The proteome of a HUPO human serum reference sample was analyzed using multidimensional separation techniques at both the protein and the peptide levels. To eliminate false-positive identifications from the search results, we employed a data filtering method using molecular weight (MW) correlations derived from denaturing 1-DE. First, the six most abundant serum proteins were removed from the sample using immunoaffinity chromatography. 1-DE was then used to fractionate the remaining serum proteins according to the MW. Gel bands were isolated and in-gel digested with trypsin, and the resulting peptides were analyzed by 2-D LC/ESI-MS/MS. A SEQUEST search using the MS/MS results identified 494 proteins. Of these, 202 were excluded formally using protein data filtering as they were single-assignment proteins and their theoretical and electrophoretically-derived MWs did not correlate at high confidence. To evaluate this method, the results were compared with those of 1-D LC/MALDI-TOF/TOF and HUPO Plasma Proteome Project analyses. Our data filtering approach proved valuable in analysis of complex, large-scale proteomes such as human serum.