Search results

Figure 3 Web interface of the MERS-CoV-3D structural mutation database. (A) The gene/protein page, shown here for spike, summarizes the selected protein and displays mutation statistics, including the number of curated mutations, mapped structures, unique structures, and total mutation observations. The page

Figure 2 Classification of protein glycosylation types: Overview of major protein glycosylation categories represented in UniProtKB and GlyGen, with representative glycan structures added from GlyGen. Protein glycosylation is broadly divided into enzymatic and non-enzymatic processes. Enzymatic glycosylation

Figure 5 IntAct visualization of interactions between heparin (CHEBI:16336) and multiple Homo sapiens proteins: Nodes are color-coded by species (dark blue: human, brown: chemical entities), with shapes indicating molecular type (circles: proteins, hexagons: chemicals, rectangles: complexes). Pink-bordered

Figure 8 GlyGen Isoform Mapper Tool: User input interface of the Isoform Mapper Tool (left) showing UniProtKB isoform accessions, amino acid positions, and residues. The output summary (right) maps isoform positions to canonical accessions using global sequence alignment. Results indicate the mapped position

Figure 1 Automated genome-wide and proteome-wide workflow for construction of the MERS-CoV structural mutation database. (A) Illustrates the automated whole-genome mutation analysis workflow. BV-BRC genome metadata were first curated, followed by retrieval of MERS-CoV FASTA sequences, MAFFT-based whole-genom

Figure 2 Genome-wide mutation distribution and structural coverage of the MERS-CoV proteome. Integrated genome and proteome analysis of the curated MERS-CoV structural mutation database. (A) Cumulative genome-level mutation observations by viral protein, reflecting the recurrence of mutations across the cura

Figure 1 PTM/Processing Features Subsection: View of the PTM/Processing Features Table (Truncated) of the UniProtKB entry for the Epidermal growth factor receptor isoform 1 (P00533-1), showing annotated N -linked glycosylation sites (positions 56, 73, 128) with supporting publication counts. Screenshot o

Figure 4 Using IntAct’s advanced search to identify proteins annotated with the N -glycosylation modification term (MOD:00006): Example results for CLEC14A (Q86T13) show an annotated N -glycosylation site (Asn189), a mutation affecting interaction strength (Arg161Ala), and binding regions. The network view

Figure 7 PTM databases subsection: PTM databases subsection of the UniProtKB entry for EGFR (P00533) showing a GlyGen cross-reference and a summary of the number of different linkage types and sites of the 25 reported glycosylation sites with glycans in GlyGen. The link directs users to the EGFR glycosylatio

Figure 3 UniProtKB Advanced Search and results for N -linked glycosylated proteins. (A) The Advanced Search interface in UniProtKB is configured to retrieve entries with the ‘Glycosylation (FT)’ feature set to ‘n-linked’. The evidence filter is set to ‘Any’. (B) The UniProtKB results page shows entries retr

Figure 6 Data flow between UniProtKB, GlyGen, and other glycoscience resources: Schematic overview of the curation workflow and data exchange between UniProtKB and GlyGen. UniProtKB provides manually curated protein annotations, glycosylation and PTM sites, and variation data to GlyGen. GlyGen further integr

Figure 9 ProtVista Tool view in UniProtKB and GlyGen. (A) UniProtKB ProtVista Feature Viewer for Epidermal growth factor receptor isoform 1 (P00533-1), displaying structural and functional annotations along the sequence. Highlighted features include an atypical N -linked glycosylation at Asn73, supported by

Figure 1 Overview of our multi-step RAG ensemble. Three answer candidates are generated via (a) Query2Doc-based with Wikipedia retrieval, (b) Rationale-based with Wikipedia retrieval, and (c) Web Search API applied. The Decision Maker then compares the candidates and selects the final answer pair or generate

Figure 2 Analysis of source preferences across different Decision Maker models. Model configuration for RAG stage: (a) Query2Doc and Rationale steps by GPT-5.2, Web Search by Gemini 3 Pro, (b) all RAG steps by Gemini 3 Pro. Two stacked bar charts showing the proportion of final answers attributed to each

Figure 2 Network Visualization Features. Node types include protein-coding genes (circles) and microRNAs (diamonds). Edge types indicate relationship types; thickness encodes confidence. Nodes use locus IDs as unique identifiers ensuring correct network topology. Screenshot of the GeneReL Network page wit

Figure 3 Database Composition. (a) Distribution of relationship types. (b) Confidence level distribution showing 90.2% high confidence. (c) Evidence type classification. Three charts. (A) Horizontal bar chart of relationship-type counts (n = 13,710), led by Regulates (3,344; 24.4 percent), Interacts (3,05