Amanote Research

Amanote Research

    RegisterSign In

Power-Law Modeling of Cancer Cell Fates Driven by Signaling Data to Reveal Drug Effects

PLoS ONE - United States
doi 10.1371/journal.pone.0165049
Full Text
Open PDF
Abstract

Available in full text

Categories
Multidisciplinary
Date

October 20, 2016

Authors
Fan ZhangMin WuChee Keong KwohJie Zheng
Publisher

Public Library of Science (PLoS)


Related search

Data-Driven Prediction of Adverse Drug Reactions Induced by Drug-Drug Interactions

BMC pharmacology & toxicology
MedicinePharmacology
2017English

Data-Driven Models Reveal Mutant Cell Behaviors Important for Myxobacterial Aggregation

2020English

Data-Driven Modeling and Application in Operation Optimization of Coal-Fired Power Generation

DEStech Transactions on Engineering and Technology Research
2017English

Data-Driven 3D Shape Modeling

English

Modeling Cell Signaling Networks

Biology of the Cell
MedicineCell Biology
2004English

NASA Satellite Data, Modeling Reveal Global Decline of Phytoplankton

Microbe
Microbiology
2016English

Contact Line Instability of Gravity-Driven Flow of Power-Law Fluids

Journal of Non-Newtonian Fluid Mechanics
Materials ScienceApplied MathematicsChemical EngineeringMechanical EngineeringCondensed Matter Physics
2015English

Demystifying Blood Stem Cell Fates

Nature Cell Biology
Cell Biology
2017English

An Integrated Data Driven Approach to Drug Repositioning Using Gene-Disease Associations

PLoS ONE
Multidisciplinary
2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy