AI Research Group
A multidisciplinary research and development unit coordinating the development of artificial intelligence applications in personalized diagnosis, treatment, and risk prediction processes based on individuals' genetic characteristics
The human genome can be thought of as a giant book consisting of 3 billion letters. This Research Group is like a research team trying to understand the effect of each letter in that book on health.
Just like putting together pieces of a puzzle, we aim to produce health solutions specific to each individual by bringing genetic information together with clinical meaning. We work through processing genome sequencing data, genetic variant analysis, and identification of disease-related biomarkers.
The main goal of our group is to support the transition from the traditional "same treatment for everyone" approach to the "unique treatment for everyone" paradigm. This process means not only technological development but also the personalization of medicine.
Main application areas where we develop AI-supported solutions in genomics and bioinformatics
Genetic variant analysis and identification of disease-related biomarkers
Detection and diagnostic algorithms for genetic-origin rare diseases
Tumor profiling systems and targeted treatment selection
Personalized drug dosage calculation and side effect prediction
Disease risk analysis and genetic counseling support
Integration of genomics, transcriptomics, proteomics, and metabolomics data
Our genomic artificial intelligence systems used and tested in real clinical environments
Analyzes genome data obtained from tumor tissue to determine targeted treatment options with 89% accuracy and predicts drug resistance development risk.
Analyzes patient genetic profile to calculate optimal dosage for 150+ drugs, assesses side effect risk, and offers alternative drug recommendations.
Integrates clinical findings and genetic test results to provide diagnostic recommendations with 94% accuracy among 7000+ rare diseases and reduces average diagnosis time from 6 months to 2 months.
Uses polygenic risk scores to predict coronary artery disease risk with 86% sensitivity and recommends personalized prevention strategies.
Illuminates molecular mechanisms of complex diseases by combining genome, transcriptome, and proteome data.
Develops personalized nutrition recommendations based on gut microbiome profile and genetic characteristics.
Analyzes maternal and paternal genetic data to calculate risk for 300+ genetic diseases.
Predicts vaccine effectiveness by analyzing HLA typing and immune system gene variants.
With our multidisciplinary approach, we collaborate with experts from health and engineering fields
Core research topics we focus on for the development of artificial intelligence technologies in genomics and personalized medicine
By combining genomics (DNA sequence), transcriptomics (RNA expression), proteomics (protein levels), and metabolomics (metabolite concentrations) data, we reveal the complete picture of cellular processes.
In genome-wide association studies (GWAS), millions of genetic variants are tested. We use advanced correction methods to overcome the multiple testing problem and filter out results that appear significant by chance.
Drug metabolism is a multifactorial process. We develop accurate dosage recommendations by modeling the complex interactions of multiple genes, age, gender, other drugs, and environmental factors.
Since there are more than 7000 rare diseases, algorithms intelligently combine phenotype (disease symptoms) and genotype (genetic variants) to reach accurate diagnosis. This process is similar to a thousand-piece jigsaw puzzle game.
Genetic data can affect not only the individual but also their family and future generations. We develop comprehensive protocols on data security, informed consent procedures, and strategies to prevent genetic discrimination.
Bringing laboratory findings together with clinical meaning is critical. We develop systems that can manage the uncertainties provided by genetic profiles about disease risk and provide clear information to clinicians for making clear decisions.
Concrete achievements and clinical impacts of our Research Group in genomics and personalized medicine
Would you like to collaborate with us to develop artificial intelligence applications in genomics and personalized medicine?
System development with real patient data in collaboration with hospitals and genetic centers
Inter-university genomic research projects and joint publications
Genomic platform development and commercialization with biotechnology companies