Fueled by an NIH SBIR grant, analytics firm Cytobank is building out its machine-learning algorithms and adding pipelines to support big-picture research.
CytoReason's machine-learning algorithms extract information from multi-omic measurements to improve indication prioritization and highlight new treatment targets.
Six microRNAs appeared to be present at enhanced levels in cerebrospinal fluid from symptom-free individuals with characteristic Huntington disease gene expansions.
Investigators identified candidate protein markers from aptamer-based proteomic profiles of samples from women with or without late-onset preeclampsia.
CSO Phil Stephens said the firm is finding specific genomic alterations that appear to affect sensitivity to immunotherapies, as it also advances overall mutation burden testing.
