An Integrative Approach for In Silico Glioma Research
| Autor: | Fusheng Wang, Sharath R. Cholleti, Ashish Sharma, Erwin G. Van Meir, Tony Pan, Lee Cooper, Joel H. Saltz, Carlos S. Moreno, Daniel J. Brat, Adam E. Flanders, Tom Mikkelsen, Patrick Widener, David A. Gutman, Jun Kong, Tahsin Kurc, Daniel L. Rubin |
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| Rok vydání: | 2010 |
| Předmět: |
Cell Nucleus
Databases Factual Genomic data In silico Biomedical Engineering Computational Biology Genomics Glioma Computational biology Biology medicine.disease Immunohistochemistry Article Diffuse Glioma Morphometric analysis Cancer genome Image Processing Computer-Assisted medicine Humans Computer Simulation Neuroscience Glioblastoma |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 57:2617-2621 |
| ISSN: | 0018-9294 |
| DOI: | 10.1109/tbme.2010.2060338 |
| Popis: | The integration of imaging and genomic data is critical to forming a better understanding of disease. Large public datasets, such as The Cancer Genome Atlas, present a unique opportunity to integrate these complementary data types for in silico scientific research. In this letter, we focus on the aspect of pathology image analysis and illustrate the challenges associated with analyzing and integrating large-scale image datasets with molecular characterizations. We present an example study of diffuse glioma brain tumors, where the morphometric analysis of 81 million nuclei is integrated with clinically relevant transcriptomic and genomic characterizations of glioblastoma tumors. The preliminary results demonstrate the potential of combining morphometric and molecular characterizations for in silico research. |
| Databáze: | OpenAIRE |
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