Find research datasets worth reusing

opencc-by-4.0Aug 2018View details →

bin3C - simulated community and associated sequencing datasets

We simulated a human gut microbiome comprising 63 genomes from the GTDB annotated with an isolation source of faeces. No two genomes are more than 96% similar in terms of ANI. A Generalized Pareto distribution was used to model an abundance profile, which was assigned in random order to the references. There is a 50:1 difference between the most and least abundant member. Illumina shotgun and Hi-C reads were simulated using MetaART and sim3C (https://github.com/cerebis/sim3C). A sweep was performed over depth of coverage, by serially subsampling initial high depth readsets. Shotgun depth was parameterised by the most abundant at 250x, while Hi-C was parameterised by the number of pairs (200 million pairs). Shotgun was subsampled once, at half depth (125x), while Hi-C was subsampled 4 times (12.5, 25, 50, 100, 200 million pairs). The random seed used throughout was 12345. These simulated readsets were then analyzed using bin3C to retrieve metagenome-assembled genomes (MAGs). The resulting genome bins were validated using CheckM to estimate completeness and contamination.

opencc-by-sa-4.0Oct 2018View details →

Data associated with the publication "The origin of the world's smallest flightless bird, the Inaccessible Island Rail Atlantisia rogersi (Aves: Rallidae)"

