Statistics and Stochastic Modeling in Bioinformatics and Computational Biology
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 57
Special Issue Editor
Special Issue Information
Dear Colleagues,
The integration of statistics and stochastic modeling into bioinformatics and computational biology has profoundly influenced research in biology, medicine, and other life sciences. Advances in these fields have led to the development of statistical and probabilistic methods that address unique challenges, such as high-dimensional data analysis, modeling of complex biological systems, and predictive modeling in noisy environments.
The aim of this Special Issue is to showcase the role of statistical techniques and stochastic modeling in addressing biological problems. Submissions showcasing theoretical advancements, innovative algorithms, or practical case studies are welcome. Topics of interest include, but are not limited to, computational statistics, machine learning, and nonparametric methods in biology.
The scope is intentionally broad, and we encourage researchers to submit their work if they believe it is relevant to the overarching theme of statistics and stochastic modeling in bioinformatics and computational biology, even if the topic is not explicitly listed here.
This Special Issue is expected to bring together leading researchers and practitioners to provide new insights and practical solutions for the challenges faced in these fields. We look forward to receiving your contributions and learning from your perspectives.
Dr. Elizabeth P. Chou
Guest Editor
Manuscript Submission Information
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Keywords
- computational statistics
- machine learning
- high-dimensional data analysis
- computational biology
- bioinformatics
- stochastic modeling
- statistical methods
- data analysis
- predictive modeling
- bioinformatics
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