to Bioinformatics and Java.- to Basic Local Alignment Search Tool.- Running BLAST using SwingBlast.- Facilitating PubMed Searches: JavaServer Pages and Java Servlets.- Creating a Gene Prediction and BLAST Analysis Pipeline.- cancer Biomedical Informatics Grid (caBIG(TM)).
Foreword.- Preface.- Introduction to Bioinformatics and Java.- Introduction to Basic Local Alignment Search Tool.- Running BLAST using SwingBlast.- Facilitating PubMed Searches: JavaServers Pages and Java Servlets.- Creating a Gene Prediction and BLAST Analysis Pipeline.- cancer Biomedical Informatics Grid (caBIG(TM)).- Appendix.-Additional Resources.
Medical science and practice have undergone fundamental changes in the last 5 years, as large-scale genome projects have resulted in the sequencing of a number of important microbial, plant and animal genomes. This book aims to combine industry standard software engineering and design principles with genomics, bioinformatics and cancer research. Rather than an exercise in learning a programming platform, the text focuses on useful analytical tools for the scientific community.
This book examines the tools being developed to meet the goal of eliminating suffering and death from cancer by 2015. It focuses on creating and integrating practical, useful tools for the scientific community in the context of real-life, real-value biomedical problems. From a software perspective, a functional approach is used to teach the Java platform and its features for enterprise-level application development. Under this approach, the various syntactical and operative elements of the language are taught in the context of definable research problems that enable the user to relate how the different parts of the language fit together. The book illustrates how individual bioinformatics applications can be stitched together into a pipeline so that users can direct the output of one tool to perform further analysis. All examples are derived from practical problems faced in biomedical/clinical data retrieval and analysis during routine bioinformatics and cancer research.