Cell Biology: Translational Impact In Cancer Biology And Bioinformatics by Maika G. MitchellCell Biology: Translational Impact In Cancer Biology And Bioinformatics by Maika G. Mitchell

Cell Biology: Translational Impact In Cancer Biology And Bioinformatics

byMaika G. MitchellEditorMaika G. Mitchell

Paperback | January 25, 2016

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Cell Biology: Translational Impact in Cancer Biology and Bioinformaticsprovides insight into the implications for cell cycle regulation and cell proliferation in cancer growth and dissemination. Offering guidance for techniques and tools to help with diagnosis, this publication provides users with a broad view of this research area, and is also useful for both early and experienced researchers across cell biology, cancer research, molecular biology, and in clinical and translational science.

  • Offers insight into how cell cycle and cell division relates to cancer biology
  • Emphasizes flow cytometry and other cell biology techniques for diagnosis
  • Includes recommendations for integration and analyzation of molecular and clinical data
The lead scientist and principle author in numerous studies involving tumor immunology, Dr. Mitchell has current teaching experience in anatomy and physiology, including recognition for contributions to research development, revenue-focused product development and management of high-tech operations. She is a contributor to the NCBI SNP...
Title:Cell Biology: Translational Impact In Cancer Biology And BioinformaticsFormat:PaperbackDimensions:350 pages, 8.75 × 6.35 × 0.68 inPublished:January 25, 2016Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0128018534

ISBN - 13:9780128018538

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Table of Contents

1. Clinical Utility / Relevance of Cell Biology Techniques
2. Applications of 3D Printing in Cell Biology
3. Transforming Bench Work Cell Biology with Cancer Informatics: From Silos to Systems
4. Overview of the Cancer Informatics Landscape
5. Current trends for Global coalition of all STEM stakeholders via Cancer Informatics
6. Conclusion & Discussion