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dc.contributor.authorDimitrios Vlachakis*
dc.date.accessioned2021-02-12T05:09:34Z
dc.date.available2021-02-12T05:09:34Z
dc.date.issued2019*
dc.date.submitted2019-10-03 07:51:53*
dc.identifier37935*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/60437
dc.description.abstractSystems biology is the inevitable outcome of long years of knowledge acquisition and data accumulation. The aim of systems biology is to integrate in a seamless way all existing knowledge in interconnected disciplines, stretching from modern biomedical research to physics, chemistry, and mathematics. The main integration tool of such complex biomedical systems is via computational and mathematical modeling. In this direction, a series of state-of-the-art computer science techniques are used, namely, data mining and fusion, machine learning, and deep learning all under the prism of big data. All in all, systems biology is at the arrowhead of modern and state-of-the-art biomedical research by attempting to address key biological questions describing holistically complex biological systems.*
dc.languageEnglish*
dc.subjectR858-859.7*
dc.subject.otherBiomedical Engineering*
dc.subject.otherPhysical Sciences*
dc.subject.otherEngineering and Technology*
dc.subject.otherTechnology*
dc.subject.otherBioinformatics*
dc.titleSystems Biology*
dc.typebook
oapen.identifier.doi10.5772/intechopen.79601*
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6*
oapen.relation.isbn9781838808037*
oapen.relation.isbn9781838808051*
oapen.relation.isbn9781838808044*
oapen.pages106*
oapen.edition1st Edition*


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