Proteins are critical actors within the cell, enabling complex biological processes essential for cell survival, development, and homeostasis. Generally, proteins function via their interactions with other biomolecules, such as nucleic acids, making knowledge of these interactions and the players involved essential to our understanding of even basic biological function. This dissertation describes the advancement of technologies for the identification of proteins interacting with target nucleic acid sequences (e.g., genomic loci or RNA transcripts), as well as the development of approaches for better understanding the diversity of proteins expressed in human cells. Chapter 2 presents the application of HyCCAPP (Hybridization Capture of Chromatin-Associated Proteins for Proteomics), a technology developed in the Smith lab for the study of protein-DNA interactions in a locus-specific manner, to identify the protein interactome of human centromeric alpha satellite DNA. We identified 90 proteins as enriched in alphoid chromatin, and this list included many known centromere-binding proteins in addition to multiple novel alpha satellite-binding proteins. This work represents the first application of the HyCCAPP technology in mammalian cells and is the first DNA-centric examination of human protein-alpha satellite interactions. In Chapter 4, we present a detailed and comprehensive guide for the application of HyPR-MS (Hybridization Purification of RNA-protein complexes followed by Mass Spectrometry), a technology developed in the Smith lab for the identification of proteins interacting with target RNA transcripts. It is our hope that the practical advice provided in this chapter will enable the widespread utilization of this technology. In Chapter 3, we explored how different types of proteomics data could be integrated to maximize proteoform identifications from a human cell line. Proteoforms are the specific molecular forms of proteins expressed in the cell, accounting for genetic variation, alternative splicing, and post-translational modifications. Through the integration of intact-mass, top-down, and bottom-up proteomics data, we were able to identify ~1,200 proteoforms representing 484 genes from the human Jurkat cell line. Finally, in Chapter 5, we present the current status of our work to combine proteoform analysis with HyPR-MS to enable the first ever study of the proteoforms bound to a target RNA transcript.