applying Findable, Accessible, Interoperable, and Reusable (FAIR) principles to the data.
applying Reproducible, Implementable, Transparent, and Explainable (RITE) principles to the data.Hongfang Liu will discuss the opportunities and challenges, including: This type of patient data is called a longitudinal patient record (LPR), and it’s a type of real-world data that can drive precision oncology forward.ĭespite recent progress using LPRs for cancer research, there are many things to consider that could improve the way researchers use this combined patient data. In this seminar, you’ll learn about the use of patient data combined from sources throughout the healthcare system. TCPA-perturbation allows the analysis of perturbed protein expression profiles in >12,000 cell line samples in response to ~170 drug compounds (Zhao et al., Cancer Cell 2020).TCPA-cell line focuses on the analysis of cell line samples and includes >1,000 CCLE samples and ~700 cell lines from the MD Anderson Cell Line project (MCLP, Li et al., Cancer Cell 2017 Ng et al., Cancer Cell 2018).TCPA-patient focuses on the analysis and visualization of patient samples (Li et al., Nature Methods 2013) and includes ~8,000 TCGA samples and independent patient cohorts.Currently, TCPA contains three independent analytic web platforms: We developed TCPA, a user-friendly web platform to analyze and visualize RPPA-based cancer functional proteomics data. This is despite proteins comprising the basic functional units in various biological processes and being major targets for many current cancer drugs. In contrast to the recent exploration of next-generation sequencing at both DNA and RNA levels, access to high-quality, large-scale proteomic data has been relatively limited in cancer research. T he Cancer Proteome Atlas (TCPA): a major bioinformatics resource for cancer proteomics data using reverse-phase protein arrays (RPPAs)
0 kommentar(er)
