About the Book
Cheminformatics with Python provides a ground-up, practical introduction that helps reader make effective use of the software. In four parts, including programming, data, methods, and applications, the book provides a brief introduction to Python language and related scientific computing, cheminformatics, machine learning, and deep learning packages and presents a systematic study of the representation of instrumental data, including molecular structures and common chemical databases. The methods section covers analytical signal processing, multivariate calibration, multivariate resolution, classical machine learning, and deep learning methods. Finally, the application section presents case studies of successful applications of cheminformatics in analytical chemistry, metabolomics, drug discovery, and more.
A supporting appendix section and the necessary mathematical, statistical, and information theory-related theories are provided, along with practical tips such as code editors and source code management. Online coding materials on GitHub and an individual Jupyter notebook for each chapter further support practical learning. This book will be a great resource for senior undergraduate students, graduate students, post-docs, and professors primarily in the field of computational and analytical chemistry.
Table of Contents:
1. Introduction
Part I: Python for Cheminformatics
2. Python Basics
3. Python Packages
Part II: Data and Databases
4. Representation of Instrumental Signals
5. Representation of Molecules
6. Databases in Chemistry
Part III: Methods
7. Instrumental Signal Processing
8. Multivariate Calibration and Resolution
9. Manipulation of Molecular Structures
10. Classic Machine Learning Methods
11. Deep Learning Methods
Part IV: Applications
12. Cheminformatics in Analytical Chemistry
13. Cheminformatics in Metabonomics
14. Cheminformatics in Drug Discovery
15. Cheminformatics in Materials Science
Appendices
A: Necessary Knowledge of Mathematics
B: Editors and IDEs
About the Author :
Zhimin Zhang is an Associate Professor of Analytical Chemistry at Central South University, PR China. He received his Bachelor and Doctoral degrees from Central South University. His main research interests are chemometrics and cheminformatics, machine learning and deep learning, high-resolution mass spectrometry and its resolution methods, Raman spectroscopy and its resolution methods, and chemometric software development. In recent years, he has hosted 4 national and provincial research projects, including the National Natural Science Foundation of China (NSFC) Youth Fund, National Major Scientific Instrument and Equipment Development Special Task, Hunan Provincial Natural Science Foundation Youth Fund, and National Postdoctoral Fund. He has also cooperated with B&W Tek, Shimadzu, ExxonMobil, National University of Defense Technology, Yunnan Institute of Tobacco Agricultural Science, and other enterprises and research institutions in the fields of data analysis and software development. He has published more than 100 SCI papers in Analytical Chemistry, Bioinformatics, Analytica Chimica Acta, Analyst, Chemometrics and Intelligent Laboratory Systems, Journal of Chemometrics, and other journals. He has been engaged in the development of chemometric software for analytical instrument data processing for a long time and has developed several sets of chemometric software and obtained 10 computer software copyrights. The developed chemometric software BWIQ (http://bwtek.com/products/bwiq/) is sold worldwide together with B&W Tek Raman and NIR spectrometers. He is currently an invited reviewer for Analytical Chemistry, Chemometrics and Intelligent Laboratory Systems, Analytica Chimica Acta, Journal of Chromatography A, and Analyst.
Hongmei Lu is a Professor of Analytical Chemistry at Central South University, PR China. She received her Bachelor and Doctoral degrees from Central South University. She is Vice Dean of the College of Chemistry and Chemical Engineering, Specially Appointed Professor of Furong Scholar, Editor of Chemometrics and Intelligent Laboratory System, Member of the Committee of Computational Chemistry of the Chinese Chemical Society, Executive Director of Hunan Chemical and Chemical Society, Executive Director of Hunan Provincial Inspection and Testing. She is also a member of the Executive Director of Hunan Chemical and Chemical Society, Executive Director of Hunan Provincial Inspection and Testing Society, Director of China Biological Testing and Monitoring Industry Technology Innovation Strategic Alliance, Director of National Chemistry Experimental Demonstration Center, Head of National Virtual Simulation Project, Member of the Tenth Hunan Youth Federation, Baosteel Excellent Teacher Award, Yuying Talent Program of Central South University. She has been awarded the second prize in Natural Science Award of Hunan Province, the third prize in Science and Technology Progress Award of Hunan Province, the third prize in Science and Technology Award of China Petroleum and Chemical Automation Industry, the first prize in Science and Technology Progress Award of Huaihua City, and the first prize of Teaching Achievement of Hunan Province. She has published more than 160 papers in international academic journals such as Anal Chem, Trend Anal Chem, Metabolomics, Bioinformatics, J Chromatogr A, etc. She has co-authored 3 monographs in English. She has led more than 20 research projects, including 7 National Natural Science Foundation of China projects. She has received funding from the Biotechnology and Life Sciences Research Council (BBSRC) and the Erasmus Mundus Program of the European Union to visit and lecture at the University of Manchester (UK), the Universities of Cadiz and Barcelona (Spain), the University of Algarve (Portugal), and the University of Bergen (Norway). In recent years, she has hosted the international conferences "6th International Conference On Separation Science and Technology" and "Chemometrics in Analytical Chemistry, 2015". She has participated in various international and domestic academic conferences and made invited presentations.
Ming Wen is a Research Assistant at the College of Chemistry and Chemical Engineering, Central South University, PR China. He received his Bachelor’s degree from Henan Normal University and Doctoral degrees from Central South University. His main research interests are in the fields of drug discovery, hyperspectral imaging, machine learning, and deep learning. In recent years, he has participated in 4 national and provincial research projects and published more than 10 papers in bioinformatics, Journal of proteome research amongst other publications.
