Evidence map›Paper›PMID 22059886›Full record

ArticleBMC bioinformatics2011

A parallel method for enumerating amino acid compositions and masses of all theoretical peptides.

Alexey V Nefedov, Rovshan G Sadygov

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Using SEQUEST with theoretically complete sequence databases.Journal of the American Society for Mass Spectrometry · 2015
    Article
  2. Parallel computing in genomic research: advances and applications.Advances and applications in bioinformatics and chemistry : AABC · 2015
    Review
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Alexey V NefedovDepartment of Biochemistry and Molecular Biology, Sealy Center for Molecular Medicine, University of Texas Medical Branch, 301 University Blvd, Galveston, TX 77555, USA.
Rovshan G Sadygov

Funding

PHS HHS HHSN272200800048CPHS HHS NLBIHHSN268201000037C
6 · The paper itself

Abstract

backgroundEnumeration of all theoretically possible amino acid compositions is an important problem in several proteomics workflows, including peptide mass fingerprinting, mass defect labeling, mass defect filtering, and de novo peptide sequencing. Because of the high computational complexity of this task, reported methods for peptide enumeration were restricted to cover limited mass ranges (below 2 kDa). In addition, implementation details of these methods as well as their computational performance have not been provided. The increasing availability of parallel (multi-core) computers in all fields of research makes the development of parallel methods for peptide enumeration a timely topic.

resultsWe describe a parallel method for enumerating all amino acid compositions up to a given length. We present recursive procedures which are at the core of the method, and show that a single task of enumeration of all peptide compositions can be divided into smaller subtasks that can be executed in parallel. The computational complexity of the subtasks is compared with the computational complexity of the whole task. Pseudocodes of processes (a master and workers) that are used to execute the enumerating procedure in parallel are given. We present computational times for our method executed on a computer cluster with 12 Intel Xeon X5650 CPUs (72 cores) running Windows HPC Server. Our method has been implemented as a 32- and 64-bit Windows application using Microsoft Visual C++ and the Message Passing Interface. It is available for download at https://ispace.utmb.edu/users/rgsadygo/Proteomics/ParallelMethod.

conclusionWe describe implementation of a parallel method for generating mass distributions of all theoretically possible amino acid compositions.

Indexed as

Amino AcidsMolecular WeightPeptide MappingPeptidesSoftwareAmino AcidsPeptides

Identifiers

PMID22059886
PMCPMC3270061

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.