Integrated proteogenomic analysis of laser capture microdissected breast tumors (AACR 2017 Annual Meeting)

To investigate the proteogenomic landscape of breast cancer subtypes by integrating comprehensive transcriptomic, proteomic, and phosphoproteomic data, in a cohort with a substantial representation of African Americans, with a secondary objective of identifying druggable proteins that are differenti...

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Hauptverfasser:	Omics, PNNL, Sridhara, Viswanadham, Liu, Tao, Gritsenko, Marina A., Sturtz, Lori A., Kovatich, Albert J., Petyuk, Vladislav A., Deyarmin, Brenda, McDermott, Jason E., Shukla, Anil K., Moore, Ronald J., Monroe, Matthew E., Webb-Robertson, Bobbie-Jo M., Hooke, Jeffrey A., Fantacone-Campbell, Leigh, Kumar Raj Kumar, Praveen, Kvecher, Leonid, Liu, Jianfang, Kane, Jennifer, Melley, Jennifer, Somiari, Stella, Iida, Joji, Benz, Stephen C., Golovato, Justin, Rabizadeh, Shahrooz, Soon-Shiong, Patrick, Smith, Richard D., J. Mural, Richard, D. Shriver, Craig, Hu, Hai, Rodland, Karin D.
Format:	Bild
Sprache:	eng
Schlagworte:	Agricultural biotechnology not elsewhere classified Bioinformatic methods development Bioinformatics and computational biology not elsewhere classified Medical biotechnology not elsewhere classified Oncology and carcinogenesis not elsewhere classified Other biological sciences not elsewhere classified
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Beschreibung
Zusammenfassung:	To investigate the proteogenomic landscape of breast cancer subtypes by integrating comprehensive transcriptomic, proteomic, and phosphoproteomic data, in a cohort with a substantial representation of African Americans, with a secondary objective of identifying druggable proteins that are differentially expressed in specific subtypes.
DOI:	10.6084/m9.figshare.5153884