Contact Dr Fady Mohareb

Areas of expertise

  • Bioinformatics
  • Computing, Simulation & Modelling
  • Digital Agriculture
  • Drug Discovery & Development
  • Food Quality
  • Food Safety
  • Food waste


Dr Mohareb is Reader and Head of the Bioinformatics Group in AgriFood at. He has ~12 years of experience in the field, and his research focuses on genome and transcriptome informatics, machine learning, data science, data visualization and cloud technologies. Dr Mohareb is leading the NGS and 3GS informatics work at Cranfield University on a number of national and international consortia, such as “Oats for the future” - BB/P001432/1, “Controlling dormancy and sprouting in potato and onion” - BB/K02065X/, and “Genomics-assisted selection of Solanum chilense introgression lines for enhancing drought resistance in tomatoes” - BB/L011611/11.  Dr Mohareb also has an established track record in the development and of bioinformatics software tools for managing and analysing high throughput genomes, proteomics or metabolic data; such as SorfML, PhyTB  and Mrmaid. His research includes the application of machine learning and pattern recognition to reveal hidden patterns in multivariate and high throughput datasets, as well as the application of the latest Web technologies and Cloud Computing to provide means for managing and visualising large datasets. Dr Mohareb's research team have extensive knowledge and experience in developing Web-based interactive frameworks for managing high-throughput experimental datasets. 

Current activities

1.    Next-Generation Sequencing informatics: leading the NGS data analysis work at Cranfield University and have been involved in a number of publicly and commercially-funded projects in this research area. This includes “Controlling dormancy and sprouting in potato and onion” - BB/K02065X/, and “Genomics-assisted selection of Solanum chilenseintrogression lines for enhancing drought resistance in tomatoes” - BB/L011611/11. Previous experiencerelated to Camelia sinensisincludes the development of data analysis pipeline for RNA-Seq de-novoassembly, abundance estimation and functional enrichment for tea transcriptome (Directly funded by Unilever), and variant calling of parental lines from a recombinant in-bred line (RIL) population (Solanum pimpinellifoliumS. lycopersicum var.cerasiforme). 

2.    Machine learning and pattern recognition: Development of novel methodologies to improve meat quality: Together with the Agricultural University of Athens, we are working on the development of classification and regression models for predicting quality and safety indices in meat products stored under different storage conditions, packaging and temperature.

3.     Data Visualisation and cloud computing: I have developed, and continue to refine and maintain, several web-based software tools, such as Mrmaid -  an online tool for mining millions of publicly available peptide spectra to help researchers design targeted proteomics assays for selected reaction monitoring experiments, and SORF an online research framework for food science research. 


  • The European Bioinformatics Institute (EBI)
  • London School of Hygiene and Tropical Medicine (LSHTM)
  • The Wellcome Sanger Institute.
  • Rothamsted Research
  • Unilever
  • GSK
  • Syngenta
  • Pepsico 


Articles In Journals

Conference Papers

  • Argyri A, Mohareb F, Panagou EZ, Bessant C & Nychas GJ (2009) An artificial neural networks approach for the rapid detection of the microbial spoilage of beef fillets based on Fourier transform infrared spectroscopy data. In: 6th Annual Conference on Predictive Modelling in Foods (ICPMF), Washington DC, 1 January 2009.
  • Mohareb F, Bessant C & Nychas GJ (2009) Symbiosis: a Web-based framework for managing and analysing high throughput metabolomic data. In: 17th Annual Internationa Conference on Intelligent Systems for Molecular Biology (ISMB) & 8th European Conference on Computational Biology (ECCB), Stockholm, 1 January 2009.
  • Mohareb F, Sattlecke M, Argyri A, Panagou EZ, Nychas E & Bessant C (2009) Identification of Meat Spoilage from FTIR Data Using the Symbiosis Data Analysis Framework. In: Euroanalysis 2009, Vienna, 1 January 2009.