From Network Inference to the Study of Human Diseases: Inference and Modelling

Paola Lecca, Angela Re, Adaoha Ihekwaba, Ivan Mura, Thanh-Phuong Nguyen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


The molecular background of the phenotypic variability in human diseases has been investigated and a spectrum of relations between clinical syndromes and molecular features have been identified. Although some genes have emerged as important players in the pathogenesis of diseases, the precise molecular machinery involved in human diseases remains largely unknown. Network medicine has come to the scene to explore complex associations between diseases and thus to infer the pathogenic mechanism of a particular disease. Based on network biology, network modeling, and network mining, several network-based approaches have made remarkable contributions to the study of human diseases. The methods offer better insights into the pathobiology of diseases from a systems point of view and have great potential for further clinical and pharmacological applications. In this chapter, we firstly present key points in network medicine and related work. Secondly, we review some available databases and tools for studying human diseases on the basis of network data. Thirdly, a practical application of network medicine for neurodegenerative diseases is introduced. Finally, we present conclusions and perspectives on network medicine.
Original languageEnglish
Title of host publicationComputational Systems Biology
Number of pages22
ISBN (Print)978-0-08-100095-3
Publication statusPublished - 2016

Publication series

NameComputational Systems Biology


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