Biostatistics and Stochastic Process Analysis
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 81
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue on “Biostatistics and Stochastic Process Analysis” marks a major step forward in the convergence of mathematical statistics, biology, and medicine. This edition focuses on how advanced statistical methods can deepen our understanding of biological processes and enhance health outcomes.
Biostatistics is crucial for designing biomedical research and analyzing data from clinical trials, observational studies, and genomics. It is essential for interpreting complex datasets, allowing researchers to draw dependable conclusions about health risks and the effects of treatments. Integrating stochastic process analysis into this domain introduces a more profound mathematical structure that models the inherent randomness in biological systems and the progression of diseases.
In this issue, readers will encounter groundbreaking research articles that illustrate the use of stochastic models in areas like epidemic modeling, genetic variation, and cellular dynamics. For example, a featured paper introduces a new stochastic model that predicts the spread of infectious diseases by including random variations in transmission rates, offering forecasts that are more accurate than those from traditional deterministic models. Another important article examines how Markov Chain Monte Carlo methods are used in genetic association studies, demonstrating how these approaches can more precisely identify genetic markers associated with diseases. This method is especially useful for managing the high-dimensional data common in modern genomics.
By compiling the latest methodologies and their applications, this Special Issue strives to enrich our understanding of how stochastic processes and biostatistical methods can be collaboratively employed to tackle significant issues in biology and medicine. It is a vital resource for statisticians, biologists, and healthcare professionals, providing fresh perspectives and tools to manage the complexities of the life sciences.
Dr. Suvo Chatterjee
Guest Editor
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Keywords
- biostatistics
- stochastic analysis
- epidemic modeling
- statistical genomics
- cellular dynamics
- survival analysis
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