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Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal.
de Bruijn I, Kundra R, Mastrogiacomo B, Tran TN, Sikina L, Mazor T, Li X, Ochoa A, Zhao G, Lai B, Abeshouse A, Baiceanu D, Ciftci E, Dogrusoz U, Dufilie A, Erkoc Z, Garcia Lara E, Fu Z, Gross B, Haynes C, Heath A, Higgins D, Jagannathan P, Kalletla K, Kumari P, Lindsay J, Lisman A, Leenknegt B, Lukasse P, Madela D, Madupuri R, van Nierop P, Plantalech O, Quach J, Resnick AC, Rodenburg SYA, Satravada BA, Schaeffer F, Sheridan R, Singh J, Sirohi R, Sumer SO, van Hagen S, Wang A, Wilson M, Zhang H, Zhu K, Rusk N, Brown S, Lavery JA, Panageas KS, Rudolph JE, LeNoue-Newton ML, Warner JL, Guo X, Hunter-Zinck H, Yu TV, Pilai S, Nichols C, Gardos SM, Philip J; AACR Project GENIE BPC Core Team, AACR Project GENIE Consortium; Kehl KL, Riely GJ, Schrag D, Lee J, Fiandalo MV, Sweeney SM, Pugh TJ, Sander C, Cerami E, Gao J, Schultz N. de Bruijn I, et al. Among authors: zhao g. Cancer Res. 2023 Dec 1;83(23):3861-3867. doi: 10.1158/0008-5472.CAN-23-0816. Cancer Res. 2023. PMID: 37668528 Free PMC article.
Automated real-world data integration improves cancer outcome prediction.
Jee J, Fong C, Pichotta K, Tran TN, Luthra A, Waters M, Fu C, Altoe M, Liu SY, Maron SB, Ahmed M, Kim S, Pirun M, Chatila WK, de Bruijn I, Pasha A, Kundra R, Gross B, Mastrogiacomo B, Aprati TJ, Liu D, Gao J, Capelletti M, Pekala K, Loudon L, Perry M, Bandlamudi C, Donoghue M, Satravada BA, Martin A, Shen R, Chen Y, Brannon AR, Chang J, Braunstein L, Li A, Safonov A, Stonestrom A, Sanchez-Vela P, Wilhelm C, Robson M, Scher H, Ladanyi M, Reis-Filho JS, Solit DB, Jones DR, Gomez D, Yu H, Chakravarty D, Yaeger R, Abida W, Park W, O'Reilly EM, Garcia-Aguilar J, Socci N, Sanchez-Vega F, Carrot-Zhang J, Stetson PD, Levine R, Rudin CM, Berger MF, Shah SP, Schrag D, Razavi P, Kehl KL, Li BT, Riely GJ, Schultz N; MSK Cancer Data Science Initiative Group. Jee J, et al. Nature. 2024 Nov 6. doi: 10.1038/s41586-024-08167-5. Online ahead of print. Nature. 2024. PMID: 39506116
The tetraploid Camellia oleifera genome provides insights into evolution, agronomic traits, and genetic architecture of oil Camellia plants.
Zhang L, Shi Y, Gong W, Zhao G, Xiao S, Lin H, Li Y, Liao Z, Zhang S, Hu G, Ye Z, Wang H, Xia Z, Yang Y, Cao H, Zhong S, Zhang X, Yuan D. Zhang L, et al. Among authors: zhao g. Cell Rep. 2024 Nov 21;43(12):115032. doi: 10.1016/j.celrep.2024.115032. Online ahead of print. Cell Rep. 2024. PMID: 39576729 No abstract available.
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