Bioinformatics · Metabolic Modeling · Functional Genomics

Metabolic models that explain how cells work

Cells turn food into energy and building blocks through thousands of chemical reactions. A genome-scale metabolic model is a computer map of all these reactions, built from an organism's DNA. It lets researchers test on screen what happens when a gene is switched off, a drug is added or the diet changes, before running an experiment. It works for microbes, parasites, gut bacteria and human cells.

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About Me

Portrait of Dr. Ömer Faruk Bay

Dr. Ömer Faruk Bay holds a degree in Molecular Biology and Genetics from Atatürk University, and earned his master's and Ph.D. in Systems Biology & Bioinformatics from the University of Manchester, UK. His doctoral research centered on the metabolism of Trichuris muris, where he pioneered the first genome-scale metabolic model for this parasitic whipworm to uncover novel therapeutic targets.

As a Postdoctoral Researcher in Lars Kuepfer's group, his work revolved around reconstructing genome-scale metabolic models for the synthetic mouse intestinal bacterial community (OMM19). By mapping their metabolic capabilities and interactions, he successfully decoded their collective phenotype and resilience to perturbations.

Currently, Dr. Bay serves as a Lecturer at AGÜ teaching Bioinformatics, and works as a consultant leveraging his deep expertise in functional genomics, systems biology, and metabolic modeling.

Metabolic Modeling Functional Genomics Transcriptomics Systems Biology Python / R Bioinformatics

Areas of work

Consulting Services

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Metabolic Modeling

Genome-scale metabolic network reconstruction, manual curation, and constraint-based modeling for eukaryotic and prokaryotic systems.

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What it covers

  • Building a metabolic model from a genome: draft reconstruction, manual curation and gap filling.
  • Simulations such as flux balance analysis: growth, essential genes and reactions, effects of nutrients and drugs.
  • Models tuned with RNA-seq data, and community models for several species together.

Typical applications

Drug-target discovery, understanding disease metabolism, gut microbiome interactions, biotechnology and strain design, and nutrition and diet research.

You provide → you get

A genome, or an existing model, plus growth data if available → a curated model file (SBML), simulation results, figures and clear documentation.

Discuss a project
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Functional Genomics

Data analysis pipelines for bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics to extract meaningful biological networks.

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What it covers

  • Bulk RNA-seq: quality control, quantification, differential expression and pathway enrichment.
  • Single-cell and spatial transcriptomics: clustering, cell types and spatial patterns.
  • Gene networks, and linking expression data to metabolic models.

Typical applications

Finding which genes and pathways change between conditions, diseased and healthy tissue, or treated and untreated samples.

You provide → you get

Raw reads or a count table, plus sample information → a reproducible analysis, result tables, figures and a short report.

Discuss a project
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Data Analysis & Pipeline Dev

Custom bioinformatics tool development and high-throughput biological data analysis tailored for your project's needs.

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What it covers

  • Custom tools and scripts in Python, R and Unix for your own data.
  • Automated, reproducible workflows for high-throughput biological data.
  • Training for your team so that the analysis can be repeated in-house.

Typical applications

Replacing manual spreadsheet work, standardising a lab's analysis, or building a small tool or dashboard around a research question.

You provide → you get

Your dataset and the question you want answered → documented code, results and a hand-over session.

Discuss a project

Current Research

Cambridge & Sanger Institute Collaboration

2024 – Present

Leading an international genomic collaboration focused on integrating RNA-seq data to improve genome annotations and construct genome-scale metabolic models for Trichuris muris and Trichuris trichiura.

Uniklinik RWTH Aachen Project

Jan 2023 – Apr 2024

Reconstructed and analyzed genome-scale metabolic models for the synthetic mouse intestinal bacterial community (OMM19), investigating metabolic interactions and mechanisms driving dysbiosis.

Metabolic Playground

Switch genes off in a pretend cell and see whether it can still grow. No science background needed. It runs live in your browser.

How it works

Think of a cell as a tiny kitchen. It takes in sugar, cooks it through a chain of steps, and uses the energy and ingredients to build a copy of itself. Each step is done by a worker called an enzyme, and each worker is built from instructions called a gene. Here you can fire workers one by one and see what happens. A computer works out the best way for the kitchen to run, using the same kind of maths scientists use on real cells.

  1. Pick the surroundings: is there air (oxygen)? How much sugar is on the menu?
  2. Fire a worker: click a gene to switch it off (it turns red). Can the cell cope without it?
  3. See the effect: the top bar shows how well the cell grows compared with a healthy one. The bars below show how busy each step is.

Try a guided story

Pick a story. It sets up the cell for you and explains what to look at, step by step.

Educational toy model: a simplified cartoon of a cell, not a real organism.

Genes (click to switch off)

Environment

Goal

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Map of the cell

How busy is each step?

Which genes can the cell not live without?

What does this mean?

An AI reads the simulation result and explains it in plain words.


            

                
                
                
            

        


        

            
What are these molecules? (in everyday words)

            

            
What does each gene do?

            

        

    


    
    

        
Key Publications

        

            

                
Nature Communications

                
2023

                
Bay, Ö.F., Hayes, K.S., Schwartz, JM. et al. A genome-scale metabolic model of parasitic whipworm. 

 Read Paper

            

        

        
See the full list on Google Scholar →

    


    
    

        
Teaching & Outreach

        
University Teaching

        

            

                
Abdullah Gül University (AGÜ)

                
Undergraduate & Graduate Lecturer

                
Currently teaching core bioinformatics curriculums, including Computational Biology and Functional Genomics. Focused on bridging theoretical sequences to practical data science.

            

            

                
University of Manchester

                
Graduate Teaching Assistant

                
Led practical modules for MSc students including Programming Skills, Computational Approaches to Biology, and Bioinformatics Tools and Resources.

            

        

        

            
TÜBİTAK 4004 — Cell Factory

            

                Bioinformatics and systems biology lessons for high-school students, built as an interactive slide system. (The lessons themselves are in Turkish.)
            

            

                

                    
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Lesson 1: From Gene to RNA

                    
Introduction to Omics Technologies

                    

                        An interactive introduction to DNA, the Central Dogma, transcription, RNA-seq, genomics, transcriptomics and single-cell analysis. 16 slides.
                    

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Lesson 2: The Cell Factory

                    
Metabolism & Modeling

                    

                        Metabolism, glycolysis, metabolic networks, the GPS analogy, FBA modeling and synthetic biology simulations. 15 slides.
                    

                    Go to lesson →
                

            

        

    


    
    

        
Key Collaborators

        

            

                
Steve Doyle & Maria Duque-Correa

                
Wellcome Sanger Institute & Cambridge Univ.

                
Collaborating closely on integrating multi-omics data for Trichuris metabolic modeling.

            

            

                
Lars Kuepfer & Zita Soons

                
Uniklinik RWTH Aachen

                
Worked together on reconstructing and analyzing the OMM19 microbiome metabolic capabilities.

            

        

    


    
    

    
    

        
Research collaborations & affiliations