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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
23,464 datasets
This dataset compares the performance of the FoMo feature selection method against the final classifier developed on the 55-feature set versus the 38-feature set from the original study. It reports the initial and final (post feature pruning and oversampling) modeling results and compares them to FoMo v1.0 and v1.3. A difference column compares performance between v1.3 and the final classifier from the 55-feature set.
5.5 KB of tabular data summarizing experimental trials used in a research paper. The table includes columns for the number of trials per condition, target items collected, and conditions analyzed. Alasdair D. F. Clarke uploaded the data to figshare on 2026-05-12.
A small (5.5 KB) Excel file containing parameter values used for simulations in a theoretical study. The data was authored by Ying-Jie Wang and last updated on 2026-05-26. Parameter values were based on or taken from a cited reference (72).
Petra Bíró provides a mapping of optode and electrode locations to hemispheres and likely cortical regions. The dataset, last updated in May 2026, includes positions AF7, AF8, F5, and F6, with cortical regions estimated using the fOLD toolbox v2.2 and the Brodmann atlas. Positions AFp3, AFp4, AFF3h, and AFF4h were assigned based on spatial proximity to neighboring electrodes.
A dataset from 2026 by Minhua Cao, shared via figshare under a CC-BY-NC-4.0 license. It contains results from a covalent tagging strategy used to directly identify bacterial transmembrane proteins involved in siderophore-mediated iron uptake. The data likely includes protein identification results from experiments using designed photo-cross-linker probes on organisms like Pseudomonas aeruginosa and Escherichia coli.
A collection of protein structure files (PDB format) detailing covalent tagging strategies for transmembrane transport proteins. The dataset, authored by Minhua Cao and last updated in May 2026, includes co-crystal structures of designed probes bound to transporters like FoxA, FpvB, FhuA, and FhuE in bacteria such as Pseudomonas aeruginosa and Escherichia coli.
Covalent photo-cross-linker probes DFO-azir-05 and DFO-azir-06 were designed to directly tag ferrioxamine-binding transmembrane transporters in bacteria. The dataset, published by Minhua Cao on figshare in 2026, contains PDB files of co-crystal structures, including Fe-D1 bound to Pseudomonas aeruginosa's FoxA transporter. This approach identified transporters like FoxA, FpvB, FhuA, and FhuE, and suggested a new role for BtuB.
Proteomic profiles from plasma small extracellular vesicles of 76 obese, chemotherapy-naïve breast cancer patients and 36 obese controls. The dataset, shared by Amr Ahmed WalyEldeen on figshare under CC-BY-4.0, identifies Fibronectin 1 and von Willebrand Factor as candidate markers associated with diagnosis and therapy response. Last updated on May 5, 2026, the 6.6 MB XLSX file contains results from nanoLC-MS/MS analysis.
76 plasma samples from obese, chemotherapy-naïve breast cancer patients (stages I–III) and 36 age-matched obese controls were analyzed via nanoLC-MS/MS proteomics. The dataset identifies Fibronectin 1 and von Willebrand Factor as candidate markers in small extracellular vesicles, with validation linking them to aggressive triple-negative breast cancer. Author Amr Ahmed WalyEldeen published this 7.1 MB XLSX file on figshare under a CC-BY-4.0 license, last updated on 2026-05-05.
Plasma small-extracellular vesicles from 76 obese, chemotherapy-naïve breast cancer patients and 36 obese controls were analyzed via nanoLC-MS/MS proteomics. The dataset, shared by Amr Ahmed WalyEldeen on figshare under CC-BY-4.0, identifies Fibronectin 1 and von Willebrand Factor as candidate markers associated with diagnosis and therapy response. Last updated in May 2026, the 6.8 MB Excel file contains raw proteomic results.
Raw proteomics results from plasma small extracellular vesicles (EVs) of 76 obese, chemotherapy-naïve breast cancer patients and 36 age-matched obese controls. The dataset, created by Amr Ahmed WalyEldeen and last updated in May 2026, identifies candidate protein markers like Fibronectin 1 and von Willebrand Factor. It is a small dataset of 311.4 KB stored in an XLSX file.
76 obese, chemotherapy-naïve breast cancer patients and 36 age-matched obese controls contributed plasma samples for small extracellular vesicle (EV) analysis. The dataset contains raw proteomics results from nanoLC-MS/MS analysis, identifying candidate markers like Fibronectin 1 and von Willebrand Factor. It was authored by Amr Ahmed WalyEldeen and last updated on 2026-05-05.
25 participants underwent structured art healing sessions while their brain activity and psychological state were recorded. The dataset contains synchronized 64-channel EEG recordings and anxiety scale scores from university students, supporting research on art-based anxiety interventions. It was created by Chenyi Chen and last updated in May 2026.
A 2026 study by Hanan Alkabkabi identified genomic regions associated with bolting in spinach. The dataset contains results from a genome-wide association study (GWAS) and genomic prediction analysis on a panel of 295 United States Department of Agriculture (USDA) accessions, using 16,563 high-quality SNPs. It reports seven significant loci, a major-effect locus on chromosome 6 explaining 21.18% of phenotypic variance, and genomic prediction accuracy.
A 2026 study by Hanan Alkabkabi provides genomic data on bolting timing in spinach. The dataset includes results from a genome-wide association study (GWAS) of 295 USDA spinach accessions, identifying seven significant loci and candidate genes. It also contains genomic prediction accuracy results for molecular breeding applications.
A study analyzing the association between NDRG4 gene methylation in peripheral blood leukocytes and gastric cancer risk, chemotherapy efficacy, and patient prognosis. The dataset includes results from a two-phase case-control study with 310 gastric cancer patients and 300 controls, along with bioinformatics analyses from TCGA and GEO databases. The research was authored by Zhan Li and last updated on 2026-04-27.
A two-phase case-control study of 310 gastric cancer patients and 300 controls analyzed the association between NDRG4 gene methylation in peripheral blood leukocytes and gastric cancer risk, chemotherapy efficacy, and prognosis. The dataset includes results from bioinformatics analysis of NDRG family genes using TCGA and GEO databases, as well as comparisons of methylation levels across rs7202037 SNP genotypes for 280 patients. The data was uploaded by Zhan Li to figshare and last updated on 2026-04-27.
310 gastric cancer patients and 300 controls were analyzed in a two-phase case-control study to investigate the association between NDRG4 gene methylation in peripheral blood leukocytes and gastric cancer risk, chemotherapy efficacy, and prognosis. The dataset, authored by Zhan Li and last updated on 2026-04-27, includes results from bioinformatics analyses of TCGA and GEO databases and methylation comparisons across rs7202037 SNP genotypes. The file is a 19.0 KB DOCX document.
A 2026 study by Zhan Li analyzes the association between NDRG4 gene methylation in peripheral blood leukocytes and gastric cancer. The dataset includes results from a two-phase case-control study with 310 gastric cancer patients and 300 controls, along with bioinformatics analyses from TCGA and GEO databases. It reports odds ratios for cancer risk and associations with chemotherapy efficacy and patient survival.
A two-phase case-control study of 310 gastric cancer patients and 300 controls analyzed the association between NDRG4 gene methylation in peripheral blood leukocytes and cancer risk, chemotherapy efficacy, and prognosis. The dataset includes results from bioinformatics analyses of NDRG family genes using TCGA and GEO databases, as well as comparisons of methylation levels across different rs7202037 SNP genotypes. The data was authored by Zhan Li and last updated on 2026-04-27.