DESCRIPTION OF FILES These are files including data and additional results, that support the paper "The origin of the world's smallest flightless bird, the Inaccessible Island Rail Atlantisia rogersi (Aves: Rallidae)", by Stervander et al. 2018, published in Molecular Phylogenetics and Evolution (doi: 10.1016/j.ympev.2018.10.007). The phylogenetic analyses focus on rails (Aves: Rallidae) and outgroups based on (1) a dataset, 'MtProt' comprising the coding sequences (cds) from full mitochondrial genome assemblyes, and (2) a mixed-marker dataset, '2Nc3Mt', comprising the mitochondrial markers cytochrome b (cytb), cytochrome oxidase subunit I (COI), and 16S ribosomal RNA (16S), and the nuclear markers β-fibrinogen intron 7 (bFib7) and recombination activating gene 1 (RAG1). The latter dataset i largely based on data from Garcia-R et al. (2014), with additions of the Inaccessible Island Rail Atlantisia rogersi and some further sequences (see our paper). Trees mentioned in our paper as "results not shown" can be found below. This deposition contains five groups of data: 1. Beast input xml files for phylogenetic analyses 2. Beast output: log files 3. Beast output: raw tree files 4. Beast output: Maximum Clade Credibility trees 5. Tree figures (pdf format) The above are available for the following analyses: A. Mixed-marker dataset ‘2Nc3Mt’, one tree  B. Mixed-marker dataset ‘2Nc3Mt’, one tree; Micropygia schomburgkii excluded C. Mixed-marker dataset ‘2Nc3Mt’, separate mitochondrial (‘3Mt’) and nuclear marker trees (RAG1 and bFib7) D. Protein coding dataset ‘MtProt’ from entire mitochondrial genomes The files are thus the following, sorted according to dataset: A1    Beast_input_2Nc3Mt_1tree.xml A2    Beast_output_2Nc3Mt_1tree.log A3    Beast_output_2Nc3Mt_1tree.raw.trees A4    Beast_output_2Nc3Mt_1tree.max_clade_cred_burnin10M.trees A5    Tree_2Nc3Mt_1tree.max_clade_cred_burnin10M.pdf B1    Beast_input_2Nc3Mt_exclMicropygia_1tree.xml B2    Beast_output_2Nc3Mt_exclMicropygia_1tree.log B3    Beast_output_2Nc3Mt_exclMicropygia_1tree.raw.trees B4    Beast_output_2Nc3Mt_exclMicropygia_1tree.max_clade_cred_burnin10M.trees B5    Tree_2Nc3Mt_exclMicropygia_1tree.max_clade_cred_burnin10M.pdf C1    Beast_input_2Nc3Mt_separate_trees.xml C2    Beast_output_2Nc3Mt_separate_trees.log C3    Beast_output_2Nc3Mt_RAG1.raw.trees C3    Beast_output_2Nc3Mt_bFib7.raw.trees C3    Beast_output_2Nc3Mt_mt.raw.trees C4    Beast_output_2Nc3Mt_RAG1.max_clade_cred_burnin10M.trees C4    Beast_output_2Nc3Mt_bFib7.max_clade_cred_burnin10M.trees C4    Beast_output_2Nc3Mt_mt.max_clade_cred_burnin10M.trees C5    Tree_2Nc3Mt_RAG1.max_clade_cred_burnin10M.trees.pdf C5    Tree_2Nc3Mt_bFib7.max_clade_cred_burnin10M.trees.pdf C5    Tree_2Nc3Mt_mt.max_clade_cred_burnin10M.trees.pdf D1    Beast_input_MtProt_1tree.xml D2    Beast_output_MtProt_1tree.log D3    Beast_output_MtProt_1tree.raw.trees D4    Beast_output_MtProt_1tree.max_clade_cred_burnin1M.trees D5    Tree_MtProt_1tree.max_clade_cred_burnin1M.pdf Or, sorted according to file type: 1A    Beast_input_2Nc3Mt_1tree.xml 1B    Beast_input_2Nc3Mt_exclMicropygia_1tree.xml 1C    Beast_input_2Nc3Mt_separate_trees.xml 1D    Beast_input_MtProt_1tree.xml 2A    Beast_output_2Nc3Mt_1tree.log 2B    Beast_output_2Nc3Mt_exclMicropygia_1tree.log 2C    Beast_output_2Nc3Mt_separate_trees.log 2D    Beast_output_MtProt_1tree.log 3A    Beast_output_2Nc3Mt_1tree.raw.trees 3B    Beast_output_2Nc3Mt_exclMicropygia_1tree.raw.trees 3C    Beast_output_2Nc3Mt_RAG1.raw.trees 3C    Beast_output_2Nc3Mt_bFib7.raw.trees 3C    Beast_output_2Nc3Mt_mt.raw.trees 3D    Beast_output_MtProt_1tree.raw.trees 4A    Beast_output_2Nc3Mt_1tree.max_clade_cred_burnin10M.trees 4B    Beast_output_2Nc3Mt_exclMicropygia_1tree.max_clade_cred_burnin10M.trees 4C    Beast_output_2Nc3Mt_RAG1.max_clade_cred_burnin10M.trees 4C    Beast_output_2Nc3Mt_bFib7.max_clade_cred_burnin10M.trees 4C    Beast_output_2Nc3Mt_mt.max_clade_cred_burnin10M.trees 4D    Beast_output_MtProt_1tree.max_clade_cred_burnin1M.trees 5A    Tree_2Nc3Mt_1tree.max_clade_cred_burnin10M.pdf 5B    Tree_2Nc3Mt_exclMicropygia_1tree.max_clade_cred_burnin10M.pdf 5C    Tree_2Nc3Mt_RAG1.max_clade_cred_burnin10M.trees.pdf 5C    Tree_2Nc3Mt_bFib7.max_clade_cred_burnin10M.trees.pdf 5C    Tree_2Nc3Mt_mt.max_clade_cred_burnin10M.trees.pdf 5D    Tree_MtProt_1tree.max_clade_cred_burnin1M.pdf Note about the tree figures (pdf format): Nodes marked with a black circle are supported by a posterior probability (PP) of 1.0, for lower PP the number is given at the node. Blue bars represent the 95% highest posterior density intervals of the node age. MYA = Million years ago. /Martin Stervander (martin@stervander.com)

opencc-by-4.0Dec 2018View details →

Meta-analysis results of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni<1.06x10-7).

