%0 Journal Article
%T GNU polyxmass: a software framework for mass spectrometric simulations of linear (bio-)polymeric analytes
%A Filippo Rusconi
%J BMC Bioinformatics
%D 2006
%I BioMed Central
%R 10.1186/1471-2105-7-226
%X The GNU polyxmass software framework performs common (bio-)chemical simulations¨Calong with simultaneous mass spectrometric calculations¨Cfor any kind of linear bio-polymeric analyte (DNA, RNA, saccharides or proteins). The framework is organized into three modules, all accessible from one single binary program. The modules let the user to 1) define brand new polymer chemistries, 2) perform quick mass calculations using a desktop calculator paradigm, 3) graphically edit polymer sequences and perform (bio-)chemical/mass spectrometric simulations. Any aspect of the mass calculations, polymer chemistry reactions or graphical polymer sequence editing is configurable.The scientist who uses mass spectrometry to characterize (bio-)polymeric analytes of different chemistries is provided with a single software framework for his data prediction/analysis needs, whatever the polymer chemistry being involved.Mass spectrometry has proven essential in structural studies in which biopolymer molecules of a variety of polymer chemistries are involved. Indeed, while proteins were once the main biopolymeric analytes studied by mass spectrometry, oligo(deoxy)ribonucleotides and saccharides also are routinely analyzed today and mass spectrometry is used, for example, for the characterization of DNA-protein complexes or for the gas phase sequencing of saccharides (for reviews, see [1-4]). The current and ever-increasing variety of mass spectrometer designs affords a rather large array of experiments that can be performed on different biopolymers. Thus, the variety of polymer chemistries analyzable by mass spectrometry is compounded by the variety of mass spectrometric experiments, producing an extremely diverse set of mass data to be either predicted or analysed with the help of appropriate software tools. It is noteworthy that, while some experiments are almost completely automatable (like in the case of high-throughput proteomics), a majority of the experiments being performed in mass spe
%U http://www.biomedcentral.com/1471-2105/7/226