Biological systems are complicated. They are also, in the technical sense of the word, complex.

Systems are said to be complex if they have properties and behaviors that can only be understood by analyzing how the components of the system interact. Properties of complex systems are said to 'emerge' from the interactions of the system's components.

In the biological realm, complexity reigns at many different scales, from the cooperative and competitive interactions of proteins and DNA, to the development of a mature organism from an embryo, to the behavior of entire ecosystems.

Systems Biology encompasses a broad spectrum of computational and experimental methods. A unifying goal is to generate and visualize large amounts of data and to use that data to model biological processes. The hope is that biological properties can be understood through a systems approach in a way that is not possible using analyses that focus on a much smaller number of components.

In the areas of molecular and cellular biology that are of interest to GIS, physical and/or genetic interactions of many different components of the system are obtained in a high-throughput manner. Experimental and computational biologists work together to use these data to gain greater insight into biological problems of interest. The labs that are part of Systems Biology at the Genome Institute of Singapore work on a wide variety of biological systems including stem cells, early development, cancer, control of the cell cycle, and the interactions of macromolecules.



Key Representative Publications

Loh Y.H, Wu Q, Chew J.L, Vega V.B, Zhang W, Chen X, Bourque G, George L, Leong B, Liu J, Wong K.Y, Sung K.W, Lee C.W, Zhao X.D, Chiu K.P, Lipovich L, Kuznetsov V.A, Robson P, Stanton L.W, Wei C.L, Ruan Y, Lim B and Ng H.H "The Oct4 and Nanog transcription network that regulates pluripotency in mouse embryonic stem cells" Nature Genetics 38:431-440, 2006.

Kuznetsov V.A, Pickalov V.V and Kanapin A.A "Proteome complexity measures based on counting of domain-toprotein links for replicative and non-replicative domains" Bioinformatics of genome regulation and structure v.2 Eds: N. Kolchanov, R. Hofestaedt, L. Milanesi, Springer: NY, USA 329-341, 2006.

Granek J.A and Clarke N.D "Explicit equilibrium modeling of transcription factor binding and gene regulation" Genome Biology 6: R87, 2005.

The FANTOM Consortium, P. Carninci, ..., Chiu K.P, Liu E.T, Ruan Y, Wei C.L, Lipovich L, et al, RIKEN Genome Exploration Research Group, Genome Science Group - Genome Network Project Core Group "The Transcriptional Landscape of the Mammalian Genome" Science 309:1559-1563, 2005.

Chew J.L, Loh Y.H, Robson P, Lim B, Ang Y.S, Pin L, Yeap L.S, Tam W.L, Chen X, Zhang W.S and Ng H.H "Reciprocal Transcriptional Regulation of Pou5f1 and Sox2 Via the Oct4/Sox2 Complex in Embryonic Stem Cells" Molecular & Cellular Biology 25:6031-6046, 2005.

Bourque G and Sankoff D "Improving gene network inference by comparing expression time-series across species, developmental stages or tissues" J. of Bioinformatics and Computational Biology 765-784, 2004.

Karuturi R.K.M and Liu J.H "Improved Fourier Transform Method for Unsupervised Cell-cycle Regulated Gene Prediction. Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference, Stanford, CA" 2004.

Peng X, Karuturi R.K.M, Miller L.D, Lin K, Kondu P, Jia Y, Wang L, Wong L, Liu E.T, Balasubramanian M.K and Liu J.H "Identification of cell cycle-regulated genes in fission yeast" Mol Biol Cell 16: 1026-1042, 2004.