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coderdata/dataset.yml

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- drug
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- drug descriptor
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- experiments
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figshare: https://api.figshare.com/v2/articles/28823159
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version: 2.1.0
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datasets:
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beataml:
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description: Beat acute myeloid leukemia (BeatAML) focuses on acute myeloid leukemia tumor data. Data includes drug response, proteomics, and transcriptomics datasets.
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references:
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- citation: Bottomly D, Long N, Schultz AR, et al. Integrative analysis of drug response and clinical outcome in acute myeloid leukemia. Cancer Cell. 2022;40(8):850-864.e9.
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doi: https://doi.org/10.1016/j.ccell.2022.07.002
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- citation: Pino JC, Posso C, Joshi SK, et al. Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia. Cell Rep Med. 2024;5(1):101359.
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doi: https://doi.org/10.1016/j.xcrm.2023.101359
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modalities:
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- sample
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- transcriptomics
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- mutations
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- proteomics
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- drug
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- drug descriptor
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- experiments
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bladderpdo:
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description: Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer. Data includes transcriptomics, mutations, copy number, and drug response data.
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references:
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- citation: Suk Hyung Lee, Wenhuo Hu, Justin T. Matulay, et al. Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer. Cell. 2018;173(2):515-528.e17.
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doi: https://doi.org/10.1016/j.cell.2018.03.017
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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ccle:
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description: Cancer Cell Line Encyclopedia (CCLE).
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references:
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- citation: Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483(7391):603-607.
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doi: https://doi.org/10.1038/nature11003
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modalities:
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- sample
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- transcriptomics
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- proteomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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cptac:
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description: The Clinical Proteomic Tumor Analysis Consortium (CPTAC) project. Simplified and Unified Access to Cancer Proteogenomic Data.
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references:
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- citation: Lindgren CM, Adams DW, Kimball B, et al. Simplified and Unified Access to Cancer Proteogenomic Data. J Proteome Res. 2021;20(4):1902-1910.
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doi: https://doi.org/10.1021/acs.jproteome.0c00919
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modalities:
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- sample
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- transcriptomics
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- proteomics
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- mutations
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- copy number
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ctrpv2:
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description: Cancer Therapeutics Response Portal version 2 (CTRPv2)
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references:
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- citation: Rees MG, Seashore-Ludlow B, Cheah JH, et al. Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nat Chem Biol. 2016;12(2):109-116.
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doi: https://doi.org/10.1038/nchembio.1986
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- citation: Seashore-Ludlow B, Rees MG, Cheah JH, et al. Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset. Cancer Discov. 2015;5(11):1210-1223.
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doi: https://doi.org/10.1158/2159-8290.CD-15-0235
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- citation: Basu A, Bodycombe NE, Cheah JH, et al. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules. Cell. 2013;154(5):1151-1161.
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doi: https://doi.org/10.1016/j.cell.2013.08.003
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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fimm:
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description: Institute for Molecular Medicine Finland (FIMM) dataset.
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references:
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- citation: Mpindi JP, Yadav B, Östling P, et al. Consistency in drug response profiling. Nature. 2016;540(7631):E5-E6.
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doi: https://doi.org/10.1038/nature20171
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- citation: Pemovska T, Kontro M, Yadav B, et al. Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia. Cancer Discov. 2013;3(12):1416-1429.
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doi: https://doi.org/10.1158/2159-8290.CD-13-0350
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modalities:
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- sample
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- transcriptomics
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- drug
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- drug descriptor
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- experiments
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hcmi:
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description: Human Cancer Models Initiative (HCMI) encompasses numerous cancer types and includes cell line, organoid, and tumor data. Data includes transcriptomics, somatic mutation, and copy number datasets.
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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mpnst:
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description: Malignant Peripheral Nerve Sheath Tumor is a rare, aggressive sarcoma that affects peripheral nerves throughout the body.
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references:
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- citation: Dehner C, Moon CI, Zhang X, et al. Chromosome 8 gain is associated with high-grade transformation in MPNST. JCI Insight. 2021;6(6):e146351.
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doi: https://doi.org/10.1172/jci.insight.146351
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modalities:
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- sample
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- transcriptomics
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- proteomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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mpnstpdx:
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description: Patient derived xenograft data for MPNST
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modalities:
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- sample
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- transcriptomics
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- drug
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- drug descriptor
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- experiments
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nci60:
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description: National Cancer Institute 60
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references:
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- citation: Shoemaker RH. The NCI60 human tumour cell line anticancer drug screen. Nat Rev Cancer. 2006;6(10):813-823.
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doi: https://doi.org/10.1038/nrc1951
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modalities:
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- sample
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- transcriptomics
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- mutations
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- proteomics
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- drug
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- drug descriptor
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- experiments
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pancpdo:
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description: Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer. Data includes transcriptomics, mutations, copy number, and drug response data.
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references:
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- citation: Tiriac H, Belleau P, Engle DD, et al. Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer. Cancer Discov. 2018;8(9):1112-1129.
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doi: https://doi.org/10.1158/2159-8290.CD-18-0349
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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prism:
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description: Profiling Relative Inhibition Simultaneously in Mixtures
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references:
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- citation: Corsello SM, Nagari RT, Spangler RD, et al. Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling. Nat Cancer. 2020;1(2):235-248.
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doi: https://doi.org/10.1038/s43018-019-0018-6
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- citation: Yu C, Mannan AM, Yvone GM, et al. High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines. Nat Biotechnol. 2016;34(4):419-423.
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doi: https://doi.org/10.1038/nbt.3460
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modalities:
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- sample
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- transcriptomics
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- drug
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- drug descriptor
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- experiments
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sarcpdo:
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description: The landscape of drug sensitivity and resistance in sarcoma. Data includes transcriptomics, mutations, and drug response data.
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references:
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- citation: Al Shihabi A, Tebon PJ, Nguyen HTL, et al. The landscape of drug sensitivity and resistance in sarcoma. Cell Stem Cell. 2024;31(10):1524-1542.e4.
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doi: https://doi.org/10.1016/j.stem.2024.08.010
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modalities:
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- sample
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- transcriptomics
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- mutations
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- drug
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- drug descriptor
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- experiments
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crcpdo:
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description: Prospective derivation of a living organoid biobank of colorectal cancer patients.
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references:
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- citation: van de Wetering M, Francies HE, Francis JM, et al. Cell. 2015;161(4):933–945.
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doi: https://doi.org/10.1016/j.cell.2015.03.053
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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liverpdo:
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description: Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology.
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references:
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- citation: Ji S, Feng L, Fu Z, et al. Science Transl Med. 2023;15(706):eadg3358.
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doi: https://doi.org/10.1126/scitranslmed.adg3358
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments
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novartispdx:
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description: High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.
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references:
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- citation: Gao H, Korn JM, Ferretti S, et al. Nat Med. 2015;21(11):1318-1325.
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doi: https://doi.org/10.1038/nm.3954
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modalities:
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- sample
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- transcriptomics
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- mutations
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- copy number
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- drug
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- drug descriptor
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- experiments

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