opencc-by-4.0Jan 2019View details →

Ontology based text mining of gene-phenotype associations: application to candidate gene prediction

Gene-phenotype associations play an important role in understanding   the disease mechanisms which is a requirement for treatment   development. A portion of gene-phenotype associations are observed   mainly experimentally and made publicly available through several   standard resources such as MGI. However, there is still a vast   amount of gene--phenotype associations buried in the biomedical   literature. Given the large amount of literature data, we need   automated text mining tools to alleviate the burden in manual   curation of gene-phenotype associations and to develop   comprehensive resources. We developed an ontology based   approach in combination with statistical methods to text mine   gene-phenotype associations from literature. Our method achieved   AUC values of 0.90 and 0.75 in recovering known gene-phenotype   associations from HPO and MGI respectively. We posit that candidate   genes and their relevant diseases should be expressed with similar   phenotypes in publications. Thus, we demonstrate the utility of our   approach by predicting disease candidate genes based on the semantic   similarities of phenotypes associated with genes and diseases. We evaluated our disease candidate prediction model on   the gene-disease associations from MGI. Our model achieved AUC   values of 0.90 and 0.87 on OMIM (human) and MGI (mouse) datasets of   gene-disease associations respectively. Our manual analysis on the   text mined data revealed that, our method can accurately extract   gene-phenotype associations which are not currently covered by the   existing public gene-phenotype resources. Overall, results indicate   that our method can precisely extract known as well as new   gene-phenotype associations from literature. This released dataset at Zenodo covers our gene-phenotype extracts from the literature. All the methods used to extract the data are available at https://github.com/bio-ontology-research-group/genepheno.

opencc-by-4.0Apr 2019View details →

Large cortical bone pores in the tibia are associated with proximal femur strength - data for reproduction

Results tables for the reproduction of: Iori G, Schneider J, Reisinger A, Heyer F, Peralta L, Wyers C, et al. Large cortical bone pores in the tibia are associated with proximal femur strength. PLOS ONE. doi:10.1371/journal.pone.0215405

opencc-by-4.0Apr 2019View details →

Dataset associated with Schyns & Vanham (2019) "The water footprint of wood for energy consumed in the European Union"

Input and output datasets related to the paper Schyns & Vanham (2019) The water footprint of wood for energy consumed in the European Union. Water, 11(2): 206.

opencc-by-4.0Oct 2018View details →

Phenome-wide association studies across large population cohorts support drug target validation

Summary-level data generated by Genomics plc as presented in: Diogo, D. et al. Phenome-wide association studies across large population cohorts support drug target validation. Nat. Commun. 9, 4285 (2018). https://doi.org/10.1038/s41467-018-06540-3 If you have any questions or comments regarding these files, please contact Genomics plc at <a href="mailto:research@genomicsplc.com">research@genomicsplc.com</a> NOTES ----------------------------- These analyses were carried out using the interim UK Biobank imputation data release. Analyses were restricted to a subset of "white-British" unrelated samples with a maximum sample size of 112,337 individuals.  Case control phenotypes were defined based on categorical datafields as listed in the accompanying file.  Quantitative phenotypes were either rank-normalised before analysis, or beta/se values were standardised after analysis using the variance of the phenotype. The normalisation value is indicated in the accompanying file.   All analyses included Age at assessment, sex, genotyping chip, and 10 principal components as covariates.  We used plink1.9 linear/logistic regression as appropriate. For chromosome X variants males were treated as having 0 or 2 alternative alleles.  The results are not adjusted for genomic control. DATA FILE CONTENT DESCRIPTION ----------------------------- CHR - Chromosome SNP - Variant rsID ALT - Alternative allele (effect allele) REF - Reference Allele (non-effect allele) BP - Position in base pairs (b37, 1-based) NMISS - Number of samples with non-missing genotypes BETA - Effect size (log odds ratio or standardised effect size) SE - Standard error P - P-value F_MISS - genotype missing rate P_hwe - Hardy-weinberg p-value MAF - ALT allele frequency

