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523 results for “Evolution analysis”
Drainage reorganisation and species evolution: model sensitivity analysis data
<p>Data description:</p> <ul> <li><strong>‘trial_factor_values.csv’:</strong> The factor values for experiment trials were generated using a quasi-random Sobol sequence (Sobol, 1967). The table field, ‘initial_landscape_id’ is the identifier for unique combinations of the following factor values that controlled the landscape elevation in the initial conditions phase of the model: initial elevation seed, <span class="math-tex">\(U\)</span>, <span class="math-tex">\(K\)</span>, and <span class="math-tex">\(k_d\)</span>. The factors, <span class="math-tex">\(U\)</span>, <span class="math-tex">\(K\)</span>, <span class="math-tex">\(k_d\)</span>, <span class="math-tex">\(P_m\)</span>, and allopatric wait time varied logarithmically. The values of these factors in the file are the exponent of base 10.</li> <li><strong>‘trial_response_values_initial_conditions_phase.csv’:</strong> Topographic relief at steady state along with the model time to initial steady state are the trial model responses included in the file. Values are listed for each initial landscape ID rather than trial because many trials had the same combinations of the factors that controlled the topography of the initial landscape. </li> <li><strong>‘trial_response_values_perturb_phase_base_level_fall_scenario.csv’ and ‘trial_response_values_perturb_phase_fault_throw_scenario.csv’:</strong> Model responses of the perturb phase for base level fall and fault throw scenario along with the initial landscape ID, species count values, and the model time back to steady state.</li> <li><strong>The files beginning with `sobol`</strong>: the sensitivity analysis results output by the software, ‘SALib’ (Herman and Usher, 2017). ‘S1’, ‘S2’, and ‘ST’ in the file name indicates if the file contains data of the Sobol first, second, or total order effect, respectively.</li> </ul>
Datasets and Jupyter notebook for the structural analysis of protein-RNA interface evolution
<p>The present repository contains data and code related to our manuscript "Structural comparison of protein-RNA homologous interfaces reveals widespread overall conservation contrasted with versatility in polar contacts". In the manuscript, we analyze the evolution of protein-RNA interfaces by building a dataset of protein-RNA interologs (homologous interfaces) and exploring how interface contacts are conserved between homologous interfaces, as well as possible explanations for non-conserved contacts.</p> <p>This repository contains the following files:</p> <ul> <li>DataAnalysisNotebook.ipynb is a Jupyter notebook to reproduce contact conservation analysis and all figures from our manuscript, and to explore data</li> <li>env.yaml is an environment file in order to build a Conda/Mamba environment to run the Jupyter notebook </li> <li>2022-02-21-PDB.csv contains data from the PDB about 3D structures of complexes containing interacting protein and RNA chains (PDB structure identifier, chain identifiers, experimental technique and resolution)</li> <li>2022-02-21-PDB_proteinchainscontactingRNAchains.groupbp.tsv contains more detailed information about interacting protein and RNA chains from these complexes (PDB and chain identifiers, protein and RNA size, interface size and number of contacts)</li> <li>2022-02-21-PDB_proteinchainscontactingRNAchains.groupbp.txt.selectXE_2.50_p30_r10_pi5_ri5_rep_bc-100.out_RNAcl_0.99.tsv contains the same detailed information, restricted to the filtered dataset used as a starting point in our interolog search pipeline</li> <li>PDBinterfaceAlign.csv contains information about the structural alignment of pairs of protein-RNA interactions (structural alignment TM-scores, sequence identity and coverage)</li> <li>DataInterologsParam.tsv contains information about a pre-filtered set of 2587 potential interologs (including interface RMSD, sequence identity and coverage and interface size)</li> <li>DataInterologsContactsFixedSASA.tsv contains detailed information about conserved and non-conserved contacts in the final set of 2022 interologs (atomic contacts, apolar contacts, hydrogen bonds, salt bridges and stacking information for aminoacid-nucleotide pairs, as well as information about whether each belongs to the interface, secondary structures, and the aminoacid surface accessibility and evolutionary conservation metrics) - compared to version 1, the