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Supreet Agarwal
PeerJ Editor & Reviewer
465 Points

Contributions by role

Reviewer 30
Editor 435

Contributions by subject area

Bioinformatics
Cell Biology
Genomics
Molecular Biology
Gastroenterology and Hepatology
Oncology
Urology
Andrology
Surgery and Surgical Specialties
Data Mining and Machine Learning
Biochemistry
Hematology

Supreet Agarwal

PeerJ Editor & Reviewer

Summary

I am a cancer biologist with 13+ years of experience and diverse background in clinical pharmaceutical sciences, cancer stem cells, cancer therapeutics, and data analytics. My research has focused on using innovative 3D organoid models for the understanding of cancer cell signaling pathways to facilitate cancer biomarker discovery and drug discovery for metastatic castrate resistant prostate cancer. I have successfully completed multiple preclinical trials of which two drugs are currently in clinical trials. Some of the methodologies I have gained expertise in include high-throughput drug screening, preclinical trials, flow cytometry, confocal microscopy, CRISPR screens, patient-derived xenografts, 3D organoid cultures, bioinformatics tools, and statistical analysis.

Bioinformatics Cell Biology Oncology Urology

Editing Journals

PeerJ - the Journal of Life & Environmental Sciences

Work details

Scientist

National Cancer Institute
Laboratory of Genitourinary Cancer Pathogenesis

Websites

  • Google Scholar

PeerJ Contributions

  • Edited 3

Academic Editor on

May 19, 2022
Association of multiple tumor markers with newly diagnosed gastric cancer patients: a retrospective study
Xiaoyang Li, Sifeng Li, Zhenqi Zhang, Dandan Huang
https://doi.org/10.7717/peerj.13488 PubMed 35611170
January 25, 2022
Identification and validation of a novel signature for prediction the prognosis and immunotherapy benefit in bladder cancer
Yichi Zhang, Yifeng Lin, Daojun Lv, Xiangkun Wu, Wenjie Li, Xueqing Wang, Dongmei Jiang
https://doi.org/10.7717/peerj.12843 PubMed 35127296
December 20, 2021
A novel machine learning derived RNA-binding protein gene–based score system predicts prognosis of hepatocellular carcinoma patients
Qiangnu Zhang, Yusen Zhang, Yusheng Guo, Honggui Tang, Mingyue Li, Liping Liu
https://doi.org/10.7717/peerj.12572 PubMed 35036125