Computational Research

Research & Computational Focus

Applying computational methods, reproducible bioinformatics workflows, and data-driven analysis to biological research and drug discovery.

Research Domains

Computational Methodologies & Focus

ZYNEX BIO focuses on developing and executing computational research workflows tailored to complex biological questions.

Transcriptomic & Omics Research

Applying high-performance computational pipelines for high-throughput sequencing data, differential gene expression modeling, and biological pathway dynamics.

Standard Technologies

STARHISAT2DESeq2featureCountsRPython

Network & Systems Pharmacology

Constructing multi-target biological interaction networks, compound-target prediction models, and topological hub gene identifications in complex disease mechanisms.

Standard Technologies

CytoscapeSTRING DBSwissTargetPredictionDisGeNET

Structural Bio-Analytics & Molecular Docking

Investigating 3D protein structures, binding pocket geometry, molecular docking pose affinities, and non-covalent interaction profiling.

Standard Technologies

AutoDock VinaPyMOLPDBMGLToolsDiscovery Studio

Publication Data Visualization

Designing vector scientific figures, hierarchical heatmaps, volcano plots, PCA projections, and interactive network diagrams for peer-reviewed journals.

Standard Technologies

ggplot2ComplexHeatmapMatplotlibSeaborn

Interactive Workflow Demos

Representative Analytical Outputs

Interactive demonstrations of analytical visualizations produced by our computational pipelines.

1. Differential Expression Analysis (Volcano Plot)

Interactive Visualizer • RNA-seq

Differential Expression Volcano Plot

Up: 6 Down: 5

Hover over gene nodes to inspect expression metricsGRCh38 • DESeq2 Workflow

2. Target Network Pharmacology (PPI Graph)

Interactive Visualizer • Network Pharmacology

Protein–Protein Interaction & Target Graph

Confidence Cutoff:

Hub Protein Target Compound

STRING DB v12 • Cytoscape Layout

3. Molecular Docking Affinity (Pose Simulation)

Interactive Visualizer • Molecular Docking

AutoDock Vina Binding Affinity Analysis

High Affinity Binding

Grid Box: 22 × 24 × 26 ÅOptimal Binding Mode (Lowest Energy)

Pose Mode:

Binding Affinity (ΔG)-9.4 kcal/mol

Key Hydrogen Bond Interactions:

SER203 (2.1 Å)TYR124 (2.6 Å)TRP86 (2.9 Å)

RMSD l.b.: 0.00 Å

RMSD u.b.: 0.00 Å

Receptor: High Resolution PDB Structure • AutoDock Vina v1.2Gasteiger Charges Assigned

Computational Publications & Benchmarks

Research Benchmarks & Publications

Detailed research case studies and computational project benchmarks will be published here as ongoing biological research studies complete.

Discuss a Research Project