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A Cell Biologist's Guide to Modeling and Bioinformatics
By: Raquell M. HolmeseBook Publisher: John Wiley & Sons
Imprint: Wiley-Liss
Format: Adobe Encrypted (DRM)
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A step-by-step guide to using computational tools to solve problems in cell biology
Combining expert discussion with examples that can be reproduced by the reader, A Cell Biologist's Guide to Modeling and Bioinformatics introduces an array of informatics tools that are available for analyzing biological data and modeling cellular processes. You learn to fully leverage public databases and create your own computational models. All that you need is a working knowledge of algebra and cellular biology; the author provides all the other tools you need to understand the necessary statistical and mathematical methods.
Coverage is divided into two main categories: Molecular sequence database chapters are dedicated to gaining an understanding of tools and strategies—including queries, alignment methods, and statistical significance measures—needed to improve searches for sequence similarity, protein families, and putative functional domains. Discussions of sequence alignments and biological database searching focus on publicly available resources used for background research and the characterization of novel gene products. Modeling chapters take you through all the steps involved in creating a computational model for such basic research areas as cell cycle, calcium dynamics, and glycolysis. Each chapter introduces a new simulation tooland is based on published research. The combination creates a rich context for ongoing skill and knowledge development in modeling biological research systems.
Students and professional cell biologists can develop the basic skills needed to learn computational cell biology. This unique text, with its step-by-step instruction, enables you to test and develop your new bioinformatics and modeling skills. References are provided to help you take advantage of more advanced techniques, technologies, and training.
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| Title of eBook: A Cell Biologist's Guide to Modeling and Bioinformatics | |
| Release Date: 08-10-2007 | |
| Publisher: Wiley-Liss |
This eBook download is available in the following formats:
| Parent title | A Cell Biologist's Guide to Modeling... |
|---|---|
| Encrypted (DRM) | Yes |
| SKU | 9780470139349 |
| File size | 8843 |
| Security | n/a |
| Printing | Not allowed |
| Copying | Not allowed |
| Read aloud | No Sys requirements Download reader |
| Devices | Samsung Tablet, Apple Ipad & Iphone, Barnes & Noble Nook, Kobo eReader, Aluratek Libre, Iliad, Nokia, Blackberry, Hanlin |
| Note | Excellent navigation features are available via Adobe such as bookmarks and a quick access table of contents. Text search is easily accessible. An Adobe DRM-protected file is different than a pdf file in that it uses Adobe DRM (Digital Rights Management) technology, which authors and publishers use to protect their content from illegal online distribution and to set certain privileges such as restrictions on copying and printing. |
A Cell Biologist's Guide to Modeling and Bioinformatics
Chapter One
Introduction
1.1 A NEW TALE OR SAME STORY, DIFFERENT DAY?
In this day and age of informatic and 'omic efforts within biology, experimentalists are challenged to exploit information systems and computational models within their research. Computational tools that are already commonly used include image analysis software, structural modeling programs, and sequence alignment tools. Mellman and Misteli (2003) suggest that it is time for computation to become recognized as a tool on a par with molecular tools in cell biology research. At the molecular level, one rarely questions if Web-based sequence alignment and database tools should be used but rather asks if they are being used efficiently and accurately to produce trustworthy results. At the cellular level, informatics tools are helpful in identifying putative molecular components and functions. However, the dynamic behaviors of cellular systems require the development of computational models (mathematical models). Mathematical models are becoming increasingly visible in the cell biology literature, and yet the methods of creating such models are less obvious to many of us trained as experimental cell biologists.
A number of opinion pieces have been published in journals commonly read by cell biologists-Nature, Science, Journal of Cell Biology, and Cell-that engage the question of what cell biologists are to do with the now-existent parts lists generated from the Human Genome Project and ongoing genomic and proteomic work (Bray, 1997; Hartwell et al., 1999). Does having such an extensive catalogue of mol
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