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This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics.
The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own.
Sample Chapter(s)
Chapter 1.1: Introduction (164 KB)
Chapter 1.2: Algorithmic Implementation (464 KB)
Chapter 1.3: Data Generation and Analysis (959 KB)
Chapter 1.4: Biological Application (431 KB)
Chapter 1.5: Conclusions (245 KB)
Contents:
- Exploring RNA Intermediate Conformations with the Massively Parallel Genetic Algorithm (B A Shapiro et al.)
- Introduction to Self-Assembling DNA Nanostructures for Computation and Nanofabrication (T H LaBean)
- Mapping Sequence to Rice FPC (C Soderlund et al.)
- Graph Theoretic Sequence Clustering Algorithms and Their Applications to Genome Comparison (S Kim)
- The Protein Information Resource for Functional Genomics and Proteomics (C H Wu)
- High-Grade Ore for Data Mining in 3d Structures (J S Richardson & D C Richardson)
- Protein Classification: A Geometric Hashing Approach (X Wang & J T L Wang)
- Interrelated Clustering: An Approach for Gene Expression Data Analysis (C Tang et al.)
- Creating Metabolic Network Models Using Text Mining and Expert Knowledge (J A Dickerson et al.)
- Phyloinformatics and Tree Networks (W H Piel)
Readership: Molecular biologists who rely on computers and mathematical scientists with interests in biology.
