The emergence of dynamic phenotyping-Reference-Cited by-同舟云学术

The emergence of dynamic phenotyping

Published:2017-09-23 Issue:6 Volume:33 Page:507-509
ISSN:0742-2091
Container-title:Cell Biology and Toxicology
language:en
Short-container-title:Cell Biol Toxicol

Author:

Ruderman Daniel^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Cell Biology,Toxicology

Link

http://link.springer.com/article/10.1007/s10565-017-9413-x/fulltext.html

Reference26 articles.

1. Bar-or RL, Maya R, Segel LA, Alon U, Levine AJ, Oren M. Generation of oscillations by the p53-Mdm2 feedback loop: a theoretical and experimental study. 2000;2–7.

2. Bass J, Lazar MA. Circadian time signatures of fitness and disease. 2016;354(6315). https://doi.org/10.1126/science.aah4965 .

3. Behar M, Hao N, Dohlman HG, Elston TC. Mathematical and computational analysis of adaptation via feedback inhibition in signal transduction pathways. Biophys J. 2007;93(3):806–21. https://doi.org/10.1529/biophysj.107.107516 .

4. Bougen-Zhukov N, Loh SY, Lee HK, Loo L-H. Large-scale image-based screening and profiling of cellular phenotypes. Cytom Part A. 2016:1–11. https://doi.org/10.1002/cyto.a.22909 .

5. Cheng Z, Taylor B, Ourthiague DR, Hoffmann A. Distinct single-cell signaling characteristics are conferred by the MyD88 and TRIF pathways during TLR4 activation. Sci Signal. 2015;8(385):ra69-ra69. https://doi.org/10.1126/scisignal.aaa5208 .

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interpretable Fine‐Grained Phenotypes of Subcellular Dynamics via Unsupervised Deep Learning;Advanced Science;2024-09-06

2. Genome-Scale Reconstruction of Microbial Dynamic Phenotype: Successes and Challenges;Microorganisms;2021-11-14

3. Clinical trajectories estimated from bulk tumoral molecular profiles using elastic principal trees;2021 International Joint Conference on Neural Networks (IJCNN);2021-07-18

4. Emerging machine learning approaches to phenotyping cellular motility and morphodynamics;Physical Biology;2021-06-17

5. Trajectories, bifurcations, and pseudo-time in large clinical datasets: applications to myocardial infarction and diabetes data;GigaScience;2020-11