opencc-by-4.0Jun 2019View details →

Human Kelch-like ECH Associated Protein 1 (KEAP1); A Target Enabling Package

KEAP1 is a highly redox-sensitive member of the BTB-Kelch family that assembles with the CUL3 protein to form a Cullin-RING E3 ligase complex for the degradation of NRF2. Oxidative stress disables KEAP1 allowing NRF2 protein levels to accumulate for the transactivation of critical stress response genes. Consequently, the KEAP1-NRF2 system is a highly attractive target for the development of protein-protein interaction inhibitors that will stabilise NRF2 for therapeutic effect in conditions of neurodegeneration and inflammation. As part of this TEP we have solved the first crystal structure of a KEAP1-CUL3 complex as well as a structure of the apo-Kelch domain suitable for small molecule soaking. We further established a selectivity assay panel of 17 human Kelch domain-containing proteins and have shown that non-covalent KEAP1 inhibitors from the literature are highly selective for KEAP1. This protein panel offers a resource for future work on KEAP1 as well as 16 other human Kelch proteins.

opencc-by-4.0May 2017View details →

Images associated to the paper "Evaluating the Sensitivity to Virtual Characters Facial Asymmetry in Emotion Synthesis"

We conducted an experiment by presenting 64 pairs of static facial expressions, one symmetric and one asymmetric, illustrating eight emotions (three basic and five complex ones) alternatively for a male and a female character. Each emotion was presented four times by swapping the symmetric and asymmetric positions and by mirroring the asymmetrical expression. Participants were asked to grade, on a continuous scale, the correctness of each facial expression with respect to a short definition

opencc-by-4.0Oct 2019View details →

Data archive associated with "Landscape age as a major control on the geography of soil weathering" (https://doi.org/10.1029/2019GB006266)

(1) Table including parameter values and weathering model outputs associated with NASGLP sampling locations (SLP_data.csv).  (2) List of rivers used for calibrating erosion estimates (river_list.csv). (3) R workspace with same data as (1), plus a data frame of global parameter values ("gm") and spatial polygons giving continent boundaries ("con"). (4) Scripts with functions for running the single-compartment weathering model at individual point locations or running a global sample of locations and computing summary statistics by continent (run_soilgenesis.R; soilgenesis.R).

Dateset on 'Disentangling associations of human wellbeing with green infrastructure, degree of urbanity, and social factors around an Asian megacity'

The data was collected a part of the baseline survey on household socio-economics among the Bengalurian along the rural-urban interface.

Data associated with the manuscript: Andean bear tree selectivity for scent-marking in Ecuadorian cloud forests

This is the original version of data used for the manuscript, Andean bear tree selectivity for scent-marking in Ecuadorian cloud forests. The data are in four files following the numerical order and titles of the Results section in the manuscript, i.e. 1_PCA.csv, 2_Modeling tree selection at the individual-tee level.csv, 3_Modeling tree selection on a local spatial scale.csv, 4_Modeling formation of marked-tree cluster sites.csv. We used these datasets for our analysis in the program R, the details are provided in the Methods section. Our field work was performed in compliance with the Framework Agreement for access to genetic resources called "Biodiversity Study of Ecuador '' made between the Ecuadorian Ministry of Environment and the UTPL. The code for the Agreement is MAE-DNB-CM-2015-0016-M-0002. The research was funded by Bears in Mind, International Association for Bear Research and Management, the Faculty of Environmental Sciences of Czech University of Life Sciences in Prague, National Geographic Society, Nature and Culture International, GIZ Ecuador, and Trailcampro.