calculation of solvent accessibility was fixed for a number of interolog pairs</li> <li>DataCons.csv contains precomputed contact conservation metrics for each of the 2022 interolog pairs, for fast reproduction of manuscript figures</li> <li>DataInterologsContactsResampledMaintainStructSeqId.tsv, DataInterologsContactsShuffled.tsv and DataInterologsShuffled.tsv relate to baselines computed for contact conservation assessment</li> <li>clan.txt, clan_membership.txt, ecod.latest.domains.uniq.txt, rfam_interfaces_977.txt, DataGroupsECOD.tsv, DataGroupesRFAM.tsv, DataGroupsRFAMClan.tsv, DataInterfaceGroupsECOD.tsv and DataInterfaceGroupsRFAM.tsv relate to the ECOD (respectively Rfam) classification of protein domains (respectively RNA) in protein-RNA interfaces from our dataset</li> <li>ListeIntraHbonds.pkl and ListeIntraSaltBridges.pkl are pickle-format data files containing intra-molecular hydrogen bonds and salt bridges (respectively) that are used to analyse scenarii of compensation for non-conserved polar contacts.</li> </ul>
Kin selection explains the evolution of cooperation in the gut microbiota, by Simonet & McNally, 2020, Dataset S1 and codes for statistical analysis and figures production
<p>Dataset S1 contains all raw and processed material referred to in the published article "Kin selection explains the evolution of cooperation in the gut microbiota". R codes files provide all codes to replicate the analysis. Please refer to the README file for a description of all code files. The manifest files are those obtained by accessing the HMP portal on April 2020 under Project > HMP, Body Site > feces, Studies>WGS-PP1, File Type > WGS raw sequences set, File format > FASTQ.</p> <p>We also provide access to these data and codes at our GitHub (https://github.com/CamilleAnna/HamiltonRuleMicrobiome gitRepos.git) which can be cloned to directly re-run this analysis. </p> <p><strong>Legends for Dataset S1:</strong></p> <ul> <li>Sheet 1: Metagenomic samples used and access links.</li> <li>Sheet 2: Reference on bacterial cooperation retrieved from Web of Science search: TI¯((microb* OR bacter* OR microorganis* OR micro-organis*) AND (coop* OR social*)</li> <li>Sheet 3: Retained bacteria cooperation keywords</li> <li>Sheet 4: GOs identified by annotating all MIDAS database genomes (5944 genomes) with PANNZER2.</li> <li>Sheet 5: Full list of potential bacterial cooperation GO terms and description of manual curation decisions.</li> <li>Sheet 6: Final list of bacterial cooperation GO used for the analysis</li> <li>Sheet 7: Genomic diversity of the bacterial population within and across host. Computed from MIDAS snp_diversity.py pipeline.</li> <li>Sheet 8: final dataset for statistical analysis.</li> <li>Sheet 9: per-gene annotation of cooperation.</li> </ul>
Data from: Combined experimental-numerical analysis of the temperature evolution and distribution during friction surfacing
<p>This dataset contains the data for the publication "Combined experimental-numerical analysis of the temperature evolution and distribution during friction surfacing".</p>
The evolution of gender monitoring and its challenges in Research and Innovation in Europe: She Figures reports analysis dataset
<p><span>The article delves into the European Commission's flagship initiative on gender monitoring in science and innovation, offering a responsible metrics perspective and drawing on equality policy literature. Over two decades, the initiative has evolved from competitiveness-related justifications to more transformative objectives related to equality policy evaluation, with the measurement areas and policy focus also undergoing changes. While there has been notable progress, the article points out a logic of invisibility in how dimensions and indicators are conceptualised and their data sources and interpretation. However, it also highlights a significant improvement in the information available. The article suggests that the contextualisation of the process could be enhanced to better integrate it into the policy-making cycle, a crucial area for further research. It concludes with proposals for future gender monitoring science and innovation. The aim is to offer an encouraging vision of monitoring that counts more on who is monitored and in opening up the debates instead of closing them.</span></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>
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>
