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Könyv Association Analysis Techniques and Applications in Bioinformatics Qingfeng Chen

Association Analysis Techniques and Applications in Bioinformatics

Szerző: Qingfeng Chen
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Springer, Berlin
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
61 267 Ft
Advances in experimental technologies have given rise to tremendous amounts of biology data. This no...

Információk a könyvről

Szerző
Qingfeng Chen
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2024
oldal
412
EAN
9789819982509
Enbook ID
44353129
Kiadó
Springer, Berlin
Súly
725
Méretek
155 x 235

Teljes leírás

Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation. The main results and approaches are described in an easy-to-follow way and accompanied by sufficient references and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics. 

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