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Protein biomarker druggability profiling
Affiliation:1. University of New Mexico Health Sciences Center, Albuquerque, NM 87131, United States;2. Myriad RBM, Austin, TX 78759, United States
Abstract:Developing automated and interactive methods for building a model by incorporating mechanistic and potentially causal annotations of ranked biomarkers of a disease or clinical condition followed by a mapping into a contextual framework in disease-linked biochemical pathways can be used for potential drug-target evaluation and for proposing new drug targets. We demonstrate the potential of this approach using ranked protein biomarkers obtained in neonatal sepsis by enrolling 127 infants (39 infants with late onset neonatal sepsis and 88 control infants) and by performing a focused proteomic profile of the sera and by applying the interactive druggability profiling algorithm (DPA) developed by us.
Keywords:Protein biomarkers  Pathway analysis  Druggability profiling  Mechanistic annotation  Neonatal sepsis  Machine learning
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