Utilizing the STRING database, we conducted network and pathway analyses to unveil functional connections and biological pathways related to our dataset. STRING, a robust bioinformatics tool, integrates data from various sources on pathways, annotations, and protein-protein interactions. Differentially expressed genes (DEGs) meeting criteria were subjected to statistical analysis and employed as input for STRING. A confidence score threshold (set at X for high confidence) ensured reliable interactions. The resulting protein-protein interaction network revealed tightly connected clusters representing similar functions or biological processes.
STRING's enrichment analysis identified pathways significantly affected by our research, offering crucial insights into chemical mechanisms and biological functions. These ensemble ids are involved in these Go process, KEGG pathways, and Functions.
Table 1
These genes are involved in the following biological processes.
Ensemble Ids | Category | Term description | ENSP00000258873 | Go Process | Very long-chain fatty acid metabolic process | ENSP00000422007 | Go Process | Regulation of oxidative phosphorylation | ENSP00000256389 | Go Process | Reproduction | ENSP00000483721 | Go Process | Developmental process involved in reproduction | ENSP00000341662 | Go Process | Lipid metabolic process | |
Table 2
KEGG pathways in which genes are involved.
ENSP00000258873 | KEGG | Fatty acid biosynthesis, Fatty acid degradation, | ENSP00000422007 | KEGG | Arrhythmogenic right ventricular cardiomyopathy | ENSP00000258168 | KEGG | Retinol metabolism, Metabolic pathways | ENSP00000356037 | KEGG | Complement and coagulation cascades, Pertussis | ENSP00000352561 | KEGG | Neuroactive ligand-receptor interaction | |
Table 3
This table shows the diseases in which these genes are involved.
ENSP00000309052 | DISEASES | Complement component 2 deficiency, Male infertility | ENSP00000219244 | DISEASES | Skin disease, Atopic dermatitis, Allergic contact dermatitis | ENSP00000289429 | DISEASES | Immune system disease, Langerhans-cell histiocytosis | ENSP00000315602 | DISEASES | Lower respiratory tract disease, Nicotine dependence | ENSP00000407546 | DISEASES | Genetic disease, Chromosomal deletion syndrome, Chromosome 15q13.3 microdeletion syndrome | | | |
Table 4
This table shows the GO functions of the genes.
ENSP00000422007 | GO Function | Actin binding, Signaling receptor binding, Integrin binding | ENSP00000256389 | GO Function | Metalloendopeptidase activity, Catalytic activity | ENSP00000483721 | GO Function | Peptide receptor activity, G protein-coupled receptor activity | ENSP00000341662 | GO Function | Monooxygenase activity, Iron ion binding | ENSP00000295897 | GO Function | DNA binding, Copper ion binding | |
This concise analysis enhances our understanding of the molecular landscape in our dataset. The SVM model results are presented below in the table and figure show the heatmap with contingency matrix. The formula used are given below as:
Accuracy = (TP + TN) / (TP + TN + FP + FN)
Where:
TP = True Positives (correctly identified positives)
TN = True Negatives (correctly identified negatives)
FP = False Positives (incorrectly identified positives)
FN = False Negatives (incorrectly identified negatives)
Sensitivity = TP / (TP + FN)
Specificity = TN / (TN + FP)
F1 Score = 2 * (Precision * Recall) / (Precision + Recall)
Where:
Precision = TP / (TP + FP)
Table 5
Results of performance measures
Evaluation Matrices | Results |
Accuracy | 0.8181818181818182 |
Sensitivity | 0.0 |
Specificity | 1.0 |
Predicted positive | 0 |
Predicted Negative | 11 |
F1 Score | Nan |
The Decision Tree model results are presented below in the table and figure show the heatmap with contingency matrix.
Table 6
Decision Tree Results of performance measures
Evaluation Metrics | Results | Accuracy | 0.9615384615384616 | Sensitivity ER+ | 0.95 | Sensitivity HER2- | 1.0 | Specificity ER+ | 0.95 | Specificity HER2- | 1.0 | Predicted positive ER+ | 1.0 | Predicted Negative HER2- | 0.95 | F1 Score | 0.9743589743589743 | |