This thesis focuses on the design, implementation and benchmarking of various software tools aiming to improve the identification and quantification of complex protein digests and metabolites analyzed by LC-MS/MS. The solutions involve different steps in the workflow, from enhanced data acquisition to novel post-acquisition data processing strategies. A significant increase of peptide/protein identification rates was achieved by combining exclusion and inclusion lists in data-dependent acquisition. Data-independent acquisition schemes are examined, in particular, related algorithms and computational methods are discussed. A program was implemented to design and optimize different SWATH acquisition methods and the benefits of variable isolation windows are demonstrated for the profiling of proteomic and metabolic samples. A ranking algorithm was developed to assign low priority to fragment ions affected by interference during SWATH acquisition and the improvements for label-free quantification are illustrated. Finally, several demultiplexing approaches towards peptide identification by sequence database search of SWATH spectra were investigated.