@TechReport{Dartmouth:TR2000-362,
  author = {Chris Bailey-Kellogg and John J. Kelley and Clifford Stein and Bruce Randall Donald},
  title = {{Reducing Mass Degeneracy in SAR by MS by Stable Isotopic Labeling}},
  institution = {Dartmouth College, Computer Science},
  address = {Hanover, NH},
  number = {TR2000-362},
  year = {2000},
  month = {February},
  URL = {http://www.cs.dartmouth.edu/reports/TR2000-362.ps.Z},
  comment = {
    This report supercedes <A HREF="http://www.cs.dartmouth.edu/reports/abstracts/TR99-359/">TR99-359</A>.
         To appear in the <a href="http://ismb00.sdsc.edu/">8th
    International Conference on Intelligent Systems for Molecular Biology</a>,
    (August 20-23, 2000) La Jolla, CA (Accepted; in press).
  },
  abstract = {
    Mass spectrometry (MS) promises to be an invaluable tool for
    functional genomics, by supporting low-cost, high-throughput
    experiments.  However, large-scale MS faces the potential problem of
    mass degeneracy -- indistinguishable masses for multiple
    biopolymer fragments (e.g. from a limited proteolytic digest).  This
    paper studies the tasks of planning and interpreting MS experiments
    that use selective isotopic labeling, thereby substantially reducing
    potential mass degeneracy.  Our algorithms support an
    experimental-computational protocol called Structure-Activity
    Relation by Mass Spectrometry (SAR by MS), for elucidating the
    function of protein-DNA and protein-protein complexes.  SAR by MS
    enzymatically cleaves a crosslinked complex and analyzes the resulting
    mass spectrum for mass peaks of hypothesized fragments.  Depending on
    binding mode, some cleavage sites will be shielded; the absence of
    anticipated peaks implicates corresponding fragments as either part of
    the interaction region or inaccessible due to conformational change
    upon binding.  Thus different mass spectra provide evidence for
    different structure-activity relations.  We address combinatorial and
    algorithmic questions in the areas of data analysis
    (constraining binding mode based on mass signature) and
    experiment planning (determining an isotopic labeling strategy to
    reduce mass degeneracy and aid data analysis).  We explore the
    computational complexity of these problems, obtaining upper and lower
    bounds.  We report experimental results from implementations of our
    algorithms.
  }
}