寻找问题

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2024-10-17 DOI:10.1016/j.cell.2024.09.017
Mu-ming Poo
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引用次数: 0

摘要

我早年接受过物理学训练,在我的职业生涯中,我不断学习和探索生物学中有趣的问题。在此,我将讲述影响我选择研究课题的一些重要事件。研究课题的多样性可归因于我自己缺乏特定的研究重点,以及碰巧加入我实验室的学生和博士后的兴趣。我的科研和教育经历使我广泛参与了中国神经科学和非人灵长类动物的各种研究。
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In search of problems
With early training in physics, my career was marked by continuous learning and searching for interesting problems in biology. Here, I recount some key events that influenced my choices of research topics. The diversity of topics could be attributed to my own lack of a particular focus and the interests of students and postdocs who happened to join my laboratory. My scientific and educational ventures led to my extensive involvement in Chinese neuroscience and various studies in non-human primates.
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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Bayesian Approach for Computing Free Energy on Perturbation Graphs with Cycles. Deterministic and Faster GW Calculations with a Reduced Number of Valence States: O(N2 ln N) Scaling in the Plane-Waves Formalism. The Dynamic Diversity and Invariance of Ab Initio Water. Automatic Feature Selection for Atom-Centered Neural Network Potentials Using a Gradient Boosting Decision Algorithm. Data Quality in the Fitting of Approximate Models: A Computational Chemistry Perspective.
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