ACM-BCB 2015 Tutorial: Computational Construction of Intra-Cellular Networks


Tutorial Presenter


Tolga Can, Department of Computer Engineering, Middle East Technical University, Ankara, Turkey, Contact: tcan [at] metu [dot] edu [dot] tr

Tutorial summary

Relational data about cellular components accumulate at public databases at an increasing rate. Protein-protein interactions (PPI), metabolic reactions, transcriptional regulatory interactions, and genetic interactions are available for many model organisms. In parallel with accumulation of biological data, computational techniques are developed for inferring relations about cellular components at higher accuracy and coverage. In this tutorial, recent computational techniques for inference of several types of biological networks will be presented. This two units length tutorial will first give an overview of different types of biological networks, such as 1) PPI networks including signaling networks and protein complexes, 2) transcriptional regulation networks with different regulatory elements such as transcription factors and microRNAs, 3) metabolic networks, and 4) functional association networks such as co-expression and genetic interaction networks. On PPI networks, we will discuss simultaneous prediction and alignment of networks (Alkan and Erten, 2015) and methods for directing the undirected edges in experimental data. At the second half, we will discuss construction of transcriptional regulation networks by utilizing ENCODE data (Gerstein et al, 2012). We will conclude by models for genome-scale metabolic networks (Dias et al, 2015) and methods for validation of such metabolic models (Schmidt et al, 2014).

Tutorial description

This tutorial's main objective is to discuss recent computational techniques for inference of different types of intra-cellular networks. A review of some of the recent papers on this subject will be given (see the Reading List below). The intended audience are graduate students or post-doctoral researchers who are working or interested in computational systems biology and in particular inference of biological networks. Some computational background on graph theory and design and analysis of algorithms is required to follow the content. The methods will be described in detail and possible alternatives and extensions will be discussed. This tutorial does not include hands-on exercises on the discussed methods; but, a theoretical discussion of the subject matter is aimed.

Tutorial Slides (Power Point)

Tutorial Slides (PDF)

Reading List

  1. SiPAN: simultaneous prediction and alignment of protein-protein interaction networks by Alkan and Erten, 2015.
  2. lpNet: a linear programming approach to reconstruct signal transduction networks by Matos et al., 2015.
  3. Directed Network Wiring Identifies a Key Protein Interaction in Embryonic Stem Cell Differentiation by Yasui et al, 2014.
  4. A directed protein interaction network for investigating intracellular signal transduction by Vinayagam et al, 2011.
  5. Architecture of the human regulatory network derived from ENCODE data by Gerstein et al, 2012.
  6. Circuitry and Dynamics of Human Transcription Factor Regulatory Networks by Neph et al, 2012.
  7. Combining tree-based and dynamical systems for the inference of gene regulatory networks by Huynh-Thu and Sanguinetti, 2014.
  8. Reconstructing genome-scale metabolic models with merlin, Dias et al, 2015.
  9. Computing autocatalytic sets to unravel inconsistencies in metabolic network reconstructions, Schmidt et al, 2014.
  10. Large-Scale Signaling Network Reconstruction, Hashemikhabir et al, 2012.