Title |
Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential
|
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Published in |
BMC Systems Biology, September 2015
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DOI | 10.1186/s12918-015-0211-x |
Pubmed ID | |
Authors |
Claudia Cava, Gloria Bertoli, Isabella Castiglioni |
Abstract |
Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics. These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses. This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 33% |
Belgium | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 1 | 1% |
Norway | 1 | 1% |
Unknown | 96 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 22 | 22% |
Student > Master | 19 | 19% |
Student > Ph. D. Student | 12 | 12% |
Student > Bachelor | 11 | 11% |
Other | 6 | 6% |
Other | 15 | 15% |
Unknown | 13 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 29 | 30% |
Agricultural and Biological Sciences | 20 | 20% |
Medicine and Dentistry | 12 | 12% |
Computer Science | 4 | 4% |
Psychology | 3 | 3% |
Other | 14 | 14% |
Unknown | 16 | 16% |