单细胞迁移的现代建模:从膜张力和流原性到机器学习。

IF 6.9 2区 生物学 Q1 CELL BIOLOGY
Wenzheng Shi, Alex Mogilner
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引用次数: 0

摘要

细胞迁移现象几十年来一直受到计算建模的启发和受益。在这里,我们回顾了传统的自下而上模型在细胞迁移的三个方面的最新应用:膜张力(MT)在组织细胞定向运动中的作用,电场(EF)作为迁移的定向线索的作用,以及三维迁移的机制。然后,我们讨论了机器学习(ML)在细胞迁移和电流趋向性方面的新兴应用。我们关注单细胞的迁移机制,并强调理论与实验之间的反馈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modern Modeling of Single-Cell Migration: From Membrane Tension and Galvanotaxis to Machine Learning.

Cell migration phenomenon has inspired and benefited from computational modeling for decades. Here, we review recent applications of traditional bottom-up modeling to three aspects of cell migration: the role of membrane tension (MT) in organizing directional cell motility, the role of the electric field (EF) as the directional cue for migration, and the mechanics of three-dimensional migration. We then discuss nascent applications of machine learning (ML) to cell migration and galvanotaxis. We focus on the migratory mechanisms of the single cell and highlight the feedback between theory and experiment.

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来源期刊
CiteScore
15.00
自引率
1.40%
发文量
56
审稿时长
3-8 weeks
期刊介绍: Cold Spring Harbor Perspectives in Biology offers a comprehensive platform in the molecular life sciences, featuring reviews that span molecular, cell, and developmental biology, genetics, neuroscience, immunology, cancer biology, and molecular pathology. This online publication provides in-depth insights into various topics, making it a valuable resource for those engaged in diverse aspects of biological research.
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