Rudiyanto Gunawan
Chemical and Biological Systems
Engineering Laboratory
ETH Zurich
Group Webpage

What do we do?

At the Chemical and Biological Systems Engineering Laboratory, we develop tools for systems modelling and the analysis of chemical and biological networks. Our mission is to create enabling theories and computational methods for the generation of systems insights, as well as for understanding and acquiring knowledge in chemical, biological and medical applications. Our research spans multiple length and time scales of cell biology, from gene/signalling/metabolic networks in single cells to the ageing process in human and cell culture bioreactors in the pharmaceutical industry.

Highlights 2016

During the course of 2016, our team released two tools which were described in separate publications in the journals of Bioinformatics and BMC Bioinformatics:

  1. DeltaNet: DeltaNet is a bioinformatics tool which is used to infer the gene targets of drug compounds from gene transcriptional profiles;
  2. TRaCE+ (Transitive Reduction and Closure Ensemble+): TRaCE+ is a tool for gene regulatory network inference from gene transcriptional profiles. TRaCE+ extends the capability of our algorithm TRaCE by inferring the regulatory modes (activation/repression).

Furthermore, the team’s analysis of single cell gene transcriptional profiles of chicken erythrocytic cell differentiation revealed a transition period marked by a peak in the cell-to-cell variability of the gene expression and the connectivity of the gene co-expression network. Importantly, this peak preceded an irreversible cellular commitment to differentiation. 

Main publications 2016

  • Noh H and Gunawan R. Inferring gene targets of drugs and chemical compounds from gene expression profiles. Bioinformatics 2016;32(4):2120-7.
  • Ud-Dean SMM et al. TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments. BMC Bioinformatics 2016;17:252.
  • Richard A et al. Single-cell-based analysis highlights a surge in cell-to-cell molecular variability preceding irreversible commitment in a differentiation process. PLoS Biol 2016; 14(12):e1002585.

Our research topics: