Bio Digitalization & Data Science

My research focuses on big data analytics and digital competencies, machine learning and artificial intelligence, and the integration of automation activities with data science. The purpose of the group research is to introduce AI, models, and the adoption of digital solutions to predict and optimize the behavior of the production process at each product life cycle stage.

We are a group of AI practitioners looking to adapt and apply principles of AI and machine learning to bioengineering in various applications to improve synbio and enable its full impact by creating a third axis in the engineering phase space: physical, chemical, and biological. We use AI and digital solutions to produce accurate predictions in bioengineering outcomes and enable effective inverse design.Another key research is normalizing, integrating, analyze imaging and omics data (genomic, transcriptomic, proteomic, and metabolomics) by numerous intelligent techniques and technologies such as machine learning, deep learning, data mining, and statistical learning approaches.

My group is collaborative, and currently included three PhD and Master Students, by facilitating collaboration with internal and external partners, and close collaboration with industries such as Novo Nordics & Novozymes in various data science projects. If you are interested in joining my research group to expand your competence in big data analytics & AI insights by using next-generation autonomous algorithms and generating highly actionable predictions, you are welcome to reach out.

Courses

Python for Data Analysis and Automation in Biology

Group Leader

Marjan Mansourvar Assistant Professor Department of Biotechnology and Biomedicine marjma@dtu.dk

publications

Go to Google Scholar

Research projects

Prediction of Promoter Strength with Machine Learning

Partners: Gerd Seibold, Jing Shen
Project status: Active

Automatic scoring of fungal strains using machine learning- image classification

Jakob Blæsbjerg Hoof(associate professor), Søren Dalsgård Petersen
Project status: Active

Data visualization tool for Enzyme Discovery

Jane Wittrup Agger (Associate professor), Bo Pilgaard (Postdoc)
Project status: Active

Self-supervised Deep learning for Biological sequences

Jorge Carrasco Muriel, Lars Keld Nielsen
Type: PhD | Project status: Active

Machine learning-based framework for the detection of essential genes in fungal strains

Sajad Tavakoli, Christopher Workman
Type: PhD | Project status: Active

Alignment of HPLC chromatograms-ML model to evaluate peaks in complex chromatograms

Type: MSc. | Project status: Active Partner: Novo Nordics

Application of Motion Amplification in Predictive Maintenance in API

Type: MSc | Project status: will start Feb 2023
Partner: Novo Nordics

AI & Modelling bioprocess in a multi-product plant

Type: MSc | Project status: will start Feb 2023
Partner: Novozymes

Simulation guided engineering of signal peptides

Type: MSc | Project status: will start Feb 2023
Uffe Hasbro Mortensen, Lucas Levassor

Associated group members

Jorge Carrasco Muriel PhD Student Novo Nordisk Foundation Center for Biosustainability Mobile: +45 93510189 jcamu@biosustain.dtu.dk

Sajad Tavakoli PhD Student Department of Biotechnology and Biomedicine sajata@dtu.dk

Maria Eduarda Della Rosa PhD student Department of Biotechnology and Biomedicine medero@dtu.dk

Baris Kara Research Assistant Novo Nordisk Foundation Center for Biosustainability bakar@dtu.dk

Jonathan Funk Visiting PhD Student Novo Nordisk Foundation Center for Biosustainability jonfu@biosustain.dtu.dk