纯数学在解决复杂生物学问题中的作用：f1 - atp酶的应用、成就和未来方向。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems Pub Date : 2025-08-26 DOI:10.1016/j.biosystems.2025.105575

Hirdesh Rohatgi

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引用次数: 0

摘要

数学应该是生物学研究的核心组成部分，而不仅仅是解决复杂问题的辅助工具。将纯数学整合到生物学研究中，为解决复杂的分子水平问题提供了一条强有力的途径，这些问题的完全阐明已被证明是传统的实验、理论和计算方法所无法单独解决的。本文探讨了数学在Nath的f1 - atp酶研究中的应用，如组合学、数论、图论，并强调了其在阐明分子机制、模拟生物系统、预测复杂行为、验证模型和提供明确结论方面的能力。我们量化了有缺陷研究的经济损失，并提出了一个数学框架来推进生物学发现，将数学定位为解决生物学问题的变革力量。

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The role of pure mathematics in resolving complex biological problems: Applications to F1-ATPase, achievements, and future directions

Mathematics should be a core component of biological research, not merely an auxiliary tool, to address intricate problems. Integration of pure mathematics into biological research offers a powerful avenue to address complex molecular-level problems whose complete elucidation has proven resistant to traditional experimental, theoretical, and computational approaches alone. This paper explores the application of mathematics in Nath's work on F₁-ATPase, such as combinatorics, number theory, graph theory, and highlights its ability to elucidate molecular mechanisms, model biological systems, predict complex behaviors, validate models, and provide definitive conclusions. We quantify the economic toll of flawed research, and propose a mathematical framework to advance biological discovery, positioning mathematics as a transformative force to solve biological problems.

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来源期刊

Biosystems 生物-生物学

CiteScore

3.70

自引率

18.80%

发文量

129

审稿时长

34 days

期刊介绍： BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.