Metabolomics data associated with "Glial swip-10 controls systemic mitochondrial function, oxidative stress, and neuronal viability via copper ion homeostasis"

Raw feature tables used for metabolomic analysis of the Caenorhabditis elegans mutant swip-10. The data were generated using liquid chromatography coupled high-resolution mass spectrometry. Two different columns were used: HILIC (+ ESI) and C18 (-ESI), coupled to a Thermo Q-Exactive Orbitrap mass spectrometer. The feature tables were generated using open-source peak peaking and alignment R packages: apLCMS and xMAanalyzer. See more details in the associated manuscript.

Prey nutrient content is associated with the trophic interactions of spiders and their prey selection under field conditions

<h2>Materials and Methods</h2> <h2><a name="_Toc58843581"></a>Fieldwork</h2> <a name="_Hlk173879015"></a><a name="_Hlk56335325"></a>Money spiders (Araneae: Linyphiidae) and wolf spiders (Araneae: Lycosidae), the two most abundant spider groups in this study, were visually located along transects in two adjacent barley fields at Burdons Farm, Wenvoe in South Wales (51°26'24.8"N, 3°16'17.9"W) and collected from occupied webs and the ground in daylight hours between April and September 2018. Each belt transect was adjacent to a randomly selected crop tramline and were distributed across the entire field and ran its length. The areas searched were 4 m2 quadrats at least 10 m apart and all observed linyphiids and lycosids were collected. The 300 spiders taken forward for molecular dietary analysis in this study were taken from 64 randomly selected locations along the aforementioned transects. Following collection of spiders, 4 m2 of ground and crop stems was suction sampled <a name="_Hlk173879230"></a>in each of these 64 sampling locations for approximately 30 seconds, with the collected material emptied into a bag and any organisms immediately killed with ethyl-acetate. Suction sampling used a ‘G-vac’ modified garden leaf-blower. All material was later frozen at -20 ºC for storage before sorting in the lab. Sticky trap data were also collected, but were not used in this study as suction sampling was found to represent the interactions of spiders more closely (Cuff, Tercel et al., 2024). These invertebrates were collected for background population densities and macronutrient analysis, not for molecular dietary analysis. All invertebrates were identified to family level using morphological keys: Araneae (Roberts, 1993), Diptera (Ball, 2008), Coleoptera (Duff, 2012), Hymenoptera (Goulet & Huber, 1993), Hemiptera (Unwin, 2001), Collembola (Dallimore & Shaw, 2013) and Chilopoda (Barber, 2008). Further identifications were not carried out due to the inability to identify some of the invertebrate groups further via the associated metabarcoding-derived dietary data (e.g., Sciaridae), and the difficulty associated with finer taxonomic resolution of many damaged or immature specimens. The only taxa not identified to family level were springtails of the superfamily Sminthuroidea (Sminthuridae and Bourletiellidae, which were often indistinguishable following suction sampling and preservation due to the fine features necessary to differentiate them) which were left at super-family, mites (many of which were immature or in poor condition, or lacked appropriate taxonomic keys) which were identified to order level and wasps of the superfamily Ichneumonoidea (which were identified no further due to obscurity of wing venation due to damage); in these cases, these taxonomic assignments were pooled to family-level for later analyses. <a name="_Hlk96098198"></a> Extraction, amplification and sequencing of DNA from the individually collected spiders, and its bioinformatic analysis are described by Cuff, Tercel, et al. (2022) and Drake et al. (2022) and are also detailed in Supplementary Information 1. In short, dietary metabarcoding was carried out using two primer pairs, one excluding predator DNA and the other amplifying it, to overcome the problem of overamplification of predator DNA (Cuff, Kitson, et al., 2023). Amplified DNA was sequenced on an Illumina MiSeq V3 2x300 cartridge, and resultant data screened for false positives following bioinformatic processing via minimum sequence copy thresholds applied according to read counts in controls and control DNA counts present in samples (Drake et al., 2022).   <h2><a name="_Toc58843582"></a>Macronutrient determination</h2> Specimens were taken for macronutrient analysis from the same suction samples collected for invertebrate community identification. Representatives were taken from each family found in the community samples for which specimens were intact, in visually good condition and relatively clean of soil and other contaminants. If specimens were from a relatively uncommon family but unclean, soil and other surface contaminants were physically removed, and the specimen then momentarily dipped in water to remove remaining surface contaminants without greatly dislodging surface lipids. <a name="_Hlk173879439"></a>Macronutrient contents were determined following the MEDI protocol (Cuff, Wilder, et al., 2021; Cuff & Wilder, 2021) with minor alterations to account for the small size of most of the invertebrates processed (Cuff, 2021) and with the omission of exoskeletal measurement. During extraction, half volumes (i.e., 500 µl) of solvents were used. For the lipid assays, 15 µl of sulfuric acid was added for a 15 min incubation, followed by only 200 µl of vanillin reagent to increase the concentration and development of analyte for more accurate readings from smaller invertebrates. Lipid and protein standard series were diluted to 50% of the concentration specified in the original protocol (i.e., 0-1 mg ml-1). Carbohydrate assays used 140 µl of reagent with 30 min incubation at 92 °C followed by a further 30 min at room temperature. Carbohydrate standard series were diluted to 1 % of the concentrations specified in the original protocol (i.e., 0-0.02 mg ml-1) to ensure signals overcame the higher limit of detection relative to typical invertebrate carbohydrate content.  <a name="_Hlk173926384"></a>Mean macronutrient contents were calculated for each taxon and converted into proportions of the total macronutrient mass detected for each taxon (i.e., macronutrient values are given as % total macronutrient mass). Macronutrient data were allocated to each prey taxon. Where macronutrient data were not available for a family (due to no or very few individuals being present in vacuum samples), average data for that order were used.   <h2><a name="_Toc58843584"></a>Statistical analysis</h2> We have assessed nutritional dynamics through a combination of multivariate models and network-based null modelling. All analyses were conducted in R v.4.0.3 (R Core Team, 2020). To compare the nutritional balance of prey consumed by different spider groups, the mean nutrient contents of all prey consumed by each spider were calculated and compared using a multivariate linear model (MLM) via the ‘manylm’ command in mvabund (Wang et al., 2012). Differences were visualised using ternary plots via ‘ggtern’ (Hamilton & Ferry, 2018) and ‘ggplot2’ (Wickham, 2016). How spider diets differ between spider groups (genera, sexes and life stages) and how this is related to the nutrient contents of those prey was assessed using a fourth corner analysis (FCA). Fourth corner analyses assess how the relationship between the presence of species (or consumed resources in a dietary context) and environmental (or consumer) traits relates to species traits (or prey traits; (Brown et al., 2014). First, overall relationships between dietary composition and spider traits were assessed using a multivariate generalized linear model (MGLM) via the ‘manyglm’ command in the ‘mvabund’ package (Wang et al., 2012) with a binomial error family. These relationships were identified via likelihood ratio test using the ‘anova.manyglm’ command. A fourth corner analysis was performed using the ‘trait.glm’ command in mvabund with the ‘R’, ‘Q’ and ‘L’ matrices representing dietary detections of prey families in each spider, spider trait data (genus (a proxy for many unmeasured traits such as morphology), sex and life stage) and prey proportional macronutrient contents, respectively, with a binomial error family. Log-likelihood ratio tests were carried out using the ‘anova.traitglm’ command with 999 bootstrap iterations and Monte-Carlo resampling. The model was repeated with the least absolute shrinkage and selection operator (LASSO) applied, which is a method of penalised likelihood that reduces model terms to zero if they lack predictive power (i.e., do not reduce the Bayesian information criterion), thereby selecting models with greater predictive accuracy (Brown et al., 2014). To assess whether the proportions of mean prey nutrient contents deviated from those expected based on random foraging, null diets were simulated using network-based null models in ‘econullnetr’ (Vaughan et al., 2018) with the ‘generate_null_net’ command. The ‘generate_null_net_indiv’ function (Cuff, Windsor, et al., 2023) was used to generate null diets for each individual spider based on local prey communities determined via suction sampling. The mean prey macronutrient contents of spider diets were compared between expected and observed diets using a MLM in mvabund, and significant differences visually represented through a ternary plot using ggtern. To ascertain how differences between spider groups factor into any deviations from random nutrient intake, the difference in macronutrient proportions between expected and observed spider diets was also compared between spider genera, life stages and sexes in a MLM. To relate prey preferences of different spider groups to different prey and their macronutrient contents, observed interactions were compared against null models based on prey abundances using the ‘generate_null_net’ command in econullnetr (as above) for each of the spider groups and, separately, for individual spiders. Ternary plots representing preference effect sizes for prey of varying macronutrient contents were generated using the group-specific data via ‘ggtern’. The observed interactions of individual spiders were divided by the interactions expected in the null model; infinite values (i.e., zero interactions expected and more than zero observed) and NAs (e.g., no interactions expected nor observed) were converted to zero. These observed/expected values were compared between spider groups via permutational multivariate analysis of variance (PerMANOVA). These results were visualised by plotting mean standardised effect sizes for each spider genus, sex and life stage from the prey choice null models via ggplot2.

