| Literature DB >> 28187516 |
R L Grossman1, B Abel2, S Angiuoli3, J C Barrett4, D Bassett5, K Bramlett6, G M Blumenthal7, A Carlsson8, R Cortese9, J DiGiovanna9, B Davis-Dusenbery9, R Dittamore10, D A Eberhard2, P Febbo2, M Fitzsimons1, Z Flamig1, J Godsey11, J Goswami12, A Gruen9, F Ortuño1, J Han2, D Hayes13, J Hicks8, D Holloway9, D Hovelson13, J Johnson4, H Juhl14, R Kalamegham15, R Kamal16, Q Kang13, G J Kelloff17, M Klozenbuecher16, A Kolatkar8, P Kuhn8, K Langone2, R Leary18, P Loverso3, H Manmathan9, A-M Martin19, J Martini20, D Miller1, M Mitchell21, T Morgan13, R Mulpuri22, T Nguyen1, G Otto23, A Pathak24, E Peters25, R Philip24, E Posadas26,27, D Reese22, M G Reese16, D Robinson18, A Dei Rossi2, H Sakul20, J Schageman6, S Singh23, H I Scher21, K Schmitt1, A Silvestro18, J Simmons3, T Simmons1, J Sislow1, A Talasaz28, P Tang1, M Tewari13, S Tomlins13, H Toukhy28, H R Tseng26,29, M Tuck13, A Tzou24, J Vinson21, Y Wang10, W Wells30, A Welsh23, J Wilbanks31, J Wolf22, L Young23, Jsh Lee17, L C Leiman32.
Abstract
The cancer community understands the value of blood profiling measurements in assessing and monitoring cancer. We describe an effort among academic, government, biotechnology, diagnostic, and pharmaceutical companies called the Blood Profiling Atlas in Cancer (BloodPAC) Project. BloodPAC will aggregate, make freely available, and harmonize for further analyses, raw datasets, relevant associated clinical data (e.g., clinical diagnosis, treatment history, and outcomes), and sample preparation and handling protocols to accelerate the development of blood profiling assays.Entities:
Mesh:
Year: 2017 PMID: 28187516 PMCID: PMC5525192 DOI: 10.1002/cpt.666
Source DB: PubMed Journal: Clin Pharmacol Ther ISSN: 0009-9236 Impact factor: 6.875
Figure 1BloodPAC Data Model.