Bioinformatics and Systems Biology: Collaborative Research and Resources

Springer Science & Business Media, 22.07.2008 - 287 Seiten
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Collaborative research in bioinformatics and systems biology is a key element of modern biology and health research. This book highlights and provides access to many of the methods, environments, results and resources involved, including integral laboratory data generation and experimentation and clinical activities. Collaborative projects embody a research paradigm that connects many of the top scientists, institutions, their resources and research worldwide, resulting in first-class contributions to bioinformatics and systems biology. Central themes include describing processes and results in collaborative research projects using computational biology and providing a guide for researchers to access them.

The book is also a practical guide on how science is managed. It shows how collaborative researchers are putting results together in a way accessible to the entire biomedical community.


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Chapter 1 Introduction
Part I Fundamental Collaborative Research and Computational Biology
Part II Resources Supporting Bioinformatics and Systems Biology Research
Part III DiseaseRelated Collaborative Research and Computational Biology
Part IV Science Management Perspectives and Conclusions

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Beliebte Passagen

Seite 6 - Consortium to produce a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing.
Seite 10 - [successful physiological analysis requires an understanding of the functional interactions between the key components of cells, organs, and systems, as well as how these interactions change in disease states. This information resides neither in the genome nor even in the individual proteins that genes code for. It lies at the level of protein interactions within the context of subcellular, cellular, tissue, organ, and system structures.
Seite 14 - Bock et al. (2002), who describe the dimensions covered by systems biology research and its anticipated development, eg the integrative analysis of physiological function. Using the computational models of the heart as examples, they discuss three types of integration: structural integration, functional integration and synthesis.

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