Collectives, associations, magazines and cultural initiatives_database_1

Collection of web pages of collectives, associations, magazines and cultural initiatives related to the Latin American world in Italy, as well as to gender topics.

Association of GDF-15 expression with immune parameter in a pan-cancer analysis

Immunotherapy with checkpoint blockers has significantly revolutionized the treatment landscape for many cancer patients. However, despite their success, checkpoint inhibitors have limitations that affect their effectiveness across a broader patient population. Soluble and cell-bound factors in the tumor microenvironment negatively impact cancer immunity. GDF15, a member of the TGF-β superfamily is associated with various physiological and pathological conditions, including cancer. Its overexpression in certain cancers has been linked to immune evasion. In this study we investigated the relationship between high GDF15 expression with various immune parameter in an in-silico analysis of 11,000 tumors from the TCGA database. Patients with non-small cell lung cancer and urothelial cancer was identified frequently GDF-15 immunosuppressed. Processed RNA sequencing data (TPM) obtained from firebrowse.org and the corresponding immune parameters were included in this dataset.

Neural Protein Associations with Parkinson's, Stroke, and Alzheimer's: Insights from UK Biobank Data

该数据集来自英国生物样本库 (UKB) 和英国生物样本库制药蛋白质组学项目 (UKB-PPP),包含来自 54,219 名参与者的全面蛋白质组学和人口统计信息。该数据集包括 2,941 种蛋白质分析物的测量值,代表 2,923 种独特蛋白质。选择了一组 217 种神经学相关蛋白和 10 种人口统计学和生活方式协变量进行分析。该研究侧重于帕金森病、中风和阿尔茨海默病,使用 ICD-10 代码确定病例。该数据集是研究蛋白质组学生物标志物与神经系统疾病之间关系的宝贵资源,可用于复制和进一步研究。

Data and code associated with Fernández_García et al 2024 Biogeosciences

These files supplement the Manuscript and Supplementary materials presented in the following paper: Palaeoecology of ungulates in northern Iberia during the Late Pleistocene through isotopic analysis of teeth  by Monica Fernández-Garcia, Sarah Pederzani, Kate Britton, Lucia Agudo-Pérez, Andrea Cicero, Jeanne Geiling, Joan Daura, Montserrat Sanz and Ana B. Marín-Arroyo under review in the Biogeosciences journal.

opencc-by-4.0Sep 2023View details →

Coat protein (CP) and trimmed replication-associated protein (Rep) amino acid alignments, phylogenetic analyses, and associated metadata for ICTV-approved begomovirus RefSeq species exemplars

