1. A method for defining a misidentification probability, comprising: dividing an experimental protein into one or more experimental peptides using a liquid chromatography (LC) tandem mass spectrometer (MS/MS); providing MS/MS data of the one or more experimental peptides by way of the liquid chromatography (LC) tandem mass spectrometer (MS/MS); receiving data representing a set of matches of the one or more experimental peptides to reference peptides that can be derived from a protein in a database of proteins; calculating a probability of observing by chance, in a search of the database of proteins, a set of matches equivalent to or better than the represented set of matches, wherein the probability of observing by chance a set of matches equivalent to or better than the represented set of matches can be expressed as one divided by a number of similar searches of a database of random proteins, the number of similar searches representing an expected number of similar searches necessary to observe by chance the set of matches equivalent to or better than the represented set of matches; defining the misidentification probability using the probability of observing by chance a set of matches equivalent to or better than the represented set of matches, wherein the step of defining the misidentification probability includes performing a calculation of the form 
 D ( d,n,p,Q )=1−(1 −C ( d,n− 1 ,p )) Q where d is the number of experimental peptides, n is the number of the matches of a subset of the experimental peptides, a parameter p being a measure of the relative size of a database protein to a size of the database, wherein the measure of the relative size is approximated as a ratio of the number of different peptides in the matching database protein, w, and a number of different singly counted peptides in the database being searched, S, such that p=w/S, Q is a maximum number of matched proteins, wherein Q is defined as Q(d,n)=max(1,min(d,N)), where d is the number of experimental peptides and N is the number of proteins represented by the peptides being searched so that Q(d,n) represents an upper bound to the maximum number of proteins that can be matched with at least one peptide, and C(d, n−1, p) is the probability of observing by chance the matches of the number of experimental peptides to reference peptides or better matches of experimental peptides to reference peptides when one experimental peptide is known to match a reference peptide that can be derived from each protein in the collection of database proteins; and outputting to a user, the results of the probability analysis of the experimental protein, wherein the misidentification probability indicates to the user the likelihood of having an incorrect peptide match.