A Linked Application of Discrete Differential Evolution Algorithm Coupled with Simulation- Optimization Model and Comparative Analysis by Genetic Algorithm for Discrete Groundwater Management Problems
<p>Complete dataset of publication name as "The complete publication dataset is "A Discrete Differential Evolution- Linear Programming Algorithm for Groundwater Management Problems." You can find all the written codes in the zip file.</p>
Data and analysis scripts associated with the paper 'Long-term experimental evolution of HIV-1 reveals effects of environment and mutational history''
<p><em>Eva Bons, Christine Leemann, Karin J. Metzner, Roland R. Regoes</em></p> <p>This repository contains all the data and analysis scripts associated with the paper 'Long-term experimental evolution of HIV-1 reveals effects of environment and mutational history'</p> <p>See the readme after unpacking the .zip for a description of the files</p>
Model, data, and analysis for Negative Niche Construction Favors the Evolution of Cooperation
<p>This repository contains the model, data, and analysis corresponding to <em>Negative Niche Construction Favors the Evolution of Cooperation</em> as submitted for review by Brian D. Connelly, Katherine J. Dickinson, Sarah P. Hammarlund, and Benjamin Kerr. Contents are released to the public domain under the Creative Commons CC0 License.</p>
Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect
<p>Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect as submitted</p>
Data behind The ALCHEMI atlas: principal component analysis reveals starburst evolution in NGC 253
<p>This depository is for additional files of the PCA paper using the ALCHEMI survey.</p> <p>std_datalist.csv: This is a csv file that includes standardized intensities for all the transitions/continua.</p> <p>pca_alchemi_corrmatrix.py: This is a python file to plot a correlation matrix of standardized intensities. It displays a transition pair when you hover the cursor on the matrix element. It uses std_datalist.csv.</p>
Unique composition and evolution histories of low velocity mantle domains: Data and analysis
<p>Dataset and Jupyter notebook accompanying 'Unique composition and evolution histories of low velocity mantle domains'. </p> <p>Dataset includes:</p> <ul> <li>Present day properties of simulated mantle for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER.</li> <li>Present day predicted seismic properties for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, MER.</li> <li>Present day predicted seismic properties for simulation PRM assuming 'primordial' material to be i) basaltic oceanic crust ii) chondrite enriched basalt (CEB).</li> <li>Present day delta Vs for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER, filtered using the resolution of seismic tomography model S40RTS.</li> <li>Properties of simulated mantle at 100 Myr intervals from 900 Ma - 100 Ma inclusive for simulation RCY. </li> <li>P-T tables with predicted abundance of post-perovskite for different mantle lithologies (harzburgite, lherzolite and basalt - as defined in the paper).</li> </ul> <p>Jupyter notebook `s-llvps.ipynb` contains code for identifying simulated large low-velocity provinces (S-LLVPs), extracting assoicated model properties and plotting results. Python module files terra_utils.py and ppv.py are also included and required by the code in the notebook. </p> <p>There are a number of pre-requisite packages that will need to be installed in order to run the Jupyter notebook, including <a title="terratools" href="https://github.com/mantle-convection-constrained/terratools" target="_blank" rel="noopener">terratools</a>, a software package written specifically for reading and postprocessing outputs from TERRA simulations. Installation instructions can be found on the GitHub repository. </p> <p>Due to the TERRA code pre-dating open source licensing, we do not currently have permission to publicly share all aspects of the code. In code_pieces.F90 we include code snippets which were implemented for this study. </p> <p>Simulations were conducted using ARCHER2, the UK's national super-computing service. </p> <p>RCY.mp4 is a movie produced for simualtion RCY, visualising the evolution of temperature (right panels) and bulk composition (left panels). Hot iso-surface (red) drawn at +500 K and cold iso-surface (blue) drawn at -400 K, composition iso-surface drawn at C=0.6. Red and blue lines indicate overlying ridges / subduction zones taken from the plate motion reconstructions of Müller et al (2022). </p>
Data for phylogenomic analysis of chelicerate gene family evolution