DATA RETRIEVAL Annotated begomovirus coding sequences corresponding to each begomovirus species exemplar with a RefSeq accession number listed in the ICTV Virus Metadata Resource (VMR #18, 2021-10-19, <a href="https://ictv.global/vmr">https://ictv.global/vmr</a>) were downloaded from GenBank in protein FASTA file format. CP and Rep amino acid sequences were extracted and split into separate data sets for analysis. We confirmed the identity of misannotated ORF products by performing a BLAST search. For exemplar sequences missing ORF annotations (listed in metadata spreadsheet), ORFfinder (<a href="https://www.ncbi.nlm.nih.gov/orffinder/">https://www.ncbi.nlm.nih.gov/orffinder/</a>) was used to identify CP and Rep ORFs that were subsequently translated and added to each corresponding data set after BLAST confirmation. ALIGNMENTS Multiple sequence alignments were constructed using the MUSCLE method (Edgar, 2004) as implemented in MEGA 11 (Tamura et al., 2021) and manually corrected using AliView v1.26 (Larsson, 2014). After an initial alignment inspection, exemplars with either severely truncated (i.e., length < 50% of the average length of the protein) or very divergent (i.e., causing us to doubt protein homology) CP or Rep sequences were excluded from the data set. Due to the difficulties in aligning the Rep sequences at the N- and C- terminal ends, the Rep alignment was trimmed to eliminate all residues prior to the iteron related domain (i.e., the known Rep functional region closest to the Rep start (Arguello-Astorga & Ruiz-Medrano, 2001)) in the N-terminus and after a conserved geminivirus motif found near the C-terminus, which corresponds to where other circular, Rep-encoding single-stranded DNA viruses possess an arginine finger motif (Kazlauskas et al., 2019; Krupovic et al., 2020). In total, our CP and Rep data sets contained amino acid sequences from 432 begomovirus species exemplars that met our inclusion criteria. PHYLOGENETIC ANALYSIS Maximum likelihood (ML) trees were inferred with IQ-Tree v2.0.7 (Minh et al., 2020) using the best fitting substitution model identified by the built-in ModelFinder feature (Kalyaanamoorthy et al., 2017). Tree inference was performed with 3000 ultrafast bootstrap (UFBoot) replicates, a perturbation strength of 0.2 and a stopping rule requiring an iteration interval of 500 iterations between unsuccessful improvements to the local optimum. The -bnni flag was enabled to reduce the risk of overestimating branch supports with UFBoot due to severe model violations. The provided phylogenies in NEXUS format are midpoint-rooted and branches are colored based on traditional begomovirus geographic groupings: exemplars sampled in the Americas in orange and exemplars sampled in the 'Africa, Asia, Europe and Oceania' (AAEO) region in blue.  METADATA Metadata associated with each ICTV-approved species exemplar (n=445) – including country of isolation, geographic designation (i.e., AAEO/Americas), genome segmentation (i.e., monopartite/bipartite), presence/absence of V2/AV2 gene and length of genome/DNA-A segments – are included. Exemplars not incorporated into the other analyses are highlighted in red on the spreadsheet.

Data associated with "Microbiota-derived metabolites inhibit Salmonella virulent subpopulation development by acting on single-cell behaviors"

Data used for the publication Microbiota-derived metabolites inihibit Salmonella virulent subpopulation development by acting on single-cell behaviors.     all_hi_2307202.csv       Single-cell quantifications of Salmonella SPI-1 reporter cells grown in the presence of SCFAs. all_no_2307202.csv      Single-cell quantifications of Salmonella SPI-1 reporter cells grown in the absence of SCFAs. odmeasurements.csv     OD measurements of plate-reader assays of Salmonella SPI-1 reporter cells and controls grown in a range of SCFA conditions.   gfpmeasurements.csv    GFP measurements of plate-reader assays of Salmonella SPI-1 reporter cells and controls grown in a range of SCFA conditions.