Hybrid Conferencee

International Conference on Computational Genetics and Genetic Algorithms (ICCGGA - 26)

12th - 13th August 2026 | Al Rayyan, Qatar

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Call for Papers Extended:
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Certificate of Presentation:
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Abstract Submissions Open:
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Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Al Rayyan conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Al Rayyan, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Al Rayyan."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 3
SDG 3 Good Health and Well-being
SDG 4
SDG 4 Quality Education
SDG 7
SDG 7 Affordable and Clean Energy
Track 01

Advancements in Computational Genetics

This track focuses on the latest methodologies and technologies in computational genetics. Researchers are invited to present their findings on novel algorithms and computational frameworks that enhance genetic analysis.

Track 02

Genetic Algorithms in Bioinformatics

This session explores the application of genetic algorithms in solving complex bioinformatics problems. Contributions should highlight innovative uses of these algorithms in sequence alignment, gene prediction, and data mining.

Track 03

Population Genetics and Evolutionary Simulations

This track invites discussions on population genetics models and their applications in evolutionary simulations. Papers should address theoretical advancements and empirical studies that enhance our understanding of genetic variation and evolution.

Track 04

Modeling and Analysis of Genomic Data

This session emphasizes the development of models for analyzing large-scale genomic data. Submissions should focus on statistical techniques and machine learning approaches that facilitate genomic insights.

Track 05

Statistical Genetics and Genotype-Phenotype Mapping

This track aims to explore the intersection of statistical genetics and genotype-phenotype relationships. Researchers are encouraged to present methodologies that improve the prediction of phenotypic traits from genetic data.

Track 06

Algorithm Development and Optimization Techniques

This session is dedicated to the development of novel algorithms and optimization techniques in genetics research. Contributions should demonstrate how these advancements can improve computational efficiency and accuracy.

Track 07

Systems Biology and Genetic Network Modeling

This track focuses on systems biology approaches to genetic network modeling. Papers should discuss how integrative models can elucidate the complex interactions within biological systems.

Track 08

Functional Genomics and Variant Annotation

This session invites research on functional genomics and the annotation of genetic variants. Presentations should highlight innovative strategies for understanding the functional impact of genetic variations.

Track 09

Predictive Modeling in Genomics

This track emphasizes the role of predictive modeling in genomics research. Submissions should showcase applications of machine learning and statistical methods in predicting genetic outcomes.

Track 10

Genetic Programming and Evolutionary Algorithms

This session explores the use of genetic programming and evolutionary algorithms in solving genetic problems. Researchers are encouraged to present novel applications and theoretical advancements in this area.

Track 11

Integrative Approaches in Computational Genomics

This track focuses on integrative approaches that combine multiple data types and methodologies in computational genomics. Contributions should highlight how these approaches enhance our understanding of genetic phenomena.