Integration, visualization and analysis of human interactome

Chiara Pastrello; Elisa Pasini; Max Kotlyar; David Otasek; Serene Wong; Waheed Sangrar; Sara Rahmati; Igor Jurisica

doi:10.1016/j.bbrc.2014.01.151

Integration, visualization and analysis of human interactome

Biochem Biophys Res Commun. 2014 Mar 21;445(4):757-73. doi: 10.1016/j.bbrc.2014.01.151. Epub 2014 Feb 1.

Authors

Chiara Pastrello¹, Elisa Pasini², Max Kotlyar¹, David Otasek¹, Serene Wong³, Waheed Sangrar¹, Sara Rahmati⁴, Igor Jurisica⁵

Affiliations

¹ Princess Margaret Cancer Centre, University Health Network and TECHNA Institute for the Advancement of Technology for Health, TMDT, Room 11-314, 101 College Street, Toronto, ON M5G 1L7, Canada.
² CRO Aviano National Cancer Institute, Cancer Bio-Immunotherapy Unit, Via Franco Gallini 2, 33081 Aviano, PN, Italy.
³ Princess Margaret Cancer Centre, University Health Network and TECHNA Institute for the Advancement of Technology for Health, TMDT, Room 11-314, 101 College Street, Toronto, ON M5G 1L7, Canada; York University, Department of Computer Science and Engineering, Toronto, ON, Canada.
⁴ Princess Margaret Cancer Centre, University Health Network and TECHNA Institute for the Advancement of Technology for Health, TMDT, Room 11-314, 101 College Street, Toronto, ON M5G 1L7, Canada; University of Toronto, Department of Medical Biophysics, Toronto, ON, Canada.
⁵ Princess Margaret Cancer Centre, University Health Network and TECHNA Institute for the Advancement of Technology for Health, TMDT, Room 11-314, 101 College Street, Toronto, ON M5G 1L7, Canada; University of Toronto, Department of Medical Biophysics, Toronto, ON, Canada; University of Toronto, Department of Computer Science, Toronto, ON, Canada. Electronic address: juris@ai.utoronto.ca.

PMID: 24491561
DOI: 10.1016/j.bbrc.2014.01.151

Abstract

Data integration and visualization are crucial to obtain meaningful hypotheses from the diversity of 'omics' fields and the large volume of heterogeneous and distributed data sets. In this review we focus on network analysis as a key technique to integrate, visualize and extrapolate relevant information from diverse data. We first describe challenges in integrating different types of data and then focus on systematically exploring network properties to gain insight into network function. We also describe the relationship between network structures and function of elements that form it. Next, we highlight the role of the interactome in connecting data derived from different experiments, and we stress the importance of network analysis to recognize interaction context-specific features. Finally, we present an example integration to demonstrate the value of the network approach in cancer research, and highlight the importance of dynamic data in the specific context of signaling pathways.

Keywords: Gastric cancer; Interactome; Network analysis; Omics; Visual data mining.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Computational Biology / methods*
Gene Regulatory Networks
Humans
Protein Interaction Mapping / methods*
Protein Interaction Maps
Stomach Neoplasms / genetics
Stomach Neoplasms / metabolism