4.8 Article

PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics

期刊

NUCLEIC ACIDS RESEARCH
卷 49, 期 W1, 页码 W510-W515

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab368

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资金

  1. HEC [21-320SRGP/RD/HEC/2014, 20-2269/NRPU/R D/HEC/12/4792, 20-3629/NRPU/RD/HEC/14/585]
  2. Ignite [SRG-209]
  3. TWAS [RG 14-319 RG/ITC/AS C]
  4. LUMS [STG-BIO-1008, FIF-BIO-2052, FIF-BIO-0255]

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PERCEPTRON is a high-performance TDP search tool that achieves high-throughput performance by executing optimized code on GPUs in parallel. Its intuitive graphical web interface allows users to set search parameters and visualize results. Validated results demonstrate that PERCEPTRON outperforms other tools by up to 135% in reported proteins and 10-fold in runtime.
PERCEPTRON is a next-generation freely available web-based proteoform identification and characterization platform for top-down proteomics (TDP). PERCEPTRON search pipeline brings together algorithms for (i) intact protein mass tuning, (ii) de novo sequence tags-based filtering, (iii) characterization of terminal as well as post-translational modifications, (iv) identification of truncated proteoforms, (v) in silico spectral comparison, and (vi) weight-based candidate protein scoring. High-throughput performance is achieved through the execution of optimized code via multiple threads in parallel, on graphics processing units (GPUs) using NVidia Compute Unified Device Architecture (CUDA) framework. An intuitive graphical web interface allows for setting up of search parameters as well as for visualization of results. The accuracy and performance of the tool have been validated on several TDP datasets and against available TDP software. Specifically, results obtained from searching two published TDP datasets demonstrate that PERCEPTRON outperforms all other tools by up to 135% in terms of reported proteins and 10-fold in terms of runtime. In conclusion, the proposed tool significantly enhances the state-of-the-art in TDP search software and is publicly available at https://perceptron.lums.edu.pk. Users can also create in-house deployments of the tool by building code available on the GitHub repository (http://github.com/BIRL/Perceptron).

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