Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques

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9781615209118: Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques

Chemoinformatics is a scientific area that endeavours to study and solve complex chemical problems using computational techniques and methods.

Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques provides an overview of current research in machine learning and applications to chemoinformatics tasks. As a timely compendium of research, this book offers perspectives on key elements that are crucial for complex study and investigation.

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About the Author:

Huma Lodhi obtained her Ph.D. in computer science from University of London. She is a researcher with the department of Computing, Imperial College London. She has published in leading international journals, books, conference proceedings and has edited a volume Elements of Computational Systems Biology (Wiley Series in Bioinformatics), (2010) by Huma M Lodhi and Stephen H Muggleton (Editors), Wiley. Her research interests are machine learning and data mining and their application to tasks in bioinformatics, chemoinformatics and computation systems biology.

Yoshihiro Yamanishi is a faculty member at Centre for Computational Biology, Mines ParisTech, France. He is also a researcher in the department of Bioinformatics and Computational Systems Biology of Cancer, Mines ParisTech - Institut Curie - INSERM U900. He is working on statistics and machine learning for bioinformatics, chemoinformatics, and genomic drug discovery. He obtained his Ph.D in 2005 from Kyoto University in Japan. He was a post-doctoral research fellow at Center for Geostatistics, Ecole des Mines de Paris from 2005 to 2006. He was an assistant professor at Institute for Chemical Research, Kyoto University from 2006 to 2007.

Review:

The book presents cutting edge tools and strategies to solving problems in chemoinformatics. It explains key elements of the filed. Authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development and progress in the field of chemoinoformatics. --Huma Lodhi (Imperial College, UK); Yoshihiro Yamanishi (Kyoto University, Japan)

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