We study the Submass Finding Problem: given a string s over a weighted alphabet, i.e., an alphabet with a weight function :→N,werefertoamassM ∈NasasubmassofsifshasasubstringwhoseweightssumuptoM.Now,forasetofinput 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(s log s ), where s is the total mass of string s. Employing methods for compressing sparse polynomials, this runtime can be viewed as O((s) log2 (s)), where (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.

Finding Submasses in Weighted Strings with Fast Fourier Transform

Liptak, Zsuzsanna
2007-01-01

Abstract

We study the Submass Finding Problem: given a string s over a weighted alphabet, i.e., an alphabet with a weight function :→N,werefertoamassM ∈NasasubmassofsifshasasubstringwhoseweightssumuptoM.Now,forasetofinput 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(s log s ), where s is the total mass of string s. Employing methods for compressing sparse polynomials, this runtime can be viewed as O((s) log2 (s)), where (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.
2007
String algorithms, Weighted strings, Protein identification, Fast Fourier Transform
File in questo prodotto:
File Dimensione Formato  
DAM2007.pdf

solo utenti autorizzati

Tipologia: Versione dell'editore
Licenza: Copyright dell'editore
Dimensione 206.4 kB
Formato Adobe PDF
206.4 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/391084
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact