Multiomics · Bioinformatics · AI-ready data

Genotope — Integrated data solutions for life sciences

Transforming complex biological data into actionable insights. We deliver scalable bioinformatics, expert data curation, and computational infrastructure tailored to your research.

25+

Years biopharma experience

Drug discovery → translational

Full research continuum

Small biotech to global pharma

Client experience

Houston · Texas Medical Center

Life sciences hub

Core capabilities

Accelerating Discovery Through High-Dimensional Data Analysis & Pipelines

Today's life science datasets — including single-cell and multiomics data — are increasingly large, complex, and difficult to integrate and interpret. Genotope helps bridge the gap between high-dimensional experimental outputs and meaningful biological insight.

Single-cell & spatial multiomics

  • scRNA-seq

  • ATAC-seq

  • Spatial Transcriptomics

AI/ML training data curation

  • Structured, annotated datasets optimized for AI/ML

  • Integration of publicly available datasets into training datasets

Custom bioinformatic analysis & pipelines

  • Bespoke computational workflows

  • Study design, data modality, and organism

  • Model development and inclusion

Agentic workflow orchestration - coming soon

  • Automated workflow orchestration

  • Scientific expert review of workflows

  • Risk mitigation

Representative Experience

Proven across the drug development continuum

From early discovery to translational research — small biotech to global pharma.
Engagements led by Genotope's founder:

Small Biotech

Translational Research

Integrative epigenomic & transcriptomic analysis

A small biotech developing treatments in the neuromuscular space required integrated multi-omics analysis to identify novel gene targets of therapeutic interest.

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Large Biopharma

Clinical genomics

Clinical Genomics & Biomarker Analysis — Oncology

A global biopharma organization engaged the team to conduct integrated genomic analysis across multiple large-scale clinical trials in oncology.

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Small Biopharma

Early Discovery

Computational Peptide Prioritization

A small biopharma company sought to rationally prioritize a library of peptide candidates ahead of costly in vitro and in vivo screening.

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Get Started

Let’s schedule a call

Whether you have a defined study or an early-stage analytical challenge, we'd like to hear about it.

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