<p>We used phylogenomics to investigate patterns of gene family evolution across ticks and other chelicerates, which include a diverse array of parasites. We used phylogenetic profiling and trait-association tests to predict gene families that may enable parasitic species to feed on hosts undetected for prolonged periods (>1 day). This release accompanies the pub, “<a href="https://doi.org/10.57844/arcadia-4e3b-bbea">Comparative phylogenomic analysis of Chelicerates points to gene families associated with long-term suppression of host detection</a>." Please see the pub for more information.</p> <ul> <li>chelicerata-v1-10062023.zip contains the outputs from NovelTree that are needed as inputs for phylogenetic profiling.</li> <li>annotated.zip contains gene annotations used to do orthogroup filtering.</li> <li>tx2gene.tsv has presence/absence of expression for each Amblyomma americanum transcript. </li> <li>chelicerate_proteome_preprocessing_outputs.zip contains the outputs of chelicerate protein data curation.</li> <li>chelicerata-v1-parameterfile.json & chelicerata-v1-samplesheet.csv were inputs for setting up the initial NovelTree run.</li> <li>2024-06-24-all-chelicerate-noveltree-proteins.fasta has the full set of chelicerate protein sequences.</li> <li>summary_of_noveltree_results.zip contains summary figures from the outputs of the NovelTree run.</li> <li>chelicerate-samples.tsv is the sample sheet used in proteome curation upstream of NovelTree.</li> </ul>
Codes and model output supporting Analysis of the Evolution of Parametric Drivers of High-End Sea-Level Hazards
<p>Codes and model output supporting Analysis of the Evolution of Parametric Drivers of High-End Sea-Level Hazards (Advances in Statistical Climatology, Meteorology and Oceanography, May 2022)</p>
Fig. 5 a–f in Integrative analysis of the West African Ceraceosorus africanus sp. nov. provides insights into the diversity, biogeography, and evolution of the enigmatic Ceraceosorales (Fungi: Ustilaginomycotina)
Fig. 5 a–f Macroscopic symptoms of infection of Bombax costatum leaves by Ceraceosorus africanus (a–d taken on the type locality; e, f taken on the locality between Zibogo and Tugu): a view of the crown of the tree with scattered infected leaves marked by white arrows; b–f different levels of development of leaf blight caused by the fungus (b, c, e, f on the leaf underside; d on the leaf upperside). g–i Macroscopic
Fig. 4 in Integrative analysis of the West African Ceraceosorus africanus sp. nov. provides insights into the diversity, biogeography, and evolution of the enigmatic Ceraceosorales (Fungi: Ustilaginomycotina)
Fig. 4 Hypothesis of phylogenetic relationships of the sampled Ustilaginomycotina based on 18S, 5.8S, 28S, RPB2, and TEF1 sequences (4896 bp). The tree was rooted with Microbotryum violaceum s.l. and Puccinia graminis. Statistical support is given as ML bootstrap above branches (≥70) and Bayesian posterior MCMC probability below branches (≥0.90). The lines in bold indicate a maximum support of 100/1.00. The superorder Exobasidianae is marked with a black dot. Mon. = Moniliellomycetes
Fig. 1 in Integrative analysis of the West African Ceraceosorus africanus sp. nov. provides insights into the diversity, biogeography, and evolution of the enigmatic Ceraceosorales (Fungi: Ustilaginomycotina)
Fig. 1 Currently known distribution of Ceraceosorus africanus (red dots) on the background of the global distribution of Bombax costatum in the Sudanian savanna biome (green area, based on the map shown on the website: http:// www.hombori.org/francais/ biodiversity/flora.html)
Fig. 8 in Integrative analysis of the West African Ceraceosorus africanus sp. nov. provides insights into the diversity, biogeography, and evolution of the enigmatic Ceraceosorales (Fungi: Ustilaginomycotina)
Fig. 8 Microstructure of Ceraceosorus africanus (all from holotype): a hymenial layer with basidioles, basidia, and basidiospores; b subhymenial layer with strongly agglutinated hyphae; c basidia and basidiole; d basidiospores. Scale bars = 10 μm
Fig. 7 in Integrative analysis of the West African Ceraceosorus africanus sp. nov. provides insights into the diversity, biogeography, and evolution of the enigmatic Ceraceosorales (Fungi: Ustilaginomycotina)
Fig. 7 Intracellular hyphae of Ceraceosorus africanus (from holotype) within a cell of Bombax costatum seen by LM. Scale bar = 10 μm
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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.