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Muhammad Arif

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About me

Systems Biology of Human Diseases

The human body is like a new, state-of-the-art car. Both need chemical energy (food for humans, fuel for cars) to be able to perform their activity. Moreover, both are complex and connected systems. When a car breaks down, most of the time we cannot fix the problem just by looking at only one component. It's the same with the human body, diseases can affect multiple parts of the body, as it is one big connected system.

My PhD research is focused on systematically revealing the underlying molecular mechanism of human diseases, especially cardiovascular diseases. I'm using systems biology approaches to achieve this goal, especially with network analysis. Specifically, I'm building network models for the diseases, by combining gene-gene, protein-protein, and gene-metabolite networks. This process provides a more complete view of the complex systems that are affected by the disease. Moreover, I'm exploring the possibility of integrating multiple tissues to understand the alteration caused by diseases in not only one tissue but in the whole body. So instead of looking at the car problem just part by part, I want to view the explore the interaction of different car parts to figure out the problem.

To date, I have been involved in many projects, including collaborative projects with other research institutes, internationally. One of my main completed projects is the development of a gene co-expression network database. The database is freely available at

I'm originally from Indonesia. I have a strong background in programming and network analysis. I received my master degree from KTH Royal Institute of Technology and UPC (Spain), and bachelor degree from Institut Teknologi Bandung (Indonesia). Prior to my master degree, I was also working as Systems Engineer for Cisco Systems in Singapore.

For more information about my interests, publications, and also how to contact me, visit my personal website:


Bioinformatics (BB2441), assistant | Course web

Systems biology (CB2030), assistant | Course web

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