Development of a computational model of synaptome architecture.
Development of a computational model of synaptome architecture.
批准号:
BB/X009343/1
负责人:
James Armstrong
金额:
$53.52万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
The brain is the most complex organ in biology and its complexity comes from its many layers of organisation Regions within the brain are specialised to serve different functions (e.g some regions handle vision while other underpin cognition and learning and others motor control). Each of these regions comprises neurons which connect to one another forming neuronal networks or circuits. At yet another level each of these neurons connects to its partners using highly specialised and complex molecular complexes known as synapses. The components of these synapses are highly dynamic through the lifespan and are region specific. However, our understanding of how brains work at this chemical level and how these age and region specific changes impact on brain function is very poorly understood. The long term impact of this understanding is vitally important to society as a whole. We need to understand these changes so we can develop new methods to treat the brain when it deteriorates with age, with disease or in response to trauma. Our project will develop new ways to bring together the information about these chemical synapses to give us a new understanding of this critical level. The data to start addressing these fundamental questions exists in part but is widely scattered and the methods for integrating these data together are in their infancy. This research will address both issues seeking to release a computational model of how these synapses can be predicted from the data available. We will release a public database for other researchers in academia and in the pharmaceutical industry so impact of what we do can be maximised. We will also validate our work by testing a selection of our predictions in the aging brain to confirm how well our computational models and algorithms perform.While our project is based on understanding the fundamental principles it is also of critical importance in terms of long-term health: These chemical synapses are the site at which drugs act but our understanding of how they vary need to be improved to unlock a new generation of drugs can be targeted to keep the brain healthy.
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