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 genome-level 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, yeasts, worms, flies, mice and humans.
- Gsponer, J., Futschik, M.E., Teichmann, S.A. and Madan Babu, M. (2008)
Tight regulation of unstructured proteins: from transcript synthesis to protein.
Science 322: 1365-8
- Janga, S.C., Collado-Vides, J. and 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. and Pombo, A. (2008)
Eukaryotic gene regulation in three dimensions and its impact on genome evolution.
Curr Opin Genet Dev 18: 571-82
- Melis Kayikci
- Aiveliagaram (AJ) Venkatakrishnan
- Charles Ravarani
- Yoichiro Sugimoto
- Natalia Sanchez de Groot
- Sreenivas Chavali
- Guilhem Chalancon
- Marc Torrent Burgas
- Daniel Estevez Prado
- Tilman Flock
- Balaji Santhanam
- Marion Ouédraogo
- Robert Weatheritt
- Natasha Latysheva