课题基金 / 基金详情

项目摘要

项目成果

Timothy C Elston的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
DESCRIPTION (provided by applicant): Cells are extraordinarily adept at detecting and tracking shallow gradients of chemicals of interest. Micro-organisms track gradients to find food or mates, and similar processes underlie axon guidance in the nervous system, homing of immune cells towards invaders, crawling of repair cells towards wound sites, and guidance of sperm towards the egg during conception. Gradient tracking also contributes to metastasis in cancer, so understanding how cells track shallow chemical gradients is of medical relevance as well as fundamental interest. Upon detecting chemicals through cell-surface receptors, cells either move or grow towards the source of the signal. In many cases, the gradients of diffusible substances are shallow, resulting in minuscule concentration differences across the diameter of small cells. Gradient detection is made even more difficult by the randomness of individual receptor-ligand interactions, which leads to molecular noise that can mask the tiny spatial gradient signal. The mechanisms that allow cells to efficiently track even very shallow gradients despite noise are poorly understood. In this proposal, we use the uniquely tractable yeast model system to investigate these mechanisms. During mating, yeast cells polarize and grow up a gradient of pheromone to find and fuse with opposite-sex partners. We propose to use a combination of cutting-edge microscopy, genetics, and computational modeling to understand how it is that yeast cells track pheromone gradients.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Predoctoral Training Program in Bioinformatics and Computational Biology
Predoctoral Training Program in Bioinformatics and Computational Biology
Predoctoral Training Program in Bioinformatics and Computational Biology
Predictive Modeling of the EGFR-MAPK pathway for Triple Negative Breast Cancer Patients
海外基金