Computational chemistry
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article