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NPJ Breast Cancer|September 14, 2018
Correlating nuclear morphometric patterns with estrogen receptor status in breast cancer pathologic specimensRishi R Rawat, Daniel Ruderman, Paul Macklin, et al.Scientific Reports|May 1, 2020
Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E imagesRishi R Rawat, Itzel Ortega, Preeyam Roy, et al.Gigascience|April 19, 2021
High-throughput microscopy reveals the impact of multifactorial environmental perturbations on colorectal cancer cell growthChun-Te Chiang, Roy Lau, Ahmadreza Ghaffarizadeh, et al.BMC Research Notes|May 17, 2019
Monitoring dynamic cytotoxic chemotherapy response in castration-resistant prostate cancer using plasma cell-free DNA (cfDNA)Katherin Patsch, Naim Matasci, Anjana Soundararajan, et al.Scientific Reports|October 7, 2016
Single cell dynamic phenotypingKatherin Patsch, Chi-Li Chiu, Mark Engeln, et al.Scientific Reports|March 4, 2016
Intracellular kinetics of the androgen receptor shown by multimodal Image Correlation Spectroscopy (mICS)Chi-Li Chiu, Katherin Patsch, Francesco Cutrale, et al.Nature Communications|November 17, 2020
Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stainsNikhil Naik, Ali Madani, Andre Esteva, et al.BMC Systems Biology|September 23, 2016
Quantifying differences in cell line population dynamics using CellPDEdwin F Juarez, Roy Lau, Samuel H Friedman, et al.Science Translational Medicine|November 11, 2011
C-path: a Watson-like visit to the pathology labDavid L RimmMethods in Molecular Biology (Clifton, N.J.)|February 12, 2017
Designing Successful Proteomics ExperimentsDaniel RudermanPageof 52