Elloumi M., Zomaya A.Y. (Eds.). Algorithms in Computational Molecular Biology: Techniques, Approaches and Applications

Wiley, 2011. - 1085 p.
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.Strings processing and application to biological sequences.
String data structures for computational molecular biology
Efficient restricted-case algorithms for problems in computational biology
Finite automata in pattern matching
New developments in processing of degenerate sequences
Exact search algorithms for biological sequences
Algorithmic aspects of arc-annotated sequences
Algorithmic issues in DNA barcoding problems
Recent advances in weighted DNA sequences
DNA computing for subgraph isomorphism problem and related problems
Analysis of biological sequences.
Graphs in bioinformatics
A flexible data store for managing bioinformatics data
Algorithms for the alignment of biological sequences
Algorithms for local structural alignment and structural motif identification
Evolution of the clustal family of multiple sequence alignment programs
Filters and seeds approaches for fast homology searches in large datasets
Novel combinatorial and information-theoretic alignment-free distances for biological data mining
In silico methods for the analysis of metabolites and drug molecules
Motif finding and structure prediction.
Motif finding algorithms in biological sequences
Computational characterization of regulatory regions
Algorithmic issues in the analysis of chip-seq data
Approaches and methods for operon prediction based on machine learning techniques
Protein function prediction with data-mining techniques
Protein domain boundary prediction
An introduction to RNA structure and pseudoknot prediction
Phylogeny reconstruction.
Phylogenetic search algorithms for maximum likelihood
Heuristic methods for phylogenetic reconstruction with maximum parsimony
Maximum entropy method for composition vector method
V. Microarray data analysis.
Microarray gene expression data analysis
Biclustering of microarray data
Computational models for condition-specific gene and pathway inference
Heterogeneity of differential expression in cancer studies: algorithms and methods
Analysis of genomes.
Comparative genomics: algorithms and applications
Advances in genome rearrangement algorithms
Computing genomic distances: an algorithmic viewpoint
Wavelet algorithms for DNA analysis
Haplotype inference models and algorithms
Analysis of biological networks.
Untangling biological networks using bioinformatics
Probabilistic approaches for investigating biological networks
Modeling and analysis of biological networks with model checking
Reverse engineering of molecular networks from a common combinatorial approach
Unsupervised learning for gene regulation network inference from expression data: a review
Approaches to construction and analysis of microRNA-mediated networks