This track focuses on the development and application of statistical methodologies specifically tailored for genetic data analysis. Topics include association mapping, single-marker analyses, and probabilistic models of genome sequences.

This session emphasizes computational approaches in genomics, including the use of bioinformatics tools to model and interrogate biological phenomena. Participants are encouraged to present novel algorithms and databases that facilitate genomic research.

This track explores the statistical analysis of functional genetics and evolutionary processes. Contributions may include studies on gene expression, evolutionary patterns, and the role of noncoding RNAs.

This session highlights statistical techniques used in comparative genomics and metagenomics. Presentations will cover methods for analyzing genomic data across different species and complex microbial communities.

This track focuses on statistical approaches to epigenomic data, including DNA methylation analysis. Researchers are invited to discuss the implications of epigenetic modifications on gene regulation and inheritance.

This session is dedicated to the statistical methodologies employed in analyzing next-generation sequencing data. Topics include data processing, variant calling, and the integration of NGS with other omics data.