ABOUT

Engineering solutions at the nexus of life sciences and computation

The Center for Omics technologies and Data Engineering (CODE) fosters interdisciplinary collaboration at the intersection of life sciences and computation, developing engineering- and data-driven solutions to complex biological challenges. 

We advance research across  genomics, transcriptomics, proteomics, phenomics, metabolomics, and other omics technologies. Our approach leverages artificial intelligence, machine learning, and advanced analytics, supported by innovations in data storage, transmission, visualization, and modeling. 

Our mission is to  develop integrative, scalable, robust, and interpretable technologies and methods  that unlock insights from complex biotic and abiotic data. 

These solutions enable transformative discoveries in precision medicine, population and cancer omics, plant and metabolic engineering, biomanufacturing, bioprocess engineering, and molecular systems engineering. CODE serves as a hub for collaborative research, student training, consulting, and partnerships that shape the future of omics- and data-driven science and engineering.

Our Vision

To establish Florida Atlantic University as a leader in engineering-driven omics technologies and computational innovation, fostering research, training, and partnerships that position South Florida as a hub for breakthroughs in precision medicine, biotechnology, and systems engineering.

Our Mission

CODE unites faculty, students, industry, and national lab partners to:

• Discover
  o Advance omics research with scalable, interpretable, engineering-driven solutions.
  o Extract insights from complex biological and environmental data using artificial intelligence, machine learning, and advanced analytics.
• Innovate
  o Engineer transformative methods bridging life sciences and computation.
  o Drive breakthroughs in precision medicine, population and cancer omics, plant and metabolic engineering, and biomanufacturing.
• Connect
  o Engage students and researchers in interdisciplinary training and mentorship programs.
  o Build collaborative networks across academia, industry, and national labs.

RESEARCH FOCUS AREAS

CODE focuses on methodological and technological innovation across omics disciplines, with key areas including:

• Population Genomics:  Studying genetic variation to uncover population dynamics anddisease-associated loci, integrating multi-omics data for insights into complex traits and history.

• Cancer and Clinical Genomics:  Applying genomics and transcriptomics to understand tumor biology, identify biomarkers, and support precision medicine initiatives.

• Systems and Molecular Engineering:  Designing and optimizing molecular and metabolic systems using omics-informed computational models for synthetic biology and biomanufacturing.

• Multi-Omics Data Integration and AI Analytics:  Developing computational frameworks to integrate genomics, transcriptomics, proteomics, and metabolomics, using artificial intelligence and machine learning to extract interpretable insights.

• Accelerating Omics Technologies:  Designing quantum and harware accelerated solutions for studying genomic and transcriptomic variation.
  
• Translational and Precision Medicine:  Applying omics-driven solutions to human health challenges, integrating laboratory and clinical datasets for patient-specific therapeutic strategies.

TRAINING AND WORKFORCE DEVELOPMENT

CODE prepares the next generation of interdisciplinary scientists and engineers through:

• Hands-On Research and Laboratory Training:  Practical experience in high-throughput sequencing, multi-omics data analysis, computational modeling, and bioinformatics workflows.
• Partnerships with Hospitals, Industry, and National Labs:  Collaborative projects, mentorship, and real-world experience that bridge research and application.
• Interdisciplinary Workshops and Mentorship Programs:  Collaborative projects, skill-building sessions, and mentorship from faculty and partner institutions at the intersection of life sciences and computation.