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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
23,258 datasets
RNA sequencing data from Mammary Paget’s disease and extramammary Paget’s disease tissues, used to identify prognostic genes. The dataset, created by Ying Chen and last updated in May 2026, includes expression levels for hub genes KLF13 and TIA1, validated in internal and external patient cohorts. A risk-score model based on these genes was constructed to stratify patients by recurrence risk.
RNA sequencing data from Mammary and Extramammary Paget's disease tissues identifies KLF13 and TIA1 as prognostic genes. The dataset supports a risk-score model validated in internal and external patient cohorts. Author Ying Chen published the data under a CC-BY-4.0 license on figshare in 2026.
RNA sequencing of Mammary and Extramammary Paget's disease tissues identified KLF13 and TIA1 as hub genes associated with recurrence. A risk-score model based on these genes stratified patients into high- and low-risk groups, validated in internal and external cohorts. The dataset, authored by Ying Chen and last updated in 2026, includes gene expression data supporting these findings.
Proteomic and enzymatic activity data for the p1/s1 nuclease cluster in Leishmania major parasites. The dataset was generated by Stella M. Schmelzle using quantitative proteomics, immunological assays, and genome editing methods. It was last updated on 2026-05-21.
Stella M. Schmelzle's dataset characterizes the p1/s1 cluster of 3'-nucleotidases/nucleases in Leishmania major parasites. It includes proteomic data from quantitative proteomics, ecto-enzymatic activity measurements, and results from a diCre-based inducible knockout system. The dataset was last updated on 2026-05-21 and is available as a 4.5 MB XLSX file under a CC-BY-4.0 license.
Integrated bioinformatics analysis identifies common differentially expressed genes between Influenza A (H1N1) infection and Guillain-Barré Syndrome (GBS). The 17.6 MB dataset, authored by Ye Deng and last updated in May 2026, contains results from enrichment and protein-protein interaction network analyses. It highlights TLR4, TNF, and ITGAM as key hub genes potentially linking the immunopathology of both conditions.
Bathymetry data for the Portsea Hole area in Port Phillip Bay, Victoria. The survey was acquired by Deakin University Marine Mapping lab over two days in January 2018 using a Kongsberg EM2040c sonar system. It was collected as part of a Parks Victoria project to map marine parks within Victorian state waters.
A 875.9 KB PDF presents results from genetic analyses examining bidirectional causal links between common mental disorders and asthma. The study by Zian Yan, last updated in April 2026, used linkage disequilibrium score regression and bidirectional two-sample Mendelian randomization on summary statistics from large-scale Genome-Wide Association Studies in European populations. It found major depressive disorder is a predisposing factor for asthma, while anxiety disorders and asthma do not show a significant causal relationship.
A three-day survey from 18/01/2018 to 21/01/2018 collected by Deakin University Marine Mapping lab. The data maps the locations of drift algae within Port Phillip Bay, Australia, using a Kongsberg EM2040c sonar system. It was collected as part of a collaborative program with the University of Melbourne.
3.1 MB of supplementary material from a Drosophila study on the gut-brain axis in autism spectrum disorder. The PDF includes results from microbiota-based interventions like probiotic supplementation and fecal transplants on social behavior in Kdm5-deficient flies. The work was posted by figshare admin karger and last updated in May 2026.
Deakin University Marine Mapping lab collected bathymetry data in Port Phillip Bay on December 13, 2021. The survey was conducted from the Motor Vessel Yolla using a Kongsberg EM2040c sonar system. These data were acquired to assess the movement of sediment through time.
Proteomics data compares the quantitative performance of a 2-mercaptoethanol/DMSO workflow against conventional iodoacetamide treatment for cysteine alkylation. Mouse liver proteomes were processed and analyzed via LC-MS/MS, resulting in improved peptide and protein quantification reproducibility. The dataset was authored by Arisa Suto and published on figshare in May 2026.
Arisa Suto's dataset compares proteomics workflows for cysteine alkylation, published on figshare in May 2026. It contains quantitative proteomics data from mouse liver samples processed with either a novel 2-mercaptoethanol/DMSO treatment or a conventional iodoacetamide method, and from ovarian clear cell carcinoma samples. The data supports the finding that the 2-ME/DMSO workflow increased cysteine-modified peptide counts by 1.6- to 1.9-fold and improved quantitative reproducibility.
6.7 MB of proteomics data compares a novel 2-mercaptoethanol/DMSO workflow against conventional iodoacetamide treatment for cysteine alkylation. The dataset, authored by Arisa Suto and last updated in May 2026, likely contains quantitative performance metrics from LC-MS/MS analysis of mouse liver proteomes and ovarian clear cell carcinoma samples.
6.3 MB of proteomics data compares the quantitative performance of a 2-mercaptoethanol/DMSO workflow against conventional iodoacetamide treatment. Mouse liver proteomes were processed and analyzed via LC-MS/MS, showing improved peptide and protein quantification reproducibility. The dataset, authored by Arisa Suto and last updated in May 2026, includes results applied to ovarian clear cell carcinoma.
World Bank data on Australia's external debt stocks and flows. The dataset likely contains quarterly external debt statistics for high-income countries and emerging markets, as well as public sector debt data on valuation methods and instruments. Data are gathered from national statistical organizations, central banks, and multilateral institutions.
A dataset from a preliminary investigation of 68 pregnant women, linking objectively measured physical activity from Fitbit monitors to gut microbiota composition via 16S rRNA sequencing of third-trimester stool samples. The data includes alpha and beta diversity metrics, differential abundance testing results, and was published by Sara Santarossa on figshare in 2026. The study found associations between sedentary time and specific microbial abundances.
68 pregnant women with Fitbit activity data and third-trimester stool 16S rRNA sequencing. The data shows a median of around 5000 steps per day and a majority of activity minutes classified as sedentary. This preliminary investigation by Sara Santarossa was last updated in April 2026.
A multi-omic dataset from a study on Camellia oleifera fruit. It integrates transcriptomics, metabolomics, and biochemical assays from seed-kernel tissues collected at 0, 12, and 24 hours of postharvest warm conditioning. The dataset was authored by Jianwen Wu and last updated on 2026-04-23.
A study evaluates six deep learning models for automatic clinical target volume segmentation in whole-breast radiotherapy using 961 planning CTs. The research leverages top-performing models to construct probability maps, aiming to improve consistency and mitigate bias in clinical predictions. Supported by the Italian Ministry of Health (CCM 2024), the dataset is a 2.9 MB PDF published by Cecilia Riani on figshare.