Reprint
Recent Developments in Cancer Systems Biology
Edited by
August 2021
272 pages
- ISBN978-3-0365-1472-7 (Hardback)
- ISBN978-3-0365-1471-0 (PDF)
This book is a reprint of the Special Issue Recent Developments in Cancer Systems Biology that was published in
Medicine & Pharmacology
Public Health & Healthcare
Summary
This ebook includes original research articles and reviews to update readers on the state of the art systems approach to not only discover novel diagnostic and prognostic biomarkers for several cancer types, but also evaluate methodologies to map out important genomic signatures. In addition, therapeutic targets and drug repurposing have been emphasized for a variety of cancer types. In particular, new and established researchers who desire to learn about cancer systems biology and why it is possibly the leading front to a personalized medicine approach will enjoy reading this book.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
Sestrin2; lung cancer; knockdown; cancer progression; bioinformatics; patient survival; lung adenocarcinoma; circulating miR-1246; glycosaminoglycan binding; prognosis; PI3K–Akt signaling pathways; TargetScan; UBE2C; cancer systems biology; experimental model systems; next-generation sequencing; single-cell sequencing; patient-derived xenografts; patient-derived organoids; triple-negative breast cancer; personalized medicine; computational methods; drug repurposing; clinical trials; cancer stem cells; ETS; Elk-1; stem cell; microarray; brain-tumor-initiating cell (BTIC); pancreatic cancer; systems biology; omics; biomarker; genomics; transcriptomics; proteomics; metabolomics; glycomics; metagenomics; personalized medicine; Ets; Elk-1; PEA3; Ets-1; glioma; biomarker; optical genome mapping; solid tumors; cancer genomics; genomics; proteomics; breast; ovarian; cancer; TCGA; non-small-cell lung cancer; lung adenocarcinoma (LUAD); lung squamous cell carcinoma (LUSC); differential expression; SNV; CNV; risk group; signature; survival; renal cancers; protein interactome; diagnostic biomarker; prognostic biomarker; virtual screening; docking; acute myeloid leukemia; Boolean model; drug resistance; network; n/a