Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16729
Title: BRAIN 2.0: Time and Memory Complexity Improvements in the Algorithm for Calculating the Isotope Distribution
Authors: Dittwald, Piotr
VALKENBORG, Dirk 
Issue Date: 2014
Source: JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY, 25 (4), p. 588-594
Abstract: Abstract. Recently, an elegant iterative algorithm called BRAIN (Baffling Recursive Algorithm for Isotopic distributioN calculations) was presented. The algorithm is based on the classic polynomial method for calculating aggregated isotope distributions, and it introduces algebraic identities using Newton-Girard and Viète’s formulae to solve the problem of polynomial expansion. Due to the iterative nature of the BRAIN method, it is a requirement that the calculations start from the lightest isotope variant. As such, the complexity of BRAIN scales quadratically with the mass of the putative molecule, since it depends on the number of aggregated peaks that need to be calculated. In this manuscript, we suggest two improvements of the algorithm to decrease both time and memory complexity in obtaining the aggregated isotope distribution. We also illustrate a concept to represent the element isotope distribution in a generic manner. This representation allows for omitting the root calculation of the element polynomial required in the original BRAIN method. A generic formulation for the roots is of special interest for higher order element polynomials such that root finding algorithms and its inaccuracies can be avoided.
Notes: Dittwald, P (reprint author), Univ Warsaw, Coll Interfac Individual Studies Math & Nat Sci, Warsaw, Poland. piotr.dittwald@mimuw.edu.pl
Keywords: isotopic distribution; isotopic abundance’s ratios; mass spectrometry; proteomics; BRAIN algorithm
Document URI: http://hdl.handle.net/1942/16729
ISSN: 1044-0305
e-ISSN: 1879-1123
DOI: 10.1007/s13361-013-0796-5
ISI #: 000333058100010
Rights: © The Author(s), 2014. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Category: A1
Type: Journal Contribution
Validations: ecoom 2015
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
dittwald 1.pdfpublished version470.37 kBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

4
checked on Sep 3, 2020

WEB OF SCIENCETM
Citations

5
checked on May 14, 2022

Page view(s)

66
checked on May 17, 2022

Download(s)

98
checked on May 17, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.