Topics covered in this book include fundamentals of modeling networks, circuits and pathways, spatial and multi cellular systems, image-driven systems biology, evolution, systems biology of disease and immunology, and personalized medicine. In the book chapter “An Integrative MuSiCO Algorithm: From the Patient-Specific Transcriptional Profiles to Novel Checkpoints in Disease Pathobiology”, written by Anastasia Meshcheryakova, Philip Zimmermann, Rupert Ecker, Felicitas Mungenast, Georg Heinze, and Diana Mechtcheriakova, the authors describe the systems biology-based integrative algorithm and discuss its applicability for translational research. This innovative approach is based on the implementation of consecutive analytical modules integrating advanced gene expression profiling of clinical patient specimens, prognostic/predictive modeling, next generation digital pathology, and systems biology. It consolidates in-depth expertise from diverse scientific and medical disciplines and hereby bridges systems biology and systems medicine to maximize the benefit of the patient. The authors also emphasize that the presented algorithm is universal in the sense that it can be applied for any biologically relevant signature and any type of complex multifactorial disorder. Given the multidisciplinary nature of the multimodular analysis strategy, the chapter might be of interest for specialists of diverse disciplines – scientists at biomedical research, oncologists and pathologists, biostatisticians, and systems biologists.
Citation
Meshcheryakova A., Zimmermann P., Ecker R., Mungenast F., Heinze G., Mechtcheriakova D. (2018) An Integrative MuSiCO Algorithm: From the Patient-Specific Transcriptional Profiles to Novel Checkpoints in Disease Pathobiology. In: Rajewsky N., Jurga S., Barciszewski J. (eds) Systems Biology. RNA Technologies. Springer, Cham
DOI https://doi.org/10.1007/978-3-319-92967-5_18