Protein-DNA recognition plays essential role in the regulation of genetic information. Transcription factors in higher organisms recognize multiple target sequences and regulate multiple genes in a complex manner. In order to understand the molecular mechanism of target recognition, and to predict target genes for transcription factors at the genome level, it is important to analyze the relationship between the structure and function (specificity) of transcription factors. We have used a knowledge-based approach, utilizing rapidly increasing structural data of protein-DNA complexes, to derive empirical potential functions for the specific interactions between bases and amino acids as well as for DNA conformation, from the statistical analyses on the structural data. Then these statistical potentials are used to quantify the specificity of protein-DNA recognition. The quantification of specificity has enabled us to establish the structure-function analysis of transcription factors, such as the effects of binding cooperativity on target recognition. The method is also applied to real genome sequences, predicting potential target sites. We are also using computer simulations of base-amino acid interactions in order to complement the empirical method. Combining the two approaches together, we can better understand the mechanism of protein-DNA recognition and improve the target prediction of transcription factors.