Titlebook: Bioinformatics Research and Applications; 19th International S Xuan Guo,Serghei Mangul,Alexander Zelikovsky Conference proceedings 2023 The

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978-981-99-7073-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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https://doi.org/10.1007/978-3-658-14057-1 behavior of the virus. This research aims to facilitate the design of efficient vaccinations and proactive measures to prevent future pandemics through the utilization of machine learning (ML) models for decision-making processes. Consequently, ensuring the reliability of ML predictions in these cr

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https://doi.org/10.1007/978-3-322-81111-0e classification. However, these methods face two primary challenges:(i) the computational complexity associated with kernel computation, which involves an exponential time requirement for dot product calculation, and (ii) the scalability issue of storing the large . matrix in memory when the number

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Fünf Kriterien der Rationalit?ttems biology, and drug discovery. However, no such database can be complete, and the chemical structure for a given compound is not necessarily consistent between databases. This paper presents ., a novel tool for resolving unique and correct molecular structures from database identifiers. . travers

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Fünf Kriterien der Rationalit?t-mediated chromatin loop prediction is important to understand diverse types of biological processes which may lead to the development of new therapeutics for neurological disorders and cancers. Existing deep learning predictors are capable to predict YY1-mediated chromatin loops in two different ce

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