Algorithmic Mass Spectrometry
This advanced PDF explores mass
spectrometry from the computational and algorithmic perspective. Peptide de novo
sequencing, database searching, and comparing mass spectra using significance
testing, such as p-values and E-values, are discussed in this note. It also
covers isotope distributions and fragmentation patterns to shed light on the
mathematical aspects behind its analysis of mass spectrometry data. It reaches
more complex dimensions and discusses issues like glycan sequencing, machine
learning, and decomposition of the isotope pattern. Finally, the note is an
invaluable resource for anyone interested in mass spectrometry and computational
methods, providing a foundation for yet more complicated applications in
bioinformatics and structural biology.
Author(s): Sebastian Bocker
253 Pages