About: Data Mining for Systems Biology

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An Entity of Type : rdac:C10001, within Data Space : data.idref.fr associated with source document(s)

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type	frbr:Work rdac:C10001
alternative label	Data mining for systems biology, methods and protocols
dc:subject	Exploration de données Systems Biology Systems biology Bioinformatics. Life Sciences. Life sciences. Biological models Biologie des systèmes -- méthodes Fouille de données -- méthodes Biologie systémique Analyse de séquence -- méthodes Biologie des systèmes -- Manuel de laboratoire Biologie systémique -- Manuels de laboratoire Data mining -- Laboratory manuals Exploration de données -- Manuels de laboratoire Fouille de données -- Manuel de laboratoire Systems biology -- Laboratory manuals
preferred label	Data Mining for Systems Biology
Language	http://lexvo.org/id/iso639-3/eng
Subject	http://www.idref.fr/040821544/id http://www.idref.fr/040846644/id http://www.idref.fr/035198222/id http://www.idref.fr/114598185/id http://www.idref.fr/038961520/id http://www.idref.fr/154377066/id http://www.idref.fr/121932036/id http://www.idref.fr/027792587/id
dc:title	Data Mining for Systems Biology
note	This fully updated book collects numerous data mining techniques, reflecting the acceleration and diversity of the development of data-driven approaches to the life sciences. The first half of the volume examines genomics, particularly metagenomics and epigenomics, which promise to deepen our knowledge of genes and genomes, while the second half of the book emphasizes metabolism and the metabolome as well as relevant medicine-oriented subjects. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that is useful for getting optimal results. Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols, Second Edition serves as an ideal resource for researchers of biology and relevant fields, such as medical, pharmaceutical, and agricultural sciences, as well as for the scientists and engineers who are working on developing data-driven techniques, such as databases, data sciences, data mining, visualization systems, and machine learning or artificial intelligence that now are central to the paradigm-altering discoveries being made with a higher frequency.
dc:type	Text
http://iflastandar...bd/elements/P1001	http://iflastandards.info/ns/isbd/terms/contentform/T1009
rdaw:P10219	2013
has content type	http://rdaregistry.info/termList/RDAContentType/1020
is primary topic of	http://www.idref.fr/211698253
is rdam:P30135 of	http://www.sudoc.fr/166725692/id http://www.sudoc.fr/171694082/id http://www.sudoc.fr/231703945/id http://www.sudoc.fr/229499317/id

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