Table 1 List of abbreviations and their full names used in the article

From: A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

Abbreviation

Full Name

ABMs

Agent-based models

ANN

Artificial neural network

APC

Antigen-presenting cell

BrCa

Breast cancer

CDKs

Cyclin-dependent kinases

CFSE

Carboxyfluorescein succinimidyl ester

CKIs

Cyclin-dependent kinase inhibitors

DCIS

Ductal carcinoma in situ

DDR

DNA damage response

DRL

Deep reinforcement learning

DSBs

Double-strand breaks

ECM

Extracellular matrix

EMT

Epithelial-mesenchymal transition

FUCCI

Fluorescent ubiquitination-based cell cycle indicator

HSC

Hematopoietic stem cell

LET

Linear energy transfer

mAbs

Monoclonal antibodies

MAPK

Mitogen-activated protein kinase

MCMC

Markov chain Monte Carlo

MIDD

Model-informed drug development

ML

Machine learning

MSMs

Multi-stage models

MTD

Maximum tolerated dose

NSCLC

Non-small cell lung cancer

OCT

Optical coherence tomography

ODEs

Ordinary differential equations

OvCa

Ovarian cancer

PaCa

Pancreatic cancer

PDEs

Partial differential equations

PPI

Protein-protein interaction

PSPMs

Physiologically structured population models

QSP

Quantitative systems pharmacology

RBF

Radial basis function

RD

Reaction-diffusion

RMSE

Root mean square error

RPIM

Radial point interpolation method

SDEs

Stochastic differential equations

SMI

Small-molecule inhibitor

SPN

Stochastic Petri net

spQSP

Spatial quantitative systems pharmacology

SSA

Stochastic simulation algorithm

SVM

Support vector machine

TGI

Tumor growth inhibition

TME

Tumor microenvironment

VEGF

Vascular endothelial growth factor

VP

Virtual patient

WCMs

Whole-cell models