Motivation: Profile-based protein homology detection algorithms are valuable tools in genome annotation and protein classification. By utilizing information present in the sequences of homologous proteins, profile-based methods are often able to detect extremely weak relationships between protein sequences, as evidenced by the largescale benchmarking experiments such as CASP and LiveBench. Results: We study the relationship between the sensitivity of a profile-profile method and the size of the

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... sequence profile, which is defined as the average number of different residue types observed at the profile's positions. We also demonstrate that improvements in the sensitivity of a profile-profile method can be made by incorporating a profile-dependent scoring scheme, such as position-specific background frequencies. The techniques presented in this article are implemented in an alignment algorithm UNI-FOLD. When tested against other well-established methods for fold recognition, UNI-FOLD shows increased sensitivity and specificity in detecting remote relationships between protein sequences. Availability: UNI-FOLD web server can be accessed at http://