Professor Marko Vuskovic joined the Department of Computer Science in 1986. Since then he developed two robotics courses: Robotics: Mathematics, Programming and Control (CS556) and Advanced Robotics, which he still teaches today. He is head of the Robotics and Neural Networks Laboratory.
His research interest has evolved from robot kinematics and dynamics to pattern recognition of prehensile EMG signals, and finally to bioinformatics applied to cancer research.
In 2006 Professor Vuskovic co-founded a startup company "Cellexicon" in La Jolla, California, and then in 2008 he joined the Tumor Glycomic Laboratory at the NYU School of Medicine as a bioinformatician and consultant. The main focus of his recent research is development of new pattern recognition algorithms which use data from the printed glycan array (PGA) and help discover new molecular biomarkers and test for early detections, diagnosis and prognosis of various human malignancies aand viral diseases. PGAs are a new high-throughput biomarker platform similar in concept to DNA arrays but contain depositions of various carbohydrate structures (glycans) instead of spotted DNAs. The philosophy of PGA-based markers discovery lies in the response of the immune system measured by the level of binding of anti-glycan antibodies from human serum to the glycans on the array. More details about PGAs and the associated bioinformatics research of Professor Vuskovic can be found in:
Vuskovic M, Barbuti AM, Goldsmith-Rooney E, Glassman L, Bovin N, et al. (2013) Plasma Anti-Glycan Antibody Profiles Associated with Nickel level in Urine. J Proteomics Bioinform 6: 302-312. doi:10.4172/jpb.1000295
Vuskovic M, Xu H, Bovin NV, Pass HI, Huflejt ME. Processing and analysis of serum antibody binding signals from Printed Glycan Arrays for diagnostic and prognostic applications. Int J Bioinform Res Appl; 2011; 7(4):402-26