Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Efficient Algorithm for Clustering of Large-Scale Mass Spectrometry
  Data   High-throughput spectrometers are capable of producing data sets containing
thousands of spectra for a single biological sample. These data sets contain a
substantial amount of redundancy from peptides that may get selected multiple
times in a LC-MS/MS experiment. In this paper, we present an efficient
algorithm, CAMS (Clustering Algorithm for Mass Spectra) for clustering mass
spectrometry data which increases both the sensitivity and confidence of
spectral assignment. CAMS utilizes a novel metric, called F-set, that allows
accurate identification of the spectra that are similar. A graph theoretic
framework is defined that allows the use of F-set metric efficiently for
accurate cluster identifications. The accuracy of the algorithm is tested on
real HCD and CID data sets with varying amounts of peptides. Our experiments
show that the proposed algorithm is able to cluster spectra with very high
accuracy in a reasonable amount of time for large spectral data sets. Thus, the
algorithm is able to decrease the computational time by compressing the data
sets while increasing the throughput of the data by interpreting low S/N
spectra.

26
The categories of this paper are: bayes-an
18
The categories of this paper are: econ
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom