Systems biology in drug discovery

By Eric J. Kunkel. Nature Biotechnology, 2004

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Utilizing graph machine learning within drug discovery and development (2021, background): “tions on disease biology (the ‘-omics view’), genetic drivers of phenotypes (driven by bioengineering) through a network view of interacting biomolecules [149].”
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue (2013, background): “Motivated by the need to maximize biomarker data from costly drug discovery efforts and clinical trials, shrinking sample sizes, and increasing appreciation of disease complexity, the use of multiplexed molecular analysis has steadily increased (7).”
Structure-based Systems Biology for Analyzing Off-target Binding (2011, background): “Thus, it is critical to model and analyze off-target binding in the context of biological networks [101].”
Cancer: a Systems Biology disease. (2006, background): “…and the ultimate challenge in this field is to integrate all processes that are relevant for understanding the system cancer and to use the acquired understanding for drug development (Gatenby and Maini, 2003; Kitano, 2003; Butcher et al., 2004; Christopher et al., 2004; Khalil and Hill, 2005).”
Integration of biological networks and gene expression data using Cytoscape (2007, methodology): “(3) If attempting to load expression data using an ID-mapping identifier, first verify that the probeset attribute file was loaded correctly using the steps above.”