Genetic underpinnings of human complex diseases are highly polygenic, comprising hundreds or thousands of genetic variants, each having a small effect on disease risk. Over the last decade, significant advances have been achieved in gene discovery of complex disorders, paving the way for an era of precision medicine in health care. However, it remains challenging to reveal how genes and genetic variants relate to each other and how they collectively affect the risk of complex diseases. Thanks to the rapid technology innovation in artificial intelligence and genome sequencing, it is feasible now to gain insightful and actionable information from genomic data, leading to more personalized diagnosis and treatment.
This Research Topic aims to publish applications of innovative computational strategies and algorithms to find the better solutions of complex genetic and genomic problems in a time efficient manner. We look for original research findings and practical applications that contribute to the diagnosis and management of human complex disorders.
Specifically, we welcome Original Research, Method, Review, and other articles including, but not limited to, the following aspects:
• Genome-wide association studies and post GWAS analyses of complex diseases
• Phenome-wide association studies of complex diseases
• Polygenic risk score and genetic correlation analyses of multiple complex diseases
• Gene set enrichment and gene network analyses of complex diseases
• Computational approaches to analyze omics data of complex diseases
• Integrative analysis of multi-omics data for gene discovery of complex diseases
• Disease gene prioritization using advanced computational methods such as artificial intelligence (AI) techniques
• Reviews of biomedical data/databases, computational methods/tools, and outstanding questions/opinions related to human complex diseases
Genetic underpinnings of human complex diseases are highly polygenic, comprising hundreds or thousands of genetic variants, each having a small effect on disease risk. Over the last decade, significant advances have been achieved in gene discovery of complex disorders, paving the way for an era of precision medicine in health care. However, it remains challenging to reveal how genes and genetic variants relate to each other and how they collectively affect the risk of complex diseases. Thanks to the rapid technology innovation in artificial intelligence and genome sequencing, it is feasible now to gain insightful and actionable information from genomic data, leading to more personalized diagnosis and treatment.
This Research Topic aims to publish applications of innovative computational strategies and algorithms to find the better solutions of complex genetic and genomic problems in a time efficient manner. We look for original research findings and practical applications that contribute to the diagnosis and management of human complex disorders.
Specifically, we welcome Original Research, Method, Review, and other articles including, but not limited to, the following aspects:
• Genome-wide association studies and post GWAS analyses of complex diseases
• Phenome-wide association studies of complex diseases
• Polygenic risk score and genetic correlation analyses of multiple complex diseases
• Gene set enrichment and gene network analyses of complex diseases
• Computational approaches to analyze omics data of complex diseases
• Integrative analysis of multi-omics data for gene discovery of complex diseases
• Disease gene prioritization using advanced computational methods such as artificial intelligence (AI) techniques
• Reviews of biomedical data/databases, computational methods/tools, and outstanding questions/opinions related to human complex diseases