Mechanistic models of cell-fate transitions from single-cell data-Reference-Cited by-同舟云学术

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Mechanistic models of cell-fate transitions from single-cell data

Published:2021-06 Issue: Volume:26 Page:79-86
ISSN:2452-3100
Container-title:Current Opinion in Systems Biology
language:en
Short-container-title:Current Opinion in Systems Biology

Author:

Torregrosa Gabriel,Garcia-Ojalvo Jordi

Funder

Ministerio de Ciencia, Innovación y Universidades

Generalitat de Catalunya

Government of Catalonia Agency for Administration of University and Research Grants

Institució Catalana de Recerca i Estudis Avançats

European Regional Development Fund

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Science Applications,Drug Discovery,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation

Reference52 articles.

1. The tension between big data and theory in the” omics” era of biomedical research;Huang;Perspect Biol Med,2018

2. The importance of computational modeling in stem cell research;del Sol;Trends Biotechnol,2021

3. Multistable and dynamic CRISPRi-based synthetic circuits;Santos-Moreno;Nat Commun,2020

4. A rationally engineered decoder of transient intracellular signals;Lormeau;Nat Commun,2021

5. Mechanistic models versus machine learning, a fight worth fighting for the biological community?;Baker;Biol Lett,2018

Cited by 11 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. Reinforcement learning guides single-cell sequencing in decoding lineage and cell fate decisions;2024-07-08

2. DELVE: feature selection for preserving biological trajectories in single-cell data;Nature Communications;2024-03-29

3. The statistical physics of single cell genomics;Molecular Physics;2023-12-28

4. Systems Biology Approaches to Understanding COVID-19 Spread in the Population;Methods in Molecular Biology;2023-12-08

5. Feature selection for preserving biological trajectories in single-cell data;2023-05-12

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