Computational Systems Bioinformatics

📖 The Scoop

This volume contains about 40 papers covering many of the latest developments in the fast-growing field of bioinformatics. The contributions span a wide range of topics, including computational genomics and genetics, protein function and computational proteomics, the transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications. Abstracts from the keynote addresses and invited talks are also included. The papers not only cover theoretical aspects of bioinformatics but also delve into the application of new methods, with input from computation, engineering and biology disciplines. This multidisciplinary approach to bioinformatics gives these proceedings a unique viewpoint of the field. Sample Chapter(s). Chapter 1: Whole-Genome Analysis of Dorsal Gradient Thresholds in the Drosophila Embryo (102 KB). Contents: Learning Predictive Models of Gene Regulation (C Leslie); Algorithms for Selecting Breakpoint Locations to Optimize Diversity in Protein Engineering by Site-Directed Protein Recombination (W Zheng et al.); Cancer Molecular Pattern Discovery by Subspace Consensus Kernel Classification (X Han); Transcriptional Profiling of Definitive Endoderm Derived from Human Embryonic Stem Cells (H Liu et al.); A Markov Model Based Analysis of Stochastic Biochemical Systems (P Ghosh et al.); Clustering of Main Orthologs for Multiple Genomes (Z Fu & T Jiang); Extraction, Quantification and Visualization of Protein Pockets (X Zhang & C Bajaj); Consensus Contact Prediction by Linear Programming (X Gao et al.); An Active Visual Search Interface for Medline (W Xuan et al.); Exact and Heuristic Algorithms for Weighted Cluster Editing (S Rahmann et al.); Reconcilation with Non-binary Species Trees (B Vernot et al.); and other papers. Readership: Research and application community in bioinformatics, systems biology, medicine, pharmacology and biotechnology. Graduate researchers in bioinformatics and computational biology.

Genre: Computers / Mathematical & Statistical Software (fancy, right?)