Isbn: 9786139874019 - machine learning & text mining methods for mining biological data sets (9 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. 100 pages. 8.66x5.91x0.23 inches. In Stock.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    EUR 47,95

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    Taschenbuch. Condición: Neu. Machine Learning & Text Mining methods for mining biological data sets | Kamal Rawal (u. a.) | Taschenbuch | 100 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139874019 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jul 2018, 2018

    6139874017 / 9786139874019

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 54,90

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Text mining or data mining is a knowledge discovery tool which is referred to the process of extracting interesting and non-trivial patterns from a database of unstructured texts. Here, we present a new machine learning system to mine biological data sets (text data/scientific literature) to understand relations between two genes (two terms) in a scientific text. The system mimics human intelligence and accurately determine the relations between two genes/proteins. We manually curated literature data sets using deep curation to generate training set. Furthermore, our prediction results were validated with the help of experts to generate confidence to use our system in different real time situations. Next the system was made automated so that people across the world can determine relations between two or more molecules in a text using support vector machines. This semi-automated system is frequently applied by our team to write reviews on a given topic. For example, our team was able to screen and mine over 36000 papers to write a review on molecular docking tools. In 2016, our team were able to reconstruct obesity molecular network using this system(Jaisri et al 2016, Plos One). 100 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 45,45

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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rawal KamalDr. Rawal is an interdisciplinary Scientist-Physician with extensive experience in building data driven precision medicine systems. Being a strong proponent & practitioner of machine learning, he is passionate to build soc. …

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    EUR 90,07

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    Cantidad disponible: 4 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 62,49

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Text mining or data mining is a knowledge discovery tool which is referred to the process of extracting interesting and non-trivial patterns from a database of unstructured texts. Here, we present a new machine learning system to mine biological data sets (text data/scientific literature) to understand relations between two genes (two terms) in a scientific text. The system mimics human intelligence and accurately determine the relations between two genes/proteins. We manually curated literature data sets using deep curation to generate training set. Furthermore, our prediction results were validated with the help of experts to generate confidence to use our system in different real time situations. Next the system was made automated so that people across the world can determine relations between two or more molecules in a text using support vector machines. This semi-automated system is frequently applied by our team to write reviews on a given topic. For example, our team was able to screen and mine over 36000 papers to write a review on molecular docking tools. In 2016, our team were able to reconstruct obesity molecular network using this system(Jaisri et al 2016, Plos One).…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139874017 / 9786139874019

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    EUR 88,99

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    Condición: New. PRINT ON DEMAND.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jul 2018, 2018

    6139874017 / 9786139874019

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 54,90

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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Text mining or data mining is a knowledge discovery tool which is referred to the process of extracting interesting and non-trivial patterns from a database of unstructured texts. Here, we present a new machine learning system to mine biological data sets (text data/scientific literature) to understand relations between two genes (two terms) in a scientific text. The system mimics human intelligence and accurately determine the relations between two genes/proteins. We manually curated literature data sets using deep curation to generate training set. Furthermore, our prediction results were validated with the help of experts to generate confidence to use our system in different real time situations. Next the system was made automated so that people across the world can determine relations between two or more molecules in a text using support vector machines. This semi-automated system is frequently applied by our team to write reviews on a given topic. For example, our team was able to screen and mine over 36000 papers to write a review on molecular docking tools. In 2016, our team were able to reconstruct obesity molecular network using this system(Jaisri et al 2016, Plos One).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch.…