ReviewInternational journal of molecular sciences2026
Mathematical and Computational Models of Biochemical Reactions and Cell Signaling-From Ordinary Differential Equations to Machine Learning.
Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
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Abstract
Cell signaling, and the biochemical reactions underlying it, are complex phenomena fundamental for control of cellular behavior in response to the incentives present in the cell's direct environment. It is crucial for coordination of cell activities such as growth, differentiation, metabolism, and death. The aim of this review is to present mathematical and computational models of biochemical reactions and cell signaling pathways in an educational and comprehensive way, outlining broad aspects of modeling such as differential equations, and artificial intelligence and machine learning approaches. This review also discusses potential applications of mathematical and computational models of cell signaling and biochemical reactions in fields such as systems biology, personalized medicine (i.e., cancer treatment, neurodegenerative disease treatment), and identification of drug targets.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.