Best Reference Books – Sequence Analysis and Data Mining

We have compiled the list of Top 10 Best Reference Books on Sequence Analysis and Data Mining subject. These books are used by students of top universities, institutes and colleges. Here is the full list of top 10 best books on Sequence Analysis and Data Mining along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Sequence Analysis and Data Mining subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Sequence Analysis and Data Mining" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

1. “Data Mining Techniques for Protein Sequence Analysis” by Duraisamy Ramyachitra and Pandurangan Manikandan

“Data Mining Techniques for Protein Sequence Analysis” Book Review: In this book are discussed principles of bioinformatics, datamining, evolutionary computing and its mutual intersection. Data-mining by means of selected evolutionary techniques are discussed with attention on protein structure, segmentation and state of art in the field of evolutionary algorithms use. Basic principles and terminology of evolutionary algorithms, as well as two evolutionary algorithms are mentioned here – differential evolution and self-organizing migrating algorithm.

2. “Sequence Data Mining (Advances in Database Systems)” by Guozhu Dong and Jian Pei

“Sequence Data Mining (Advances in Database Systems)” Book Review: This book details both frequent/closed sequence patterns and the similarity sequence patterns and motifs. Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place. Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.

3. “Problems and Solutions in Biological Sequence Analysis” by Mark Borodovsky and Svetlana Ekisheva

“Problems and Solutions in Biological Sequence Analysis” Book Review: This book provides a large collection of bioinformatics problems with accompanying solutions. Notably, the problem set includes all of the problems offered in Biological Sequence Analysis, by Durbin et al. (Cambridge, 1998), widely adopted as a required text for bioinformatics courses at leading universities worldwide. Although many of the problems included in Biological Sequence Analysis as exercises for its readers have been repeatedly used for homework and tests, no detailed solutions for the problems were available. Bioinformatics instructors had therefore frequently expressed a need for fully worked solutions and a larger set of problems for use on courses. This book provides just that: following the same structure as Biological Sequence Analysis and significantly extending the set of workable problems, it will facilitate a better understanding of the contents of the chapters in BSA and will help its readers develop problem-solving skills that are vitally important for conducting successful research in the growing field of bioinformatics.

4. “Advances in Knowledge Discovery and Data Mining” by Joshua Zhexue Huang and Longbing Cao

“Advances in Knowledge Discovery and Data Mining” Book Review: This book constitutes the refereed proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China, May 2007. It covers new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems.

5. “Advances in Sequence Analysis: Theory, Method, Applications (Life Course Research and Social Policies)” by Philippe Blanchard and Felix Bühlmann

“Advances in Sequence Analysis: Theory, Method, Applications (Life Course Research and Social Policies)” Book Review: This book includes innovative contributions on life course studies, transitions into and out of employment, contemporaneous and historical careers, and political trajectories. The approach presented in this book is now central to the life-course perspective and the study of social processes more generally. This volume promotes the dialogue between approaches to sequence analysis that developed separately, within traditions contrasted in space and disciplines. It includes the latest developments in sequential concepts, coding, atypical datasets and time patterns, optimal matching and alternative algorithms, survey optimization, and visualization. Overall the book reassesses the classical uses of sequences and it promotes new ways of collecting, formatting, representing and processing them. The introduction provides basic sequential concepts and tools, as well as a history of the method. Chapters are presented in a way that is both accessible to the beginner and informative to the expert.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn | Youtube | Instagram | Facebook | Twitter