Integration, visualization and analysis of human interactome.
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.
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.
Chiara
C
Pastrello
CRO Aviano National Cancer Institute, Cancer Bio-Immunotherapy Unit, Via Franco Gallini 2, 33081 Aviano, PN, Italy.
Elisa
E
Pasini
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.
Max
M
Kotlyar
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.
David
D
Otasek
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.
Serene
S
Wong
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.
Waheed
W
Sangrar
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.
Sara
S
Rahmati
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.
Igor
I
Jurisica
D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps; D013274:Stomach Neoplasms / Q000235:genetics / Q000378:metabolism
Gastric cancer; Interactome; Network analysis; Omics; Visual data mining