Biological networks inference, also referred to as 'reverse engineering', is the scientific process of using (low- and high-throughput) experimental data, statistical and computational techniques to reconstruct how the elements of the biological network (genes, proteins, signaling molecules, cells) interact and operate as a system. We briefly outline inference and reconstruction approaches of some among the most relevant types of biological networks in molecular biology and neuroscience, and some of the most promising methodologies applied in the recent field of network medicine.

Network Inference and Reconstruction in Bioinformatics

2018

Abstract

Biological networks inference, also referred to as 'reverse engineering', is the scientific process of using (low- and high-throughput) experimental data, statistical and computational techniques to reconstruct how the elements of the biological network (genes, proteins, signaling molecules, cells) interact and operate as a system. We briefly outline inference and reconstruction approaches of some among the most relevant types of biological networks in molecular biology and neuroscience, and some of the most promising methodologies applied in the recent field of network medicine.
2018
Istituto Applicazioni del Calcolo ''Mauro Picone''
978-0-12-811432-2
Computational biology
Gene co-expression networks
Gene regulatory networks
Metabolic networks
Network analysis
Network medicine
Neuroscience
Protein-protein interactions
Signaling networks
Statistical inference
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/355625
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