Daniel Machado

Daniel Machado is an Associate Professor of Computational Biology at the Department of Biotechnology and Food Science, Norwegian University of Science and Technology (NTNU). He joined NTNU in September 2020 and leads the Machado Lab, which focuses on computational approaches to understanding microbial communities. His work is affiliated with several important research initiatives including SFI - Industrial Biotechnology, a research-based innovation center aiming to boost the competitiveness of the Norwegian biotech industry, and ELIXIR Norway, the national node of the pan-European infrastructure for biological information.

Daniel Machado completed his Bsc/Msc in Mathematics and Computer Science at the University of Minho, Portugal, followed by a PhD in Bioengineering and Biotechnology through the MIT-Portugal Program. His academic journey reflects a strong foundation in both computational methods and biological applications.

His research primarily focuses on unlocking the potential of microbes to address multiple societal challenges. The Machado Lab uses computational models to understand how microbes work together in their natural habitats, particularly examining microbial communities that play important roles in human health and environmental sustainability. They follow an interdisciplinary approach, combining computational models and biological data to design synthetic communities for biotechnological applications and create more sustainable industries. Key research areas include exploring the functional potential of microbes across diverse ecosystems, understanding metabolic interactions in complex microbial communities, predicting metabolic regulation responses to perturbations, and designing synthetic microbial consortia for sustainable applications.

The Machado Lab's work has resulted in significant contributions to the field of computational biology, particularly in genome-scale metabolic modeling. Their research shows that synthetic microbial consortia can run fermentation processes more efficiently than traditional single-organism models through beneficial division of labor. They have also pioneered approaches using more sustainable substrates like lignocellulosic waste rather than sugar, with applications in biofuels, industrial products, and medicines.

Daniel Machado actively supervises numerous students at various levels, including PhD candidates Miguel Alves Magalhaes Teixeira, Idun Maria Tokvam Burgos, and Elisa Márquez-Zavala, as well as multiple Master's students. He teaches courses such as BT8120 - Prokaryote Molecular Biology and Synthetic Biology, BT2100 - Computational Biotechnology, TBT4508 - Bioinformatics and Biopolymeric Materials, and TBT4507 - Bioinformatics and Experimental design and data analysis.

The Machado Lab maintains strong connections with the broader scientific community through projects like Cell4Chem, which focuses on engineering microbial communities for the conversion of lignocellulose into medium-chain carboxylates. They have developed important computational tools including CarveMe (for genome-scale metabolic model reconstruction), SMETANA (for analyzing interactions in microbial communities), and ReFramed (a metabolic modeling package), which have been widely adopted in the field.