Incorporating computational resources in a cancer research program

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• 作者：Nicholas T. Woods ; Ankita Jhuraney ; Alvaro N. A. Monteiro
• 刊名：Human Genetics
• 出版年：2015
• 出版时间：May 2015
• 年：2015
• 卷：134
• 期：5
• 页码：467-478
• 全文大小：596 KB
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• 作者单位：Nicholas T. Woods (1) (2)
  Ankita Jhuraney (1) (3)
  Alvaro N. A. Monteiro (1)
  
  1. Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA
  2. Department of Oncological Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
  3. Cancer Biology Ph.D. Program, University of South Florida, Tampa, FL, USA
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Biomedicine
  Human Genetics
  Molecular Medicine
  Internal Medicine
  Metabolic Diseases
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-1203

文摘

Recent technological advances have transformed cancer genetics research. These advances have served as the basis for the generation of a number of richly annotated datasets relevant to the cancer geneticist. In addition, many of these technologies are now within reach of smaller laboratories to answer specific biological questions. Thus, one of the most pressing issues facing an experimental cancer biology research program in genetics is incorporating data from multiple sources to annotate, visualize, and analyze the system under study. Fortunately, there are several computational resources to aid in this process. However, a significant effort is required to adapt a molecular biology-based research program to take advantage of these datasets. Here, we discuss the lessons learned in our laboratory and share several recommendations to make this transition effective. This article is not meant to be a comprehensive evaluation of all the available resources, but rather highlight those that we have incorporated into our laboratory and how to choose the most appropriate ones for your research program.