Section “Molecular medicine: gene expression and human diseases”
The development of high-throughput omics technologies has made it possible to perform large-scale sequencing of individual patients’ genomes and to profile them using transcriptomic, proteomic, and metabolomic analyses. The resulting information explosion in molecular medicine has led to the accumulation of enormous datasets, growing at rates of up to tens of exabytes per year.
Among the key tasks of molecular medicine currently being formed, addressed on the basis of multi-omics data using modern information technologies, are the following:
- molecular epidemiology: analysis of the prevalence of multifactorial diseases in populations and ethnic groups;
- multi-omics profiling of patients;
- development of mathematical models to forecast the spatiotemporal dynamics of diseases treatable by therapy (internal medicine);
- identification of genetic markers (polymorphisms in genomic DNA, changes in RNA expression, proteins, metabolite levels, etc.) associated with diseases;
- assessment of the predictive power of these markers and of the risk of predisposition to developing multifactorial diseases;
- reconstruction of gene networks from multi-omics data, formed by dozens (and sometimes hundreds!!!) of genes controlling the development of multifactorial diseases;
- prediction of disease progression using computer models of gene-network functioning dynamics;
- prevention and personalized therapy: selection of safe and effective drugs and their dosages, taking into account the patient’s individual metabolism, which helps minimize side effects.
The rapid growth in the volume of multi-omics and other data obtained in precision medicine requires the development of a new generation of analysis methods based on integrating classical bioinformatics approaches with machine learning and artificial intelligence methods.
The purpose of organizing and holding the Section is to consider these and other issues that are important for solving problems in molecular medicine.