Cell Based Assays:
We can accurately quantitate a cell population's response to external factors, whether it is an increase in cell growth, no effect, or a decrease in growth due to necrosis or apoptosis.
AlamoMedAI - Data-Driven Biomedical Discovery:
AI-Driven Hypothesis Generation
Data-guided discovery using AI and statistical modeling
Identification of novel biomarkers, pathways, and therapeutic targets
Predictive AI models integrating omics, experimental, and clinical data
Bioinformatics & Public Data Mining
We specialize in extracting high-value insights from authenticated, widely used biomedical repositories, including:
cBioPortal / TCGA – cancer genomics and clinical data
Gene Expression Omnibus (GEO) – transcriptomics and proteomics
GTEx – tissue-specific gene expression
UK Biobank – population-scale genetics, phenotypes, and imaging
ClinVar & gnomAD – clinically relevant variants and population allele frequencies
Ensembl / UCSC Genome Browser – genome annotation and visualization
These analyses enable rapid generation of grant-ready preliminary data for manuscripts, NIH/DoD/SBIR proposals, and early-stage translational programs.
Molecular Modeling & Simulation
Protein–ligand docking and virtual screening to identify novel drug candidates
Molecular dynamics simulations to evaluate binding stability and conformational behavior
Compound stability and interaction analysis supported by experimental confirmation
High-Throughput Data Visualization
Publication-ready figures, graphical abstracts, and visual analytics
AI-assisted visualization of screening, docking, and omics data
Figures are suitable for:
Peer-reviewed manuscripts
Grant proposals (NIH, DoD, SBIR/STTR, CDMRP)
Investor and pitch presentations
Grant & Regulatory Support
Preliminary data generation for competitive funding
Scientific input for NIH, DoD, SBIR/STTR, and CDMRP proposals
Support for IRB, IND, and regulatory documentation
Alignment with scientific rigor, reproducibility, and compliance standards
Protein Service:
Cell Line Development