Data mining in bioinformatics

✍ Scribed by Jason T. L. Wang, Mohammed J. Zaki, Hannu Toivonen, Dennis E. Shasha

Publisher: Springer
Year: 2005
Tongue: English
Leaves: 336
Series: Advanced information and knowledge processing
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

The goal of this book is to help readers understand state-of-the-art techniques in biological data mining & data management & includes topics such as: * preprocessing tasks such as data cleaning & data integration as applied to biological data * classification & clustering techniques for microarrays * comparison of RNA structures based on string properties & energetics * discovery of the sequence characteristics of different parts of the genome * mining of haplotypes to find disease markers * sequencing of events leading to the folding of a protein * inference of the subcellular location of protein activity * classification of chemical compounds based on structure * special purpose metrics & index structures for phylogenetic applications * a new query language for protein searching based on the shape of proteins * very fast indexing schemes for sequences & pathways Aimed at computer scientists, necessary biology is explained.

📜 SIMILAR VOLUMES

Data Mining in Bioinformatics

📁 Data Mining in Bioinformatics

✍ Jason T. L. Wang, Mohammed J. Zaki, Hannu T. T. Toivonen, Dennis Shasha (auth.), 📂 Library 📅 2005 🏛 Springer-Verlag London 🌐 English

8. 1. 1 Protein Subcellular Location The life sciences have entered the post-genome era where the focus of biologicalresearchhasshiftedfromgenomesequencestoproteinfunctionality. Withwhole-genomedraftsofmouseandhumaninhand,scientistsareputting more and more e?ort into obtaining information about t

Data Mining in Bioinformatics

📁 Data Mining in Bioinformatics

✍ Jason T. L. Wang, Mohammed J. Zaki, Hannu Toivonen, Dennis E. Shasha 📂 Library 📅 2004 🏛 Springer 🌐 English

Advanced Data Mining Technologies in Bio

📁 Advanced Data Mining Technologies in Bioinformatics

✍ Hui-Huang Hsu 📂 Library 📅 2006 🏛 Idea Group Pub 🌐 English

The technologies in data mining have been successfully applied to bioinformatics research in the past few years, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining play

Data Mining for Bioinformatics

📁 Data Mining for Bioinformatics

✍ Sumeet Dua, Pradeep Chowriappa 📂 Library 📅 2012 🏛 CRC Press 🌐 English

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overv

Data Mining for Bioinformatics Applicati

📁 Data Mining for Bioinformatics Applications

✍ He Zengyou 📂 Library 📅 2015 🏛 Woodhead Publishing 🌐 English

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-

Data Mining for Bioinformatics Applicati

📁 Data Mining for Bioinformatics Applications

✍ He Zengyou 📂 Library 📅 2015 🏛 Woodhead Publishing 🌐 English