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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
23,228 datasets
Gene expression data from the GEO database (GSE52804, GSE6858, GSE41665) was analyzed to identify shared mechanisms in combined allergic rhinitis and asthma syndrome (CARAS). The study identified 56 differentially expressed genes and validated findings in a murine model. The dataset, authored by Zhuiyue Wang and last updated on 2026-05-15, includes analysis files in TIF, DOCX, and XLSX formats totaling 16.0 MB.
Clinical and molecular data were generated for a patient diagnosed with osteosarcoma in November 2022. The dataset includes longitudinal single-cell and bulk RNA/DNA sequencing, spatial transcriptomics, residual disease testing, flow cytometry, imaging, and clinical lab results. It is shared by the Rare Cancer Research Foundation via AWS Open Data to advance cancer research.
Continuity of Earth Observation Data for Australia - Operational Requirements to 2015 for Lands, Coasts and Oceans is a document outlining the operational needs for satellite-based Earth observation data in Australia. It was published by the Australian Ocean Data Network and last updated on 2026-06-04. The description notes the data's wide use by government agencies, research institutions, and the private sector for monitoring a long coastline and natural disasters.
A methodological paper and associated materials proposing a novel procedure for variable selection in high-dimensional matrix-valued data. The work, authored by Lei Yan and last updated in May 2026, includes a PDF document, markdown files, and a ZIP archive totaling 14.6 MB. The method is designed to control the false discovery rate for simultaneous row and column selection without requiring p-value computation.
Research materials accompany a study on institutional learnability and community knowledge-building in smart region governance. The dataset includes structured observation documentation, anonymized stakeholder survey results, and analytical coding materials from the Tokaj Wine Region, Hungary, spanning 2023 to 2025. It was authored by Tamás Dr. Köpeczi-Bócz and published on figshare in 2026.
A genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) maps transcriptional phenotypes associated with 11,739 perturbed genes across more than 2.5 million single cells. The dataset was generated by Yesh Doctor and published on figshare in May 2026. It includes expressed genome-wide and pilot screen datasets for chromatin modifiers and metabolic enzymes.
A 1.15 Gb chromosome-level genome assembly for the threatened marbled teal (Marmaronetta angustirostris), generated by Joaquin Ortego and published on figshare in 2026. The assembly was created using PacBio HiFi long reads and Omni-C data, with 97.16% anchored into 36 chromosome-scale scaffolds. It contains 16,048 predicted protein-coding genes and supports genome-wide conservation analyses.
Gun-Hwi Yeon provides a dataset of vectors and primers used in a metabolic engineering study. The dataset, shared on figshare, details genetic constructs engineered in Escherichia coli to produce the rare sugar l-fuculose. The final engineered strain achieved a production titer of 50.25 ± 4.30 mg/L.
Top Enriched GO Biological Processes Identified by Enrichr Based on Cancer-Associated Gene Set. The dataset is a 5.5 KB XLS file published by Nosayba Al-Damook on figshare under a CC-BY-4.0 license. It was last updated on June 4, 2026.
A 5.5 KB Excel file lists the top enriched KEGG pathways identified from a selected gene set using the Enrichr tool. The dataset was authored by Nosayba Al-Damook and last updated on June 4, 2026. The full results are referenced in S3 Table of a related PLOS ONE article.
Jianming Hu published data on genomic regions associated with stripe rust resistance in wheat. The dataset includes results from BSA-seq and QTL mapping using a 120K SNP array, identifying a key QTL on chromosome 3A explaining 20.10%–25.21% of phenotypic variance. The data was last updated on 2026-04-22.
A 16.3 KB dataset from figshare, last updated on 2026-04-22, documents genomic regions associated with stripe rust resistance in wheat. Author Jianming Hu identified a quantitative trait locus (QTL) on chromosome 3A, QYr.cib-3AS, explaining 20.10%–25.21% of phenotypic variance. The data supports marker-assisted breeding by detailing candidate genes and the enhanced resistance from pyramiding QYr.cib-3AS with YrT14.
Two genomic regions associated with wheat stripe rust resistance were identified using BSA-seq and QTL mapping with a 120K SNP array. The QTL QYr.cib-3AS explained 20.10%–25.21% of phenotypic variance and was delimited to an interval flanked by markers dCAPS-78 and dCAPS-83. The dataset, authored by Jianming Hu and last updated in April 2026, provides a foundation for marker-assisted breeding and gene cloning.
Two genomic regions associated with stripe rust resistance in wheat were identified using BSA-seq and QTL mapping with a 120K SNP array. The QTL QYr.cib-3AS on chromosome 3A explained 20.10%–25.21% of phenotypic variance and was delimited to a specific interval containing 48 high-confidence genes. This dataset, authored by Jianming Hu and last updated in April 2026, provides a foundation for cloning resistance genes and developing elite wheat cultivars.
Supplementary file 2 from a study identifying genomic regions for wheat stripe rust resistance. The research, authored by Jianming Hu and last updated in April 2026, used BSA-seq and QTL mapping with a 120K SNP array to locate a key resistance QTL, QYr.cib-3AS, and candidate genes. The findings are intended to support the development of durable, resistant wheat cultivars.
A 225.3 KB DOCX file contains supplementary data from a study identifying genomic regions for stripe rust resistance in wheat. The research, authored by Jianming Hu and last updated on 2026-04-22, identified a QTL on chromosome 3A explaining 20.10%–25.21% of phenotypic variance and nominated two candidate genes. The findings aim to support the development of resistant wheat cultivars.
Two genomic regions associated with stripe rust resistance in wheat were identified, including a QTL on chromosome 3A explaining 20.10%–25.21% of phenotypic variance. The research, authored by Jianming Hu and last updated in April 2026, provides a foundation for marker-assisted breeding and gene cloning. The dataset is a 44.0 KB DOCX file from figshare, licensed under CC-BY-4.0.
Two genomic regions, including the QTL QYr.cib-3AS, were identified as associated with stripe rust resistance in wheat. The study, authored by Jianming Hu and last updated in April 2026, provides supporting data from BSA-seq and QTL mapping using a 120K SNP array. The pyramiding of QYr.cib-3AS with YrT14 increased resistance by 77.20%, and two candidate genes were proposed.
Table 1_The pyramiding of QYr.cib-3AS and YrT14 enhances wheat resistance to stripe rust.docx contains data from a study identifying quantitative trait loci for stripe rust resistance in wheat. The dataset, authored by Jianming Hu and last updated on 2026-04-22, includes results from BSA-seq and QTL mapping using a 120K SNP array. It reports a QTL on chromosome 3A explaining 20.10%–25.21% of phenotypic variance and a 77.20% increase in resistance from pyramiding two loci.
Table 2_The pyramiding of QYr.cib-3AS and YrT14 enhances wheat resistance to stripe rust.docx contains data from a study identifying quantitative trait loci (QTL) for stripe rust resistance in wheat. The dataset was authored by Jianming Hu and last updated on 2026-04-22. It includes results from BSA-seq and QTL mapping using a 120K SNP array, detailing a major QTL on chromosome 3A and its pyramiding effect with another resistance locus.