- Išsiųsime per 10–14 d.d.
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- Autorius: Ilkka Havukkala
- Leidėjas: World Scientific Publishing Company
- Metai: 2010
- Puslapiai: 307
- ISBN-10: 9812790365
- ISBN-13: 9789812790361
- Formatas: 15.5 x 22.9 x 2.3 cm, kieti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Biodata Mining and Visualization: Novel Approaches (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
There is a lack of an exposition on interdisciplinary and innovative methods of data mining and visualization for biodata. This book fills the gap by introducing an interdisciplinary set of the most recent methods and references on novel techniques from artificial intelligence, data mining, engineering, pattern recognition, and ontological data mining fields that are applicable to bioinformatics. The latest novel approaches are explained in detail, their advantages and disadvantages are summarized, and pointers to the future development of new applications are given. By widening the pool from which biologists and bioinformaticians can adopt methods for biodata mining and visualization, computational data mining experts in nonbiological fields are also encouraged to utilize their expertise in order to contribute to the progress of computational biology, thus enhancing the collaboration between these two disciplines.
EXTRA 15 % nuolaida su kodu: ENG15
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- Autorius: Ilkka Havukkala
- Leidėjas: World Scientific Publishing Company
- Metai: 2010
- Puslapiai: 307
- ISBN-10: 9812790365
- ISBN-13: 9789812790361
- Formatas: 15.5 x 22.9 x 2.3 cm, kieti viršeliai
- Kalba: Anglų Anglų
There is a lack of an exposition on interdisciplinary and innovative methods of data mining and visualization for biodata. This book fills the gap by introducing an interdisciplinary set of the most recent methods and references on novel techniques from artificial intelligence, data mining, engineering, pattern recognition, and ontological data mining fields that are applicable to bioinformatics. The latest novel approaches are explained in detail, their advantages and disadvantages are summarized, and pointers to the future development of new applications are given. By widening the pool from which biologists and bioinformaticians can adopt methods for biodata mining and visualization, computational data mining experts in nonbiological fields are also encouraged to utilize their expertise in order to contribute to the progress of computational biology, thus enhancing the collaboration between these two disciplines.
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