Automated Interpretation of Edman Sequencing Data

We will develop statistical algorithms and software providing automated amino acid sequence determiprotein sequencing by Edman degradation. Studies indicate that automatic interpretation of sequencininadequate. Manual interpretation of sequencing data is time consuming, expensive, and provides no sestimates. This project's long-term goals will provide: 1) significant improvement in the accuracy ocalling, especially for low to sub-picomole sample quantities; 2) significant increase in the confidresidues (and number of residues) determined from later cycles; 3) reliable determination of candidaprotein, including probability that each residue/candidate sequence is correct; 4) similar determinamixture of several proteins sequenced simultaneously. The Phase l effort will demonstrate the feasibproviding prototype software able to accurately determine sequences from the relevant data. Softwaresignificant fraction of the long-term goals of this work would be of great importance due to the appsequencing in fields ranging from immunology and virology to genetics and drug design in academic, mpharmaceutical, and agricultural contexts. Such software would be invaluable to both producers and usequencing equipment.