Shashanka Ubaru, Lior Horesh, et al.
Journal of Biomedical Informatics
We study the Submass Finding Problem: given a string s over a weighted alphabet, i.e., an alphabet Σ with a weight function μ : Σ → N, we refer to a mass M ∈ N as a submass of s if s has a substring whose weights sum up to M. Now, for a set of input masses { M1, ..., Mk }, we want to find those Mi which are submasses of s, and return one or all occurrences of substrings with mass Mi. We present efficient algorithms for both the decision and the search problem. Furthermore, our approach allows us to compute efficiently the number of different submasses of s. The main idea of our algorithms is to define appropriate polynomials such that we can determine the solution for the Submass Finding Problem from the coefficients of the product of these polynomials. We obtain very efficient running times by using Fast Fourier Transform to compute this product. Our main algorithm for the decision problem runs in time O (μs log μs), where μs is the total mass of string s. Employing methods for compressing sparse polynomials, this runtime can be viewed as O (σ (s) log2 σ (s)), where σ (s) denotes the number of different submasses of s. In this case, the runtime is independent of the size of the individual masses of characters. © 2006 Elsevier B.V. All rights reserved.
Shashanka Ubaru, Lior Horesh, et al.
Journal of Biomedical Informatics
John S. Lew
Mathematical Biosciences
Alfred K. Wong, Antoinette F. Molless, et al.
SPIE Advanced Lithography 2000
Michael Ray, Yves C. Martin
Proceedings of SPIE - The International Society for Optical Engineering