Gsponer, J., Futschik, M.E., Teichmann, S.A. & Madan Babu, M. (2008)
Tight regulation of unstructured proteins:
from transcript synthesis to protein
Science 322, 1365-8.
Janga, S.C., Collado-Vides, J. & Madan Babu M. (2008)
Transcriptional regulation constrains the organization
of genes on eukaryotic chromosomes.
Proc Natl Acad Sci U S A. 105, 15761-6.
Madan Babu, M., Janga, S.C., de Santiago, I. & Pombo, A. (2008)
Eukaryotic gene regulation in three dimensions and its impact on genome evolution..
Curr Opin Genet Dev. 18, 571-82.
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Group Members
- Benjamin Lang
- Aiveliagaram (AJ) Venkatakrishnan
- Kai Kruse
- Natalia Sanchez de Groot
- Sreenivas Chavali
- Marija Buljan
- Guilhem Chalancon
- Marc Torrent Burgas
- Liz Ing-Simmons
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The molecules of life, such as proteins, nucleic acids and metabolites have traditionally been studied in isolation. Recently, it is becoming increasingly clear that they are tied together to form a large, inter-linked, complex system, which is best represented and investigated as a network.
In order to gain a deeper understanding of how living organisms function, it is important to discern the spatio-temporal organization of these biological networks and to understand the evolutionary forces that shape them. Our research investigates the properties and the evolution of biological networks and has the ultimate objective of gaining a genomelevel understanding of regulation in living systems. In particular, we investigate how chemical molecules affect signalling, and how this influences transcriptional and posttranscriptional regulation.
To achieve this objective, we use traditional computational approaches, such as sequence analysis, structure analysis and evolutionary analysis, and develop novel integrative approaches, that use expression data, chromosomal location data, comparative genomics analysis, chemical genomics data, network analysis, genomic variation and phenotype data.
Currently, we are investigating cell-to-cell communication, signalling pathways and transcriptional regulation at a systems level. Using the datasets and methods described above, we approach these problems in a wide variety of model organisms that include bacteria, yeast, worm, fly, mouse and human.
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Group Leaders 
