MicrobIdentifier: A Microbial Identification Software Based on Mass-Spectrometry by ProQuest


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									J. Software Engineering & Applications, 2009, 2: 206-208
doi:10.4236/jsea.2009.23028 Published Online October 2009 (http://www.SciRP.org/journal/jsea)

MicrobIdentifier: A Microbial Identification Software
Based on Mass-Spectrometry
Feng LIU, Lu LI, Chi ZHANG, Lingbing WANG, Pei LI
International School of Software, Wuhan University, Wuhan, China.
Email: wolflf@126.com, {lulu.li1989, chzhcn88}@gmail.com

Received May 18th, 2009; revised July 5th, 2009; accepted July 16th, 2009.

As the technology of microbial identification by mass cataloging has been widely used, we have developed the micro-
bial identification software, MicrobIdentifier, which integrates and automates different steps in the procedure of rapid
species identification based on mass-spectrometry. This software is written in Java for cross-platform intention.

Keywords: Microbial Identification, Mass-Spectrometry

1. Introduction                                                      tion, which has N1 elements with mi standing for the ith
                                                                     element, while M’ is the mass vector of the other sample,
With the development of the technology, microbial iden-              which has N2 elements with m’j standing for the ith ele-
tification by mass cataloging has attracted considerable             ment. The discrete delta function is:
attention due to its high efficiency and automation. In
order to improve efficiency and automation of this tech-                                        1   k 0
                                                                                        (k )
nology, we’ve developed this microbial identification                                           0 otherwise
software based on the spectral coincidence function pro-
                                                                        Based on the formulas, the inner-product is greater if
posed in [1]. The software has two major functions: First,
                                                                     the two samples have more fragmentation of the same
it can be used to search for all the possible primer pairs           mass. The coincidence function normalizes the inner-pro-
among the given genes of different species, and evaluate             duct value to a range between zero and one, and a high
these primer candidates by giving each pair a score. This            value of the coincidence function indicates more similar-
is proved to be a useful reference during primer design.             ity between the two genes in comparison. Therefore, this
Second, it takes advantage of the spectral coincidence               function can be used to score the similarity in both the
function to compare mass spectrometric observables with              primer search process and the identification process.
theoretical fragmentation patterns, and further to deter-               The algorithm in primer search process is as follow:
mine the genetic affinity between the sample gene and                   1) Align all the gene sequences with ClustalW algo-
genes of known species in the d
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