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Overview of the harmonization process and quality metrics. (A) Simplified w... Open Access
Published: 22 May 2026
Figure 1
Overview of the harmonization process and quality metrics. (A) Simplified workflow showing the major steps in metadata harmonization. The harmonization process begins with ‘Original Metadata’ from heterogeneous research-driven omics data sources. During the ‘Schema Mapping’ step, conceptually simila
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Improved metadata quality for cBioPortalData. (A) The left bar (‘Original M... Open Access
Published: 22 May 2026
Figure 3
Improved metadata quality for cBioPortalData . (A) The left bar (‘Original Metadata’) represents 673 original attributes selected for harmonization based on completeness, clinical relevance, and prevalence across studies. Colours indicate which harmonized attribute(s) each original field contribute
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Improved metadata quality for curatedMetagenomicData. (A) Attribute compres... Open Access
Published: 22 May 2026
Figure 2
Improved metadata quality for curatedMetagenomicData . (A) Attribute compression. The left bar (‘Original Metadata’) displays 142 original attributes colour-coded by the harmonized attribute(s) into which they were consolidated. The right bar (‘Curated Metadata’) shows the resulting 66 harmonized a
Journal Article
Large-scale manual curation and harmonization of metadata from metagenomic and cancer genomic repositories: challenges and solutions Open Access
Database, Volume 2026, 2026, baag027, https://doi.org/10.1093/database/baag027
Published: 22 May 2026
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Repository-wide statistics enabled by harmonized metadata. (a) Comprehensiv... Open Access
Published: 22 May 2026
Figure 4
Repository-wide statistics enabled by harmonized metadata. (a) Comprehensive ancestry distribution across cBioPortal studies. UpSet plot showing the distribution of 134 032 samples from 218 studies across eight standardized ancestry categories and their combinations. The top bar chart displays inter
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RNA–miRNA correlation networks specific to four metastatic sites of BLCA. (... Open Access
Published: 19 May 2026
Figure 1
RNA–miRNA correlation networks specific to four metastatic sites of BLCA. (A) Subnetworks show top-ranked RNA–miRNA pairs (P .001) specific to bone (blue), liver (yellow), lung (purple), and lymph node (red) metastases. Yellow nodes in the networks represent miRNAs and cyan nodes represent RNAs.
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Lung metastasis associated RNA–miRNA pairs common to different primary canc... Open Access
Published: 19 May 2026
Figure 2
Lung metastasis associated RNA–miRNA pairs common to different primary cancer types. The orange bars in the left panel show the number of RNA–miRNA pairs from each primary cancer type. The blue bars in the top panel show the number of common pairs in each combination of primary cancer types, while t
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Example of using MetaCancerDB. (A) The Cancer Type panel visualized in a pi... Open Access
Published: 19 May 2026
Figure 3
Example of using MetaCancerDB. (A) The Cancer Type panel visualized in a pie chart shows the primary cancer types in MetaCancerDB. The number of samples of each cancer type is displayed when users move a mouse over a cancer type. When users click a primary cancer type, a table of metastatic sites of
Journal Article
TEITbase: a database for transposable element (TE)-initiated transcripts in human cancers Open Access
Database, Volume 2026, 2026, baag025, https://doi.org/10.1093/database/baag025
Published: 19 May 2026
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Detection of TE-initiated transcripts. (A) Pipeline designed to identify TE... Open Access
Published: 19 May 2026
Figure 1
Detection of TE-initiated transcripts. (A) Pipeline designed to identify TE-initiated transcripts by using a deep learning model. (B) RAMPAGE and CapTrap-seq signals of the PRKACB gene, along with TSS predictions of our method. (C) The distances to the true TSSs of predicted TSSs from our method (
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Schematic of the pipeline used in the construction of the FuNGI database. F... Open Access
Published: 19 May 2026
Figure 1
Schematic of the pipeline used in the construction of the FuNGI database. Fungal proteomes from UniProtKB were analysed to predict nucleolar localization signals (NoLSs) using the NoD server, nuclear localization signals (NLSs) using NLStradamus, and subcellular localization using WoLF PSORT. A comp
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Overview of nucleolar localization predictions. (a) Summary statistics of t... Open Access
Published: 19 May 2026
Figure 2
Overview of nucleolar localization predictions. (a) Summary statistics of the FuNGI database. The total number of proteomes analysed from each fungal phylum is indicated in square brackets. Horizontal bars represent the proportion of proteins predicted to contain nucleolar localization signals (NoLS
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Snapshot of user interface for exploring proteomes in FuNGI. (a) The Proteo... Open Access
Published: 19 May 2026
Figure 3
Snapshot of user interface for exploring proteomes in FuNGI. (a) The Proteomes page lists UniProt proteomes available in the database, allowing users to control the number of entries displayed per page and search for specific species. (b) The Taxonomy Browser enables users to search fungal proteomes
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Snapshot of individual proteome information page in FuNGI. (a) Proteome Det... Open Access
Published: 19 May 2026
Figure 4
Snapshot of individual proteome information page in FuNGI. (a) Proteome Details: metadata for the selected fungal species, including UniProt accession, taxonomy, strain name, gene and protein counts, and hierarchical lineage. (b) Summary and Statistics: a pie chart showing the categorization of prot
Journal Article
MetaCancerDB: a database of site-specific RNA–miRNA correlations in cancer metastasis Open Access
Database, Volume 2026, 2026, baag026, https://doi.org/10.1093/database/baag026
Published: 19 May 2026
Journal Article
FuNGI: Fungal Nucleolar Genomic Inventory—a comprehensive database of fungal proteins with predicted nucleolar localization signals Open Access
Database, Volume 2026, 2026, baag023, https://doi.org/10.1093/database/baag023
Published: 19 May 2026
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Applications of TEITbase. (A) The homepage of TEITbase. (B) Box plot showin... Open Access
Published: 19 May 2026
Figure 3
Applications of TEITbase. (A) The homepage of TEITbase. (B) Box plot showing the promoter activity of L1HS in TCGA tumours (top) and GTEx normal tissues (bottom). (C) Box plot showing the promoter activity of L1HS in LUSC and adjacent normal tissues. (D) Box plot illustrating the promoter activity o
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Tumour-specific TE-initiated transcription promotes tumourigenesis. (A) The... Open Access
Published: 19 May 2026
Figure 2
Tumour-specific TE-initiated transcription promotes tumourigenesis. (A) The distribution of the activated TE loci across the TE classes. (B) The distribution of the neighbouring genes across the gene type. (C) The reactome pathway enrichment analysis of neighbouring genes associated with the tumour-
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Snapshot of NoLS information for an individual protein of the selected orga... Open Access
Published: 19 May 2026
Figure 5
Snapshot of NoLS information for an individual protein of the selected organism in FuNGI. (a) Detailed information of the selected protein, including confidence rank, general information, and highlighted NoLS segments (in red). (b) NoD server prediction results displayed as a line graph, where the
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Co-localization of MoNOP1-RFP with candidate nucleolar proteins predicted b... Open Access
Published: 19 May 2026
Figure 6
Co-localization of MoNOP1-RFP with candidate nucleolar proteins predicted by FuNGI in Magnaporthe oryzae hyphae. Fluorescence microscopy images of M. oryzae hyphae co-expressing the nucleolar marker MoNOP1-RFP and individual GFP-tagged candidate proteins predicted to localize to the nucleolus by
