ICBGER · Registering as Listener

International Conference on Biostatistics and Genetic Epidemiology Research

1st Dec – 2nd Dec 2026 Jakarta Raya, Indonesia Standard / Physical Participation
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ConferenceICBGER
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Conference Session Tracks
SDG Wheel

SDG-Aligned Research Themes

International Conference on Biostatistics and Genetic Epidemiology Research conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 2 - Zero Hunger SDG 3 - Good Health and Well-being SDG 4 - Quality Education SDG 9 - Industry, Innovation and Infrastructure

This track focuses on innovative biostatistical techniques that enhance the analysis of biological data. Emphasis will be placed on novel methodologies that improve the accuracy and efficiency of statistical modeling in life sciences.

This session will explore the intersection of genetic epidemiology and public health initiatives. Discussions will center on how genetic insights can inform disease prevention and health promotion strategies.

This track will delve into the principles of population genetics and their applications in understanding genetic variation within populations. Researchers will present findings that illuminate the evolutionary dynamics influencing genetic diversity.

This session will highlight the role of statistical genetics in identifying genetic variants associated with diseases. Presentations will cover methodologies and findings from recent genome-wide association studies (GWAS).

This track will address the theoretical foundations and practical applications of quantitative genetics. Participants will discuss heritability estimation, trait mapping, and their implications for breeding and selection.

This session will focus on the integration of genomic data with epidemiological research. Topics will include the use of genomic information to identify risk factors and inform public health policies.

This track will explore computational approaches in genetics research, including software tools and algorithms for variant analysis. Emphasis will be placed on the role of computational methods in managing and interpreting large-scale genomic data.

This session will discuss the development and application of predictive models in genetic research. Participants will present case studies demonstrating how predictive analytics can enhance understanding of genetic risk factors.

This track will examine the challenges associated with heritability estimation in complex traits. Researchers will present innovative approaches to accurately quantify heritability in diverse populations.

This session will focus on the latest advancements in trait mapping techniques and their implications for understanding complex traits. Presentations will highlight novel methodologies and case studies from various fields.

This track will cover the entire spectrum of variant analysis, from discovery through to clinical application. Discussions will include the implications of genetic variants for disease risk and treatment strategies.

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