A statistical model to correct systematic bias introduced by algorithmic thresholds in protein structural comparison algorithms

The identification of protein function is crucial to under-standing cellular processes and selecting novel proteins as drug targets. However, experimental methods for determining protein function can be expensive and time-consuming. Protein partial structure comparison methods seek to guide and accel-erate the process of function determination by matching char-acterized functional site representations, motifs, to substruc-tures within uncharacterized proteins, matches. One common difficulty of all protein structural comparison techniques is the computational cost of obtaining a match. In an effort to main-tain practical efficiency, some algorithms employ efficient ge-ometric threshold-based searches to eliminate biologically ir-relevant matches. Thresholds refine and accelerate the method by limiting the number of potential matches that need to b