Live Demos

Explore interactive examples of BioMedGPS Explainer in action.

Asthma Drug Discovery

Complete drug repurposing analysis for asthma (MONDO:0004979) with comprehensive visualizations and network analysis.

Drug Prediction Network Analysis Pathway Enrichment
View Original Report

Asthma Disease

Drug discovery analysis for asthma diseases with focus on network centrality and gene pathway analysis.

Network Centrality Gene Analysis Interactive Plots
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Neurological Disorders

Analysis of potential drug candidates for neurological disorders using advanced filtering and visualization techniques.

Advanced Filtering Visualization Statistical Analysis
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Diabetes Drug Discovery

Comprehensive drug repurposing analysis for diabetes (MONDO:0005148) with metabolic pathway analysis and network visualization.

Metabolic Analysis Pathway Enrichment Interactive Reports
View Full Report

Code Examples

Practical code examples showing how to use BioMedGPS Explainer for different scenarios.

Basic Drug Discovery Pipeline

from drugs4disease.core import DrugDiseaseCore
from drugs4disease.filter import DrugFilter
from drugs4disease.visualizer import Visualizer

# Initialize components
core = DrugDiseaseCore()
filter_tool = DrugFilter()
visualizer = Visualizer(disease_id="MONDO:0004979", disease_name="asthma")

# Run complete analysis
core.run_full_pipeline(
    disease_id="MONDO:0004979",  # Asthma
    output_dir="results/asthma_analysis/",
    model='TransE_l2',
    top_n_diseases=50,
    gamma=12.0,
    threshold=0.5,
    top_n_drugs=100
)

# Apply filtering for high-scoring new drugs
filter_tool.filter_drugs(
    input_file="results/asthma_analysis/annotated_drugs.xlsx",
    expression="score > 0.7 and existing == False",
    output_file="results/asthma_analysis/high_scoring_drugs.xlsx"
)

# Generate comprehensive report
visualizer.generate_report(
    data_file="results/asthma_analysis/high_scoring_drugs.xlsx",
    output_file="results/asthma_analysis/analysis_report.html",
    title="Asthma Drug Discovery Analysis"
)

Advanced Filtering Examples

# Filter for drugs with shared genes and pathways
filter_expression_1 = """
score > 0.6 and 
existing == False and 
num_of_shared_genes_in_path >= 2 and 
num_of_shared_pathways >= 1
"""

# Filter for network-central drugs
filter_expression_2 = """
drug_degree > 10 and 
num_of_key_genes >= 3 and 
score > 0.5
"""

# Filter for drugs with specific pathway involvement
filter_expression_3 = """
score > 0.6 and 
existing == False and 
(num_of_shared_genes_in_path >= 1 or num_of_shared_pathways >= 1) and
pvalue < 0.05
"""

# Apply filters
filter_tool.filter_drugs(
    input_file="results/annotated_drugs.xlsx",
    expression=filter_expression_1,
    output_file="results/filtered_by_genes_pathways.xlsx"
)

Custom Visualization

# Generate specific visualization types
visualizer.create_visualization(
    data_file="results/filtered_drugs.xlsx",
    viz_type="score_distribution",
    output_file="results/score_distribution.png"
)

visualizer.create_visualization(
    data_file="results/filtered_drugs.xlsx",
    viz_type="drug_similarity_network",
    output_file="results/drug_network.html"
)

visualizer.create_visualization(
    data_file="results/filtered_drugs.xlsx",
    viz_type="shared_genes_pathways",
    output_file="results/gene_pathway_analysis.html"
)

Use Cases

Common use cases and applications of BioMedGPS Explainer in biomedical research.

Drug Repurposing

Identify existing drugs that could be repurposed for new therapeutic indications using knowledge graph embeddings and network analysis.

  • Predict drug-disease associations
  • Analyze shared biological pathways
  • Evaluate network centrality

Network Medicine

Analyze complex biological networks to understand disease mechanisms and identify therapeutic targets.

  • PPI network analysis
  • Pathway enrichment analysis
  • Gene-disease associations

Biomarker Discovery

Identify potential biomarkers by analyzing shared genes and pathways between drugs and diseases.

  • Gene expression analysis
  • Pathway overlap analysis
  • Statistical significance testing

Precision Medicine

Develop personalized treatment strategies by analyzing individual disease profiles and drug responses.

  • Patient-specific analysis
  • Drug response prediction
  • Personalized drug selection

Sample Reports

Comprehensive analysis reports demonstrating the full capabilities of BioMedGPS Explainer.

Asthma Analysis Report Preview

Asthma Drug Discovery Analysis

Complete analysis of potential drug candidates for asthma treatment, including network analysis, pathway enrichment, and interactive visualizations.

150 Drugs Analyzed 25 Genes Identified 12 Pathways Enriched
View Report
Cardiovascular Analysis Report Preview

Cardiovascular Disease Analysis

Network-based analysis of cardiovascular disease drug candidates with focus on heart-related pathways and gene interactions.

200 Drugs Analyzed 35 Genes Identified 18 Pathways Enriched
View Report
Diabetes Analysis Report Preview

Diabetes Drug Discovery Analysis

Comprehensive analysis of potential drug candidates for diabetes treatment with focus on metabolic pathways and glucose regulation.

180 Drugs Analyzed 28 Genes Identified 15 Pathways Enriched
View Report

Tutorials

Step-by-step tutorials to help you get started with BioMedGPS Explainer.

01

Getting Started with Drug Discovery

Learn the basics of running drug discovery analysis with BioMedGPS Explainer.

15 minutes Beginner
Start Tutorial
02

Advanced Filtering Techniques

Master advanced filtering techniques to identify the most promising drug candidates.

20 minutes Intermediate
Start Tutorial
03

Custom Visualization Reports

Create custom visualization reports and interactive dashboards for your analysis results.

25 minutes Advanced
Start Tutorial