Fig 1.
An overview of the methodological approach, including the flowchart and overall research design.
Fig 2.
The graphical PPI network of all stickler syndrome related TMGs, created using Cytoscape as described in material and method section.
Table 1.
List of top 15 enriched GO biological process terms assigned to the text-mining genes.
Table 2.
List of top 10 enriched KEGG pathways assigned to the text-mining genes.
Table 3.
List of hub node genes in the PPI network which were identified with a filtering node degree ≥2.
Fig 3.
Identification and enrichment analysis of the TMGs.
(A) PPI network of 22 Text mining genes visualized through Cytoscape; (B) Using MCODE, a single module of Hub Genes was obtained related to Stickler syndrome as visualized through Cytoscape.
Fig 4.
Illustration of the GO terms associated with the hub genes.
Functional and pathway enrichment analyses were performed using the DAVID tool and visualized through the REVIGO web platform as described in material and method section.
Fig 5.
The illustration depicting the GO terms within the module identified as significant.
A hierarchical tree was generated using the ShinyGO web server, revealing a strong correlation (P < 0.005). Functional and pathway enrichment analyses related to Stickler syndrome showed high enrichment scores.
Table 4.
List of US FDA-approved drugs (with their present disease implication) that are predicted to target 5 of the 9 hub genes. * Indicates not currently US FDA approved for any use but holds Fast Track and Orphan Drug Designations. COPD means chronic obstructive pulmonary disease.
Fig 6.
Functional characterization of the nine central hub genes within the module.
(A) Key biological processes and pathways were visualized using the ClueGO plugin. (B) Functional and pathway distributions across the core genes are presented. (C) KEGG pathways and enriched GO terms are shown, with each pathway represented by a distinct color. A corrected P-value of less than 0.01 was considered statistically significant.