://doi.org/10.1029/2022GL100987">https://doi.org/10.1029/2022GL100987</a></p>
Data for paper on the evolution of Chinese characters
<p>This dataset contains all image, complexity and distinctiveness data that was used for:</p> <p>Han, S. J, Kelly, P., Winters, J., & Kemp, C. (2022). Simplification is not dominant in the evolution of Chinese characters. <em>Open Mind</em>.</p> <p>The code for this project can be found <a href="https://github.com/cskemp/chinesecharacters">here</a>. The file uploaded here is intended to replace the sample data folder that is available in the code repository.</p> <p>Our dataset includes data scraped from hanziyuan.net, as well as data from the following sources:</p> <p>Sun, C. C., Hendrix, P., Ma, J., & Baayen, R. H. (2018). Chinese lexical database (CLD): A large-scale lexical database for simplified Mandarin Chinese. Behavior Research Methods, 50(6), 2606–2629.</p> <p>Wikimedia Commons. (2021). Chinese characters decomposition. <a href="https://commons.wikimedia.org/wiki/Commons:Chinese_characters_decomposition">https://commons.wikimedia.org/wiki/Commons:Chinese_characters_decomposition</a></p> <p>Liu, C.-L., Yin, F., Wang, D.-H., & Wang, Q.-F. (2011). CASIA online and offline Chinese handwriting databases. In 2011 international conference on document analysis and recognition (pp. 37–41). <a href="https://doi.org/10.1109/ICDAR.2011.17">https://doi.org/10.1109/ICDAR.2011.17</a></p> <p>Chen, P.-C. (2020). Traditional Chinese handwriting dataset. GitHub. <a href="https://github.com/AI-FREE-Team/Traditional-Chinese-Handwriting-Dataset">https://github.com/AI-FREE-Team/Traditional-Chinese-Handwriting-Dataset</a></p>
Alignments from "Caecilian genomes reveal molecular basis of adaptation and convergent evolution of limblessness in vertebrates"
<p>Compressed file containing the alignments at both nucleotide and amino acid level for the manuscript "Caecilian genomes reveal molecular basis of adaptation and convergent evolution of limblessness in vertebrates" </p>
Analysis of the P. lividus sea urchin genome highlights contrasting trends of genomic and regulatory evolution in deuterostomes
<p><br> Supplementary datasets accompanying paper: </p> <p>stage_peaks_anc_sel.xlsx : ATAC peaks with classification, conservation and binding sites<br> Pliv.mfuzz.enrichGO.txt : GO enrichment in MFuzz cluster<br> Pliv_genes_master_filt.xlsx : Gene models with corresponding information<br> bindetect_results_anf.txt : results of TOBIAS<br> hits_pprx_cl0_ord3vrr+Et_red.fa : alignment of homeobox sequences<br> Pliv_aH2p.gn.gtf.gz : annotation in GTF format<br> Pliv_PqN3S_sm.fa.gz : genome of P. livius <br> ansr_*_network.tsv.gz : Stage specific networks from ANANSE analysis<br> ATAC_pks_normcov.tsv : Coverage of unified peaks for ATAC-seq<br> Cttg_pks_normcov.tsv : Coverage of unified peaks for Cut-and-tag H3K27Ac data<br> lncRNA_stgSpe_fpkm.tsv : Expression levels (FPKM) for predicted lncRNAs for available RNA-seq samples <br> Split_Urchin_FPKMs.clean.txt.gz : Expression levels for unified ATAc-seq peaks following direct and reverse orientation</p> <p> </p> <p> </p> <p> </p> <p> </p>
Break the Code? Breaking Changes and Their Impact on Software Evolution (Artefacts)
<p>The artefacts included in this repository accompany the thesis "Break the Code? Breaking Changes and Their Impact on Software Evolution" authored by Lina María Ochoa Venegas and supervised by prof.dr. Jurgen Vinju, prof.dr. Mark van den Brand, and dr.Thomas Degueule. The thesis was developed at Eindhoven University of Technology (TU/e) in Eindhoven, The Netherlands and Centrum Wiskunde & Informatica (CWI) in Amsterdam, The Netherlands. It was submitted to revision in 2022 and defended in 2023.</p> <p> </p> <p><strong>Relevant Links</strong></p> <ul> <li><strong>Maracas:</strong> https://github.com/alien-tools/maracas</li> <li><strong>BreakBot: </strong>https://github.com/alien-tools/breakbot</li> </ul>
Induced immune reaction in the acorn worm, Saccoglossus kowalevskii, informs the evolution of antiviral immunity
<p>The data present in this repository reflect intermediate and processed data presented in the manuscript, <em>Induced immune reaction in the acorn worm, Saccoglossus kowalevskii, informs the evolution of antiviral immunity. </em>This manuscript is still under review; as such, this page will be updated upon publication.</p> <p> </p> <p><strong>Manuscript Abstract:</strong></p> <p>Evolutionary perspectives on the deployment of immune factors following infection have been shaped by studies on a limited number of biomedical model systems with a heavy emphasis on vertebrate species. Though their contributions to contemporary immunology cannot be understated, a broader phylogenetic perspective is needed to understand the evolution of immune systems across Metazoa. In our study, we leverage differential gene expression analyses to identify genes implicated in the antiviral immune response of the acorn worm hemichordate, <em>Saccoglossus kowalevskii</em>, and place them in the context of immunity evolution within deuterostomes – the animal clade composed of chordates, hemichordates, and echinoderms. Following acute exposure to the synthetic viral dsRNA analog, poly(I:C), we show that <em>S. kowalevskii </em>responds by regulating the transcription of genes associated with canonical innate immunity signaling pathways (e.g., NF-κB and IRF signaling) and metabolic processes (e.g., lipid metabolism), as well as many genes without clear evidence of orthology with those of model species. Aggregated across all experimental time point contrasts, we identify 423 genes that are differentially expressed in response to poly(I:C). We also identify 147 genes with altered temporal patterns of expression in response to immune challenge. By characterizing the molecular toolkit involved in hemichordate antiviral immunity, our findings provide vital evolutionary context for understanding the origins of immune systems within Deuterostomia.</p> <p> </p> <p><strong>Repository contents:</strong></p> <p>### Processed Data ###</p> <ul> <li><em>Full_DESeq2_matrix.csv </em>--> DESeq2 results for each contrast (e.g., 2hpi treatment vs. control)</li> <li><em>MaSigPro.Clusters.csv</em> --> Mean expression for each gene placed within a pDEG cluster</li> <li><em>MaSigPro.SigGenes.TreatmentvsControl.Robj</em> --> T.fit() R-object output from MaSigPro pipeline. This can be opened in R using the load() function.</li> </ul> <p>### Homology Assessment ###</p> <ul> <li><em>Orthofinder.tar.gz</em> --> OrthoFinder results</li> <li><em>Skowalevskii_Genome_Annotation.SPHuman_and_HOG.csv</em> --> Assignment of IDs to Skow1.1 genes conforming to "PANTHER-Human" and "HOG" output described in the main text of the paper</li> <li><em>Skowalevskii_Genome_Annotation.SPPANTHER.csv </em>--> Assignment of IDs to Skow1.1 genes conforming to "PANTHER-SwissProt" output described in the main text of the paper</li> </ul> <p>### Functional Annotation ###</p> <ul> <li><em>Skow.HMMER_Pfam.domtblout.tsv</em> --> Pfam annotation of the Skow1.1 genome assembly in HMMER's domblout format</li> <li><em>Skow.KofamKOALA.detail.tsv</em> --> KO annotation of the Skow1.1 genome assembly using KofamKOALA (detailed output)</li> <li><em>Skow.KofamKOALA.detail.tsv </em>--> KO annotation of the Skow1.1 genome assembly using KofamKOALA (mapper output)</li> <li><em>SkowAnnotations.GO.tsv</em> --> GO annotation of the Skow1.1 genome assembly</li> <li><em>SkowAnnotations.PF.tsv</em> --> PF annotation of the Skow1.1 genome assembly</li> <li><em>SkowAnnotations.PP.tsv</em> --> PP annotation of the Skow1.1 genome assembly</li> </ul> <p>### Enrichment Data ###</p> <ul> <li><em>DESeqEnrichments.tsv</em> --> Pearson's chi-squared enrichment calculations for every annotation present in the Skow1.1 genome assembly for genes resolved as significantly differentially expressed by DESeq2.</li> <li><em>MaSigProEnrichments.tsv</em> --> Pearson's chi-squared enrichment calculations for every annotation present in the Skow1.1 genome assembly for genes resolved as significantly differentially expressed by MaSigPro.</li> </ul>
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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.