1-20 of 9242
Image
The web interface of Panorama. (A) Overview of the Panorama web interface, ... Open Access
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
Image
Protein summary page. The Protein Summary Table displays Accession ID, Prot... Open Access
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
Image
Use cases of Panorama. (A) Kaplan–Meier survival curves for SMARCA4 mutatio... Open Access
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
Image
Overview of the TearFluid platform architecture. The top panel illustrates ... Open Access
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
Image
Overview of proteomic expression across samples. Proteins passing a QValue ... Open Access
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
Journal Article
Panorama: a database for the oncogenic evaluation of somatic mutations in pan-cancer Open Access
Database, Volume 2026, 2026, baaf086, https://doi.org/10.1093/database/baaf086
Published: 16 January 2026
Journal Article
Tear fluid database: a reference website for tear fluid proteomics Open Access
Database, Volume 2026, 2026, baaf091, https://doi.org/10.1093/database/baaf091
Published: 16 January 2026
Image
Workflow and scheme for the database. (A) Step 1: Dataset preparations. Dat... Open Access
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
Image
Tissue-specificity of TP53 mutation and candidate driver mutations. (A) Rad... Open Access
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
Image
Overview of the TearFluid database schema. The relational design of the dat... Open Access
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
Image
Protein data page. The Protein Data Table displays Sample ID, Accession ID,... Open Access
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.
Image
Database content statistics. (A) Source repository distribution, (B) part c... Open Access
Published: 15 January 2026
Figure 3.
Database content statistics. (A) Source repository distribution, (B) part category distribution (Level 1), and (C) verification status distribution.
Image
A case study of finding overlap of experimentally perturbed enhancers with ... Open Access
Published: 15 January 2026
Figure 3.
A case study of finding overlap of experimentally perturbed enhancers with predicted enhancers using H3K27ac ChIP-seq peaks from patient-derived xenograft (PDX) models of triple-negative breast cancer (TNBC). (A) Bar plot showing the number of experimental perturbations (sgRNA or eRNA-based knockout
Image
An overview of the results of the intersection of eRNA associated with surv... Open Access
Published: 15 January 2026
Figure 4.
An overview of the results of the intersection of eRNA associated with survival in breast cancer (in TCEA database) with the enhancer perturbations curated in our database. (A) Distribution of intersecting enhancer perturbations in terms of the source of study. The overlapping enhancer perturbations
Image
Overview of ePerturbDB website. Users can search the database using genomic... Open Access
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
Image
Graphical Abstract Open Access
Published: 15 January 2026
Graphical Abstract
Graphical Abstract
Image
Application screenshots for enrichment and knowledge graph generation. (a) ... Open Access
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
Image
Overview of MTB genomic data in GdbMTB. (a) Genomic quality profile. A unif... Open Access
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
Image
Global distribution and environmental context of MTB genomes. (a) Global di... Open Access
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
SynVectorDB: embedding-based retrieval system for synthetic biology parts Open Access
Database, Volume 2026, 2026, baaf088, https://doi.org/10.1093/database/baaf088
Published: 15 January 2026
