Understanding how proteins, such as transcription factors, search target sites on DNA and in cell environments for genetic regulation, is fundamentally important in molecular biophysics. After about fifty years of experimental and theoretical approaches, models such as facilitated diffusion of protein on DNA, have been well formulated, yet physical understanding, from local structure dynamics to genome-wide search mechanisms, remains limited due to complications of protein-DNA interactions and heterogeneous chromatin configurations. With technological advancements, from structural determination of protein-DNA complexes and high-performance computing, to genome-wide ChIP-seq and high-resolution live-cell imaging and tracking, there are new opportunities to substantially improve existing knowledge. The current method collection brings together recent computational and experimental approaches, utilizing the above advanced technologies, supplying protocols and details to elucidate key technique issues, and reducing barriers to make these techniques transferable and reproducible. To probe protein-DNA interactions from the bottom-up, structure-based molecular dynamics simulation techniques, from atomic to coarse-grained levels are used, along with methods for enhanced or distributed sampling and dimension-reduction representation. With regards to the top-down cellular scale, high throughput protein profiling and statistical data learning help to interrogate protein-DNA association throughout the genome, while real-time single-molecule tracking and imaging essentially demonstrate how proteins search via diffusion and clustering, individually and collectively. Overall, this collection aims at promoting transparency and reproducibility for implementing a myriad of quantitative techniques, facilitating collaborative efforts for improving understanding, and accelerating future developments.