Biological Complexity and the Need for Computational Approaches View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Hiroaki Kitano

ABSTRACT

“Biological systems are highly complicated, non-linear, and require very high-dimensional and high volume data analysis. In reality, we are as human beings not good at handling such data. How can we understand biological systems in face of this complexity? This is the major challenge for biological and biomedical research. I would claim that a combination of artificial intelligence and human research is the most powerful way to proceed, rather than relying solely on the human brain in trying to understand biology… The most powerful research team will consist of highly intelligent AI systems and human researchers. Just like we need high-throughput measurement devices and next generation sequencers for any high profile research institution in systems biology today, so will highly intelligent AI systems sooner or later be mandatory for any future high profile research institution.” More... »

PAGES

169-180

Book

TITLE

Philosophy of Systems Biology

ISBN

978-3-319-46999-7
978-3-319-47000-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-47000-9_16

DOI

http://dx.doi.org/10.1007/978-3-319-47000-9_16

DIMENSIONS

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50 schema:description “Biological systems are highly complicated, non-linear, and require very high-dimensional and high volume data analysis. In reality, we are as human beings not good at handling such data. How can we understand biological systems in face of this complexity? This is the major challenge for biological and biomedical research. I would claim that a combination of artificial intelligence and human research is the most powerful way to proceed, rather than relying solely on the human brain in trying to understand biology… The most powerful research team will consist of highly intelligent AI systems and human researchers. Just like we need high-throughput measurement devices and next generation sequencers for any high profile research institution in systems biology today, so will highly intelligent AI systems sooner or later be mandatory for any future high profile research institution.”
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