Mass spectrometry has emerged as having a vital role in various applications to biochemical fields. In this thesis, we have utilized a variety of mass spectrometry techniques for both bacteriophage proteomics and colostrum and milk lipidomics studies. Our first study was the proteome characterization of Great Salt Lake bacteriophage NS01 with SDS-PAGE GEL to separate the viral proteins and high performance liquid chromatography (HPLC) coupled with an LTQ Orbitrap to identify the proteins after in-gel digestion. In this project, we have successfully identified 11 proteins with high confidence, p-values < 0.01, including coat protein gp88 with a coverage of 91% and tail protein gp86 with a coverage of 40.96%, which facilitated the classification of NS01 as a T7-like phage. Our second study was the discovery of colostrum and milk biomarkers that can be used to predict the likelihood of development of production-related metabolic diseases (PRMDs) in dairy cows through a lipidomics approach. In this study, an electrospray ionization, time-of-flight mass spectrometer was applied to lipid profiling, quantification and significant biomolecule selection. A Q-Star quadrupole, orthogonal time-of-flight mass spectrometer and an Agilent 6530 accurate-mass quadrupole/time-of flight mass spectrometer were both used for lipid biomarker fragmentation and identification. According to linear discriminative statistical modeling, three panels of biomarkers were defined. A combination of 2 milk lipid predictors, including DG18:0/18:0 and TG 18:0/18:0/18:1, provided PRMD predictions with 75.0% sensitivity at 90.0% specificity. A combination of 3 colostrum lipid predictors, including TG16:0/18:1/18:3, DG16:0/16:0 and C40H60NO, provided PRMD prediction with 90.0% sensitivity at 86.4% specificity. Furthermore, a combination of 7 colostrum and milk biomarkers, including calculated differences between 'shared' markers found to be significantly different in both colostrum and milk, provided a predictive sensitivity of 87.5% at a specificity of 100%. Thus, three panels of lipid biomarkers have been discovered in 1-4 day postparturient dairy cow colostrum and milk that can be used to predict resistance or susceptibility prior to onset of clinically apparent PRMDs. These novel lipids could be used as important diagnostic predictors in the future. Therefore, mass spectrometry based proteomics and lipidomics approaches have been efficient tools in the biochemical research described in this thesis.