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Record Nr. |
UNINA9910139003203321 |
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Titolo |
Data mining in drug discovery / / edited by Rémy D. Hoffmann, Arnaud Gohier, and Pavel Pospisil |
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Pubbl/distr/stampa |
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Weinheim : , : Wiley-VCH, , [2014] |
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©2014 |
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ISBN |
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3-527-65600-6 |
3-527-65598-0 |
3-527-65601-4 |
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Descrizione fisica |
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1 online resource (347 p.) |
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Collana |
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Methods and principles in medicinal chemistry ; ; vol. 57 |
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Altri autori (Persone) |
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HoffmannRémy D |
GohierArnaud |
PospisilPavel |
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Disciplina |
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Soggetti |
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Drug development - Computer simulation |
Data mining |
Drugs - Research |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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part one. Data sources -- part two. Analysis and enrichment -- part three. Applications to polypharmacology -- part four. system biology approaches. |
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Sommario/riassunto |
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Written for drug developers rather than computer scientists, this monograph adopts a systematic approach to mining scientifi c data sources, covering all key steps in rational drug discovery, from compound screening to lead compound selection and personalized medicine. Clearly divided into four sections, the first part discusses the different data sources available, both commercial and non-commercial, while the next section looks at the role and value of data mining in drug discovery. The third part compares the most common applications and strategies for polypharmacology, where data mining |
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