Ten-Yang Yen

Learn More
Determining the number and location of disulfide bonds within a protein provide valuable insight into the protein's three-dimensional structure. Purely computational methods that predict the bonded cysteine pairings given a protein's primary structure have limitations in both prediction correctness and the number of bonds that can be predicted. Our approach(More)
BACKGROUND Determining the disulfide (S-S) bond pattern in a protein is often crucial for understanding its structure and function. In recent research, mass spectrometry (MS) based analysis has been applied to this problem following protein digestion under both partial reduction and non-reduction conditions. However, this paradigm still awaits solutions to(More)
Mesenchymal stromal cells (MSCs) transiently transfected with notch1 intracellular domain (NICD) are beneficial for neurological disorders as observed in several preclinical studies. Extracellular matrix (ECM) derived from NICD-transfected MSCs has been previously shown to support in vitro neural cell growth and survival better than that of un-transfected(More)
We present an algorithmic approach for determining, in polynomial time, disulfide bonds in proteins using mass spectrometry data. The proposed technique is based on matching the set of all theoretically possible disulfide bonded structures with precursor ions derived from a tandem MS/MS experiment. For each match found, theoretical fragments from a(More)
The tertiary structure and biological function of a protein can be better understood given knowledge of the number and location of its disulfide bonds. By utilizing mass spectrometric (MS) experimental procedures that produce spectra of the protein's peptides joined by a disulfide bond, we can make initial identifications of these bonded cysteine pairings.(More)
  • Ten-Yang Yen, Sucharita M. Dutta, Christina Litsakos-Cheung, Alejandro A. Corona, Leslie C. Timpe, Bruce A. Macher
  • 2013
Glycoproteomics has emerged as a prime area of interest within the field of proteomics because glycoproteins have been shown to function as biomarkers for disease and as promising therapeutic targets. A significant challenge in the study of glycoproteins is the fact that they are expressed in relatively low abundance in cells. In response, various(More)
Approximately 20 drugs have been approved by the FDA for breast cancer treatment, yet predictive biomarkers are known for only a few of these. The identification of additional biomarkers would be useful both for drugs currently approved for breast cancer treatment and for new drug development. Using glycoprotein expression data collected via mass(More)
  • 1