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Journal Article
Seung-Jin Park and Seon-Young Kim
Database, Volume 2026, 2026, baaf086, https://doi.org/10.1093/database/baaf086
Published: 16 January 2026
Journal Article
Drew Mayernik and others
Database, Volume 2026, 2026, baaf091, https://doi.org/10.1093/database/baaf091
Published: 16 January 2026
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Published: 16 January 2026
Figure 3. Use cases of Panorama. (A) Kaplan–Meier survival curves for SMARCA4 mutations in LUAD from CPTAC (left) and TCGA (right) datasets. Log-rank test. (B) Box plots comparing Z-differences in mRNA and protein expression levels for AURKA across multiple breast cancer (BRCA) cohorts. P -value is calculate
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Published: 16 January 2026
Figure 1. Overview of the TearFluid platform architecture. The top panel illustrates the model–view–controller (MVC) architecture of the TearFluid Database. Controllers query the Microsoft SQL database, process the data as models, and present them to users through views. Each page includes a set of interactiv
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Published: 16 January 2026
Figure 3. Overview of proteomic expression across samples. Proteins passing a QValue threshold of 0.01 are included (n  = 2134). Mean log-transformed MaxLFQ expression is plotted against the proportion of samples in which each protein is detected. Proteins are categorized into four abundance classes: Rare (&l
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Published: 16 January 2026
Figure 1. Workflow and scheme for the database. (A) Step 1: Dataset preparations. Data were collected from proteogenomics and multiomics datasets from multiple tissues and biological data types. The number of samples per tissue is shown in parentheses. (B) Step 2: Preprocessing. Data filtering criteria and to
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Published: 16 January 2026
Figure 4. Tissue-specificity of TP53 mutation and candidate driver mutations. (A) Radar plots displaying the evaluation of TP53 mutations across 12 cancer types. Each sector of the radar plot represents a different functional category: PB, EP, IM, PE, and AD. (B) Distribution of the AOS across 12 cancer types
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Published: 16 January 2026
Figure 2. Overview of the TearFluid database schema. The relational design of the database highlights interoperability among tables. The ‘ID’ fields represent hidden, unique server-side identifiers for each record. The ‘Sample ID’ and ‘Accession ID’ fields serve as foreign keys that enable integration across
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Published: 16 January 2026
Figure 4. Protein data page. The Protein Data Table displays Sample ID, Accession ID, Protein Symbol, MaxLFQ value, Posterior Error Probability (PEP), and QValue for each protein-sample pair.
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Published: 16 January 2026
Figure 2. The web interface of Panorama. (A) Overview of the Panorama web interface, (1) logo of the Panorama database, (2) a brief description and functionalities of the Panorama database, and (3) Panorama menu bar. (B) Detailed view of the Panorama database function interface: (1) a brief description of the
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Published: 16 January 2026
Figure 5. Protein summary page. The Protein Summary Table displays Accession ID, Protein Symbol, Protein Description, Gene Symbol, total and average protein abundance, Sample detection proportion, and molecular characteristics for each protein, including amino acid count, molecular weight, and calculated isoe
Journal Article
Hao Li and others
Database, Volume 2026, 2026, baaf088, https://doi.org/10.1093/database/baaf088
Published: 15 January 2026
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Published: 15 January 2026
Figure 1. Overview of ePerturbDB website. Users can search the database using genomic region, cell type, gene, or tissue name. ePerturbDB provides results in terms of matching enhancer locations. For each matching enhancer, it provides other details such as study ID, protocol, and corresponding CRISPR sgRNA o
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Published: 15 January 2026
Graphical Abstract Graphical Abstract
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Published: 15 January 2026
Figure 2. Application screenshots for enrichment and knowledge graph generation. (a) Results of the association analysis of specific gene sets are visualized as a dot plot of significantly enriched terms and a tree of their hierarchical clustering based on Jaccard’s similarity index. (b) Each selected enrichm
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Published: 15 January 2026
Figure 2. Overview of MTB genomic data in GdbMTB. (a) Genomic quality profile. A unified four-panel composite visualization of the genomic quality of 365 MTB genomes. A shared colour scheme denotes high-quality genomes in red, medium-quality in blue, low-quality in yellow, and high-contamination genomes in gr
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Published: 15 January 2026
Figure 3. Global distribution and environmental context of MTB genomes. (a) Global distribution of MTB genomes. This figure presents the global geographical distribution of 365 MTB genomes compiled in GdbMTB, with each red dot marking the sampling location of an individual genome. The map highlights the world
Journal Article
Samiksha Maurya and others
Database, Volume 2026, 2026, baaf084, https://doi.org/10.1093/database/baaf084
Published: 15 January 2026
Journal Article
Marios Tomazou and others
Database, Volume 2026, 2026, baaf083, https://doi.org/10.1093/database/baaf083
Published: 15 January 2026
Journal Article
Runjia Ji and others
Database, Volume 2026, 2026, baaf090, https://doi.org/10.1093/database/baaf090
Published: 15 January 2026