TACSY: Training Alliance for Computational Systems Chemistry
TACSY: Training Alliance for Computational Systems Chemistry
批准号:
EP/X025837/1
负责人:
Annette Taylor
金额:
$33.8万
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
Many important questions and grand challenges in research, industry, and society involve large and complex networks of chemical reactions. Some examples are: studying metabolic networks in humans; planning and optimizing chemical synthesis in industry and research labs; modeling the fragmentation process in mass spectrometry; developing personalized medicine; probing hypotheses of the origins of life; monitoring environmental pollution in air, water, and soil. In project TACsy, we will develop ground-breaking new computational methods for analyzing such networks of chemical reactions and we will train a new generation of excellent and innovative early stage researchers (ESRs) capable of evolving and applying these methods in research and industry. Combined, these efforts carry very strong potential for impact on the grand challenges mentioned above, on the EU commission priority on jobs, growth, investment, and competitiveness, and on the well-being of EU citizens. The research methodology of TACsy arises from the novel application of formalisms, algorithms, and computational methods from computer science to questions in systems chemistry. The first steps demonstrating the strong capabilities of this approach have recently been made. In TACsy, the ESRs will vastly expand these methods and their formal foundations, they will create efficient algorithms and implementations of them, and they will use these implementations for research in complex chemical systems in three flagship application areas. TACsy is a consortium of world-class, experienced scientists which will ensure excellent research training conditions for the ESRs in this highly interdisciplinary field. Through a carefully designed training programme and secondments at leading industry partners, the ESR will acquire a broad career perspective and a strong set of transferable skills. Their unique blend of competences from computer science and chemistry will further increase their high employment.
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会议论文
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批准号:EP/K030574/1
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项目类别:Research Grant
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资助金额:$36.66万
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财政年份:2014
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负责人:Annette Taylor
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依托单位:
Kinetic Switches: Exploiting Feedback in Enzyme Microparticles
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批准号:EP/K030574/2
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项目类别:Research Grant
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资助金额:$28.81万
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财政年份:2014
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负责人:Annette Taylor
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依托单位:
Chemistry in Flow: Amplification versus Extinction
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批准号:EP/F048777/1
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项目类别:Research Grant
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资助金额:$12.85万
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财政年份:2009
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负责人:Annette Taylor
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依托单位:
海外基金