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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
22,640 datasets
50 specific-pathogen free chicks were used in a study examining immune responses to Salmonella Enteritidis infection at 2 and 6 days post-infection. The dataset, published by Shuja Majeed on figshare under CC-BY-4.0, integrates spectral flow cytometry and single-cell RNA sequencing results. It reveals the expansion of innate-like cytotoxic intraepithelial lymphocytes as a key early defense mechanism.
Shuja Majeed published a dataset on figshare in 2026 containing single-cell transcriptomic profiling data from chickens. The data likely includes results from spectral flow cytometry and scRNA-seq of intraepithelial lymphocytes from 50 specific-pathogen free chicks, challenged with Salmonella Enteritidis. The study aimed to characterize innate-like cytotoxic T cell responses in the intestinal epithelium at 2 and 6 days post-infection.
A 1.7 MB document details experimental findings on the long non-coding RNA LUCAT1's role in promoting cancer stemness in head and neck squamous cell carcinoma. Authored by Yifan Wen and uploaded to figshare in June 2026, the data sheet describes assays including sphere-forming and limiting dilution tests. The study identifies LUCAT1 as a competing endogenous RNA that sponges miR-128, affecting downstream targets like BMI1.
A study of 13,402 Mycobacterium tuberculosis isolates, including 4,051 multidrug-resistant (MDR) and 1,044 single-drug resistant (SDR) strains, analyzed by Qiang Ji in 2026. Whole-genome sequencing was used to identify single nucleotide polymorphisms (SNPs) in respiratory chain genes associated with phylogenetic clustering and MDR development.
Qiang Ji's research dataset, published on figshare in May 2026, contains genomic analysis results from 13,402 Mycobacterium tuberculosis isolates. The study identified specific single nucleotide polymorphisms (SNPs) in respiratory chain genes associated with multidrug-resistant (MDR) and single-drug-resistant (SDR) isolates. The data likely includes mutation identifiers and their statistical associations with drug resistance and phylogenetic clustering.
13,402 isolates of Mycobacterium tuberculosis were analyzed using whole-genome sequencing to identify mutations associated with drug resistance. The study identified specific single nucleotide polymorphisms (SNPs) in respiratory chain genes linked to multidrug-resistant (MDR) and single-drug resistant (SDR) isolates. Author Qiang Ji published this data under a CC-BY-4.0 license on figshare in May 2026.
13,402 isolates of Mycobacterium tuberculosis were analyzed via whole-genome sequencing to identify mutations in respiratory chain genes linked to multidrug resistance. The study, authored by Qiang Ji and last updated in May 2026, used random forest and gradient boosting models to find significant associations between specific SNPs and the phylogenetic clustering and formation of MDR isolates. Results highlight specific mutations in genes like atpH, cydA, and qcrB.
A study analyzing 13,402 isolates of Mycobacterium tuberculosis to identify genetic mutations associated with drug resistance. The dataset, authored by Qiang Ji and last updated in May 2026, uses whole-genome sequencing and machine learning models to link specific single nucleotide polymorphisms in respiratory chain genes to multidrug-resistant and single-drug-resistant isolates.
13,402 isolates of Mycobacterium tuberculosis were analyzed via whole-genome sequencing to identify mutations linked to multidrug resistance. The dataset, authored by Qiang Ji and last updated in May 2026, contains results from random forest, gradient boosting, and generalized linear mixed models. It identifies specific single nucleotide polymorphisms in genes like atpH, cydA, and qcrB significantly associated with phylogenetic clustering and MDR formation.
A genomic analysis of 13,402 Mycobacterium tuberculosis isolates, including 4,051 multidrug-resistant (MDR) and 1,044 single-drug resistant (SDR) strains, conducted by Qiang Ji and last updated in May 2026. The study identifies specific single nucleotide polymorphisms (SNPs) in respiratory chain genes associated with the phylogenetic clustering and development of MDR tuberculosis. It uses whole-genome sequencing data analyzed with random forest, gradient boosting decision tree, and generalized linear mixed models.
A dataset of 13,402 Mycobacterium tuberculosis isolates analyzed via whole-genome sequencing to identify respiratory chain gene mutations linked to multidrug resistance. The study, authored by Qiang Ji and uploaded in 2026, identified specific single nucleotide polymorphisms (SNPs) significantly associated with phylogenetic clustering and the formation of multidrug-resistant (MDR) and single-drug-resistant (SDR) isolates.
13,402 isolates of Mycobacterium tuberculosis were analyzed via whole-genome sequencing. The study identified specific single nucleotide polymorphisms (SNPs) in respiratory chain genes associated with multidrug-resistant (MDR) and single-drug resistant (SDR) isolates. The dataset was created by Qiang Ji and last updated in May 2026.
13,402 isolates of Mycobacterium tuberculosis were analyzed via whole-genome sequencing. The study, authored by Qiang Ji and last updated in May 2026, identified specific single nucleotide polymorphisms (SNPs) in respiratory chain genes significantly associated with multidrug-resistant (MDR) and single-drug resistant (SDR) isolates.
13,402 isolates of Mycobacterium tuberculosis were analyzed via whole-genome sequencing to identify mutations linked to drug resistance. The study, authored by Qiang Ji and last updated in May 2026, identified specific SNPs in genes like atpH, cydA, and qcrB significantly associated with multidrug-resistant (MDR) and single-drug resistant (SDR) isolates. These findings provide insights into the genetic basis of drug resistance clustering and development.
A study analyzing 13,402 Mycobacterium tuberculosis isolates to identify gene mutations associated with multidrug resistance. Whole-genome sequencing was performed, and machine learning models identified specific single nucleotide polymorphisms (SNPs) in respiratory chain genes linked to phylogenetic clustering and MDR development. The dataset was authored by Qiang Ji and last updated in May 2026.
Wenlong Gong assembled and annotated the first high-quality mitochondrial genome of Festuca pratensis, a forage grass. The genome has a multichromosomal structure totaling 449,613 base pairs, containing 51 genes, and was analyzed for structure, selection pressure, and phylogeny. The dataset was last updated on 2026-05-13.
Rozhin Penjweini's dataset from figshare, last updated 2026-05-29, provides single-cell imaging data on mitochondrial metabolism and remodeling during myogenic differentiation. The 882.7 MB collection includes fluorescence and redox imaging data to study intracellular oxygenation, ATP production, and mitochondrial dynamics. It offers a single-cell perspective on metabolic shifts and spatial organization in a murine skeletal muscle cell model.
1,571 peer-reviewed articles and reviews on gene editing therapies for human genetic diseases were analyzed from 2005 to 2025. The bibliometric study by Xinhao Zhou, published on figshare in 2026, maps the field's evolution from engineered nucleases to CRISPR and precision translation. It identifies leading disease targets, institutional hubs, and emerging frontiers like base editing and AI-assisted design.
1,571 peer-reviewed articles and reviews on gene editing therapies for human genetic diseases, published between 2005 and 2025. The data was analyzed by Xinhao Zhou using CiteSpace and VOSviewer to map collaboration networks and thematic clusters. Publication growth is described in three phases: engineered nucleases (2005–2012), CRISPR revolution (2013–2018), and precision translation (2019–2025).
Transport Facility Line is a geospatial dataset from Spatial Services, a business unit of the Department of Customer Service NSW. It defines linear transport facilities, specifically wharves and launching ramps, across the state of New South Wales. The dataset was initially published in 2020 and is part of the state's Foundational Spatial Data Framework (FSDF).