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dc.contributor.authorBasharat, Abdul Rehman
dc.contributor.authorIman, Kanzal
dc.contributor.authorKhalid, Muhammad Farhan
dc.contributor.authorAnwar, Zohra
dc.contributor.authorHussain, Rashid
dc.contributor.authorKabir, Humnah Gohar
dc.contributor.authorTahreem, Maria
dc.contributor.authorShahid, Anam
dc.contributor.authorHumayun, Maheen
dc.contributor.authorHayat, Hira Azmat
dc.contributor.authorMustafa, Muhammad
dc.contributor.authorShoaib, Muhammad Ali
dc.contributor.authorUllah, Zakir
dc.contributor.authorZarina, Shamshad
dc.contributor.authorAhmed, Sameer
dc.contributor.authorUddin, Emad
dc.contributor.authorHamera, Sadia
dc.contributor.authorAhmad, Fayyaz
dc.contributor.authorChaudhary, Safee Ullah
dc.date.accessioned2019-08-18T12:06:02Z
dc.date.available2019-08-18T12:06:02Z
dc.date.issued2019-08-02
dc.identifier.citationBasharat, A. R., Iman, K., Khalid, M. F., Anwar, Z., Hussain, R., Kabir, H. G., … Chaudhary, S. U. (2019). SPECTRUM – A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data. Scientific Reports, 9(1). doi:10.1038/s41598-019-47724-1
dc.identifier.doi10.1038/s41598-019-47724-1
dc.identifier.urihttp://hdl.handle.net/10754/656468
dc.description.abstractTop-Down Proteomics (TDP) is an emerging proteomics protocol that involves identification, characterization, and quantitation of intact proteins using high-resