Sepsis and Autoimmune Disease: Pathology, Systems Medicine, and Artificial Intelligence - Jendrek, Sebastian; Lai, Xin; Riemekasten, Gabriela; Vera González, Julio; Schmeck, Bernd; Bertrams, Wilhelm (Systems Medicine: Integrative, Qualitative and Computational Approaches, 2020)
Pathologic conditions in which the body׳s own response to an insult is the most damaging aspect of the disease, such as in auto-immunity and sepsis, have seen researchers and clinicians struggle to find therapeutic targets for decades. Large clinical cohorts and advanced molecular biology are key elements in the search for new medications. Methodology with increasing resolution is constantly being developed to identify new subsets of cells embedded in the disease framework and to map their complex gene expression profile, secretome and epigenome. Big data that is thus being generated require advanced computational methods in order to distil knowledge from them, and in order to use them as the basis for modeling approaches. Models need to integrate the spatial, temporal and organizational domains in order to reflect biology with a certain degree of fidelity. The ultimate goal of the combined efforts of clinical studies, molecular biology with cutting-edge technology and comprehensive mathematical modeling is the bench-to-bedside translation of knowledge to reduce the socio-economic burden of disease.
CRIS-Team Scopus Importer:2024-12-16
Keywords: Agent-based model (ABM); Autoantibodies; Autoimmunity; Biomarkers in rheumatic diseases; Cytokine; Epigenetics in rheumatic diseases; Genome-wide association study (GWAS); Mathematical modeling; Micro-thrombosis; Network analysis; systems level analysis; Ordinary differential equation (ODE); Organ dysfunction; Sepsis; Septic shock; Transcriptome analysis