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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
22,726 datasets
Six consensus predictors—smoking, diabetes duration, wound depth, elevated C-reactive protein, elevated procalcitonin, and hypoalbuminemia—were used to build a random forest model predicting infection risk in chronic wounds. The model was developed using a primary cohort of 500 patients from two tertiary hospitals in China and validated on an external cohort of 300 patients. Yang Jiang published this research on figshare in May 2026, deploying the model as a free web calculator for clinical use.
Chiara Pollicardo's dataset provides reference values for the human gut microbiome derived from 250 fecal samples analyzed using a CE-certified 16S rRNA bacterial profiling assay. The data, last updated in 2026, establishes a baseline for a Southern European population characterized by a Mediterranean diet. It represents a step towards standardized clinical interpretation of microbiota imbalances.
A bibliometric and text-mining analysis of 9,628 scientific articles from 2004 to 2024, sourced from Scopus and validated against Web of Science and PubMed. The study was conducted by Alejandro I. Trejo-Castro and provides an overview of the evolution of lipidomics and metabolomics in human disease research. It identifies leading journals, authors, countries, and thematic trends within the field.
Alejandro I. Trejo-Castro's dataset contains bibliometric and text-mining analysis results for 9,628 scientific articles on lipidomics and metabolomics from 2004 to 2024. The data was sourced from Scopus and validated against Web of Science and PubMed, identifying trends in journals, authors, countries, and research themes. The file was last updated on May 19, 2026.
9,628 scientific articles from 2004 to 2024 were harmonized and analyzed to map the evolution of lipidomics and metabolomics. The analysis, conducted by Alejandro I. Trejo-Castro, identified a 32.6% annual growth rate in the field and leading topics like Alzheimer’s disease and breast cancer. Data was sourced from Scopus and validated against Web of Science and PubMed.
9,628 scientific articles from 2004 to 2024 were harmonized and analyzed using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts. The analysis, conducted by Alejandro I. Trejo-Castro, identifies productive journals, authors, countries, and thematic structures in lipidomics and metabolomics research. The field shows rapid expansion with an annual growth rate of 32.6%.
9,628 scientific articles from 2004 to 2024 were harmonized and analyzed using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts. The dataset, created by Alejandro I. Trejo-Castro and last updated in May 2026, provides a bibliometric overview of lipidomics and metabolomics research in human diseases. It identifies productive journals, authors, countries, and thematic trends, with cross-validation from Web of Science and PubMed.
9,628 scientific articles on lipidomics and metabolomics from 2004 to 2024, harmonized and analyzed by Alejandro I. Trejo-Castro. The dataset was created using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts, with data sourced from Scopus and validated against Web of Science and PubMed. It captures the field's evolution, including key journals, authors, countries, and thematic trends.
Alejandro I. Trejo-Castro's analysis provides bibliometric and text-mining insights into lipidomics and metabolomics research from 2004 to 2024. The dataset likely contains quantitative trends and semantic mapping derived from 9,628 articles sourced from Scopus, Web of Science, and PubMed. It was last updated on May 19, 2026.
Alejandro I. Trejo-Castro's dataset provides a bibliometric and text-mining analysis of 9,628 scientific articles on lipidomics and metabolomics in human disease from 2004 to 2024. The data was harmonized and analyzed using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts. It was last updated on 2026-05-19.
9,628 scientific articles on lipidomics and metabolomics in human disease were analyzed from 2004 to 2024. The dataset, created by Alejandro I. Trejo-Castro, shows the field expanded at an annual growth rate of 32.6%. It identifies leading journals, authors, countries, and emerging research themes like artificial intelligence and multi-omics integration.
A bibliometric analysis of 9,628 scientific articles on lipidomics and metabolomics from 2004 to 2024, sourced from Scopus and validated against Web of Science and PubMed. The dataset was created by Alejandro I. Trejo-Castro and last updated in May 2026. It tracks the rapid expansion of the field, with a reported annual growth rate of 32.6%, and identifies leading countries, journals, and emerging research themes.
1,844 participants from Kai Luan General Hospital were genotyped for the QDPR rs3733570 polymorphism. The study found the AA genotype was associated with increased risk of type 2 diabetes and, in carriers with dyslipidemia, diabetic kidney disease. Author Minda Dong published this data on figshare under a CC-BY-4.0 license in 2026.
A 2026 study by Kara M. Joseph analyzed PFAS burdens in northern elephant seals using LC-IMS-HRMS. The dataset includes quantitative measurements from plasma of 14 mother-pup pairs and milk from 9 mothers, identifying 27 PFAS compounds. Concentrations in milk and pup plasma exceeded relevant human-based exposure thresholds, indicating pronounced early-life accumulation.
Behavioral and morphometric data from adult Swiss male mice, a naturally anxious strain. The dataset includes measurements of anxiety index, ejaculation latency, ejaculation number, and other andrological characteristics, collected by Itztli Trejo-Sánchez. The data was last updated on 2026-05-28.
Lingling Liu published transcriptomic data analysis on 2026-06-04. The dataset supports a study identifying hyaluronic acid mediated motility receptor (HMMR) as a prognostic biomarker in oral squamous cell carcinoma. It integrates data from the TCGA OSCC cohort and two GEO cohorts (GSE37991, GSE41613).
493 placental samples with DNA methylation data and histopathologic characterization were used to evaluate the eoPRED score. The score was developed by Hannah J. Illing and is associated with early-onset preeclampsia and maternal vascular malperfusion pathology. The dataset was last updated on June 4, 2026.
A 30.5 KB dataset from a multi-cohort bioinformatics analysis, last updated on 2026-06-04. It contains results from a study by Lingling Liu integrating transcriptomic data from the TCGA OSCC cohort and two GEO cohorts (GSE37991, GSE41613). The data likely includes differential expression, survival analysis, and immune correlation results for the HMMR gene and other prognostic markers in oral cancer.
A dataset of 493 placental samples with DNA methylation scores and histopathologic characterization. The eoPRED score is associated with early-onset preeclampsia and maternal vascular malperfusion pathology. The data was contributed by Hannah J. Illing and last updated on 2026-06-04.
245 common differentially expressed genes were identified across three cohorts of oral squamous cell carcinoma (OSCC) patients. Lingling Liu integrated transcriptomic data from the TCGA OSCC cohort and two GEO cohorts (GSE37991, GSE41613) to analyze the prognostic biomarker HMMR. The analysis, last updated in June 2026, links HMMR overexpression to advanced tumor stage, poor survival, and immune cell infiltration.