149 related articles for article (PubMed ID: 31108201)
1. Single-cell approaches to cell competition: High-throughput imaging, machine learning and simulations.
Gradeci D; Bove A; Charras G; Lowe AR; Banerjee S
Semin Cancer Biol; 2020 Jun; 63():60-68. PubMed ID: 31108201
[TBL] [Abstract][Full Text] [Related]
2. Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.
Ozen M; Lipniacki T; Levchenko A; Emamian ES; Abdi A
Integr Biol (Camb); 2020 May; 12(5):122-138. PubMed ID: 32424393
[TBL] [Abstract][Full Text] [Related]
3. Cell competition in tumor evolution and heterogeneity: Merging past and present.
Pelham CJ; Nagane M; Madan E
Semin Cancer Biol; 2020 Jun; 63():11-18. PubMed ID: 31323289
[TBL] [Abstract][Full Text] [Related]
4. Modeling of spatially-restricted intracellular signaling.
Neves SR
Wiley Interdiscip Rev Syst Biol Med; 2012; 4(1):103-15. PubMed ID: 21766466
[TBL] [Abstract][Full Text] [Related]
5. Cell-scale biophysical determinants of cell competition in epithelia.
Gradeci D; Bove A; Vallardi G; Lowe AR; Banerjee S; Charras G
Elife; 2021 May; 10():. PubMed ID: 34014166
[TBL] [Abstract][Full Text] [Related]
6. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G
Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477
[TBL] [Abstract][Full Text] [Related]
7. From observing to predicting single-cell structure and function with high-throughput/high-content microscopy.
Chessel A; Carazo Salas RE
Essays Biochem; 2019 Jul; 63(2):197-208. PubMed ID: 31243141
[TBL] [Abstract][Full Text] [Related]
8. Solid stress, competition for space and cancer: The opposing roles of mechanical cell competition in tumour initiation and growth.
Levayer R
Semin Cancer Biol; 2020 Jun; 63():69-80. PubMed ID: 31077845
[TBL] [Abstract][Full Text] [Related]
9. Reflections on cell competition.
Baillon L; Basler K
Semin Cell Dev Biol; 2014 Aug; 32():137-44. PubMed ID: 24811317
[TBL] [Abstract][Full Text] [Related]
10. Data-Driven and Machine Learning-Based Framework for Image-Guided Single-Cell Mass Spectrometry.
Xie YR; Chari VK; Castro DC; Grant R; Rubakhin SS; Sweedler JV
J Proteome Res; 2023 Feb; 22(2):491-500. PubMed ID: 36695570
[TBL] [Abstract][Full Text] [Related]
11. Local cellular neighborhood controls proliferation in cell competition.
Bove A; Gradeci D; Fujita Y; Banerjee S; Charras G; Lowe AR
Mol Biol Cell; 2017 Nov; 28(23):3215-3228. PubMed ID: 28931601
[TBL] [Abstract][Full Text] [Related]
12. Study Quiescence Heterogeneity by Coupling Single-Cell Measurements and Computer Modeling.
Kwon JS; Wang X; Yao G
Methods Mol Biol; 2018; 1686():287-299. PubMed ID: 29030828
[TBL] [Abstract][Full Text] [Related]
13. Biologically Relevant Heterogeneity: Metrics and Practical Insights.
Gough A; Stern AM; Maier J; Lezon T; Shun TY; Chennubhotla C; Schurdak ME; Haney SA; Taylor DL
SLAS Discov; 2017 Mar; 22(3):213-237. PubMed ID: 28231035
[TBL] [Abstract][Full Text] [Related]
14. Integrated, multi-scale, spatial-temporal cell biology--A next step in the post genomic era.
Horwitz R
Methods; 2016 Mar; 96():3-5. PubMed ID: 26361333
[TBL] [Abstract][Full Text] [Related]
15. scGen predicts single-cell perturbation responses.
Lotfollahi M; Wolf FA; Theis FJ
Nat Methods; 2019 Aug; 16(8):715-721. PubMed ID: 31363220
[TBL] [Abstract][Full Text] [Related]
16. High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.
Guo B; Lei C; Kobayashi H; Ito T; Yalikun Y; Jiang Y; Tanaka Y; Ozeki Y; Goda K
Cytometry A; 2017 May; 91(5):494-502. PubMed ID: 28399328
[TBL] [Abstract][Full Text] [Related]
17. A Review of Cell-Based Computational Modeling in Cancer Biology.
Metzcar J; Wang Y; Heiland R; Macklin P
JCO Clin Cancer Inform; 2019 Feb; 3():1-13. PubMed ID: 30715927
[TBL] [Abstract][Full Text] [Related]
18. Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.
Duffy IR; Boyle AJ; Vasdev N
Mol Imaging; 2019; 18():1536012119869070. PubMed ID: 31429375
[TBL] [Abstract][Full Text] [Related]
19. Machine Learning Methods in Computational Toxicology.
Baskin II
Methods Mol Biol; 2018; 1800():119-139. PubMed ID: 29934890
[TBL] [Abstract][Full Text] [Related]
20. High content imaging for monitoring signalling dynamics in single cells.
Garner KL
J Mol Endocrinol; 2020 Nov; 65(4):R91-R100. PubMed ID: 33075744
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
