“…Glioblastoma is a complex disease that is difficult to treat. Network and data science offer alternative approaches to classical bioinformatics pipelines to study gene expression patterns from single-cell datasets, helping to distinguish genes associated with the control of differentiation and aggression. …”
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“…A crucial question in data science is to extract meaningful information embedded in high-dimensional data into a low-dimensional set of features that can represent the original data at different levels. …”
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“…This article contributes new perspectives in this underexplored direction at the intersection of data science, AI, citizen science, and human-computer interaction. …”
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“…Thus, PORT enables a host of potential applications of social data science to hitherto unobtainable data.…”
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“…Here, we make use of machine learning and data science to characterize tip–sample forces purely from experimental data with sub-microsecond resolution. …”
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“…We present a framework, case studies, best practices, and tools for applying participative data science to healthcare, enabling data scientists, clinicians, and patients to work together. …”
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“…The propounded model has a bathtub and J-shapes hazard rate characteristics in data science. Thus, it has enhanced data analysis because of its productivity. …”
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“…Obtaining a standardized benchmark of computational methods is a major issue in data-science communities. Dedicated frameworks enabling fair benchmarking in a unified environment are yet to be developed. …”
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“…This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics. Data Science > Chemoinformatics.…”
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“…Ultimately, DenseNet regression is applied to predict relative humidity, and the outcome shows a high correlation with observations, which indicates that our model could advance environmental data science.…”
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“…Recent advances in remote sensing and data science can provide a wide range of possibilities to account for and reduce the predictive uncertainties; hence improving the predictability of CF events, enabling risk-informed decision-making, and ensuring a sustainable CF risk governance.…”
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“…The dataset is comprehensive and organised according to the Brain Imaging Data Structure (BIDS) specification, providing a valuable starting point for both aspiring and experienced researchers in a range of fields, including cognitive neuroscience, data science, machine learning, and clinical neurophysiology.…”
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“…By employing an intuitive and user-friendly graphical user interface, beeRapp empowers behavioral scientists without programming and data science expertise to perform clustering, dimensionality reduction, correlational and inferential statistics and produce up to thousands of high-quality output plots visualizing results in a standardized and automated way. …”
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“…Ligand parametrization and AI based data science can potentially help predict the facile formation of L(1)Pd(0) species.…”
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“…This talk highlights the importance of moving beyond post-hoc subgroup analysis to an approach that integrates theories, observational and experimental data, and data science in the study of HTEs.…”
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“…Finally, we call on atomists and holists within the ever-expanding data science community to exhibit greater empathy during ethical disagreements and propose four targeted strategies to ensure AI research benefits society.…”
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“…After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of Machine Learning (AI) which holds much promise for this domain.…”
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“…Peter Mueller is Professor in the Department of Mathematics and the Department of Statistics & Data Science at the University of Texas at Austin. He has published widely on nonparametric Bayesian statistics, with an emphasis on applications in biostatistics and bioinformatics.…”
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“…Along with many deep theoretical results, these volumes contain numerous applications to problems in signal processing, medical imaging, geodesy, statistics, and data science. The chapters within cover an impressive range of ideas from both traditional and modern harmonic analysis, such as: the Fourier transform, Shannon sampling, frames, wavelets, functions on Euclidean spaces, analysis on function spaces of Riemannian and sub-Riemannian manifolds, Fourier analysis on manifolds and Lie groups, analysis on combinatorial graphs, sheaves, co-sheaves, and persistent homologies on topological spaces. …”
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