Title |
Novel alternative splicing isoform biomarkers identification from high-throughput plasma proteomics profiling of breast cancer
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Published in |
BMC Systems Biology, December 2013
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DOI | 10.1186/1752-0509-7-s5-s8 |
Pubmed ID | |
Authors |
Fan Zhang, Mu Wang, Tran Michael, Renee Drabier |
Abstract |
In the biopharmaceutical industry, biomarkers define molecular taxonomies of patients and diseases and serve as surrogate endpoints in early-phase drug trials. Molecular biomarkers can be much more sensitive than traditional lab tests. Discriminating disease biomarkers by traditional method such as DNA microarray has proved challenging. Alternative splicing isoform represents a new class of diagnostic biomarkers. Recent scientific evidence is demonstrating that the differentiation and quantification of individual alternative splicing isoforms could improve insights into disease diagnosis and management. Identifying and characterizing alternative splicing isoforms are essential to the study of molecular mechanisms and early detection of complex diseases such as breast cancer. However, there are limitations with traditional methods used for alternative splicing isoform determination such as transcriptome-level, low level of coverage and poor focus on alternative splicing. |
X Demographics
Geographical breakdown
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Denmark | 1 | 3% |
Unknown | 35 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 13 | 36% |
Researcher | 7 | 19% |
Student > Master | 5 | 14% |
Student > Postgraduate | 2 | 6% |
Student > Bachelor | 2 | 6% |
Other | 4 | 11% |
Unknown | 3 | 8% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 13 | 36% |
Biochemistry, Genetics and Molecular Biology | 8 | 22% |
Computer Science | 6 | 17% |
Medicine and Dentistry | 2 | 6% |
Immunology and Microbiology | 1 | 3% |
Other | 2 | 6% |
Unknown | 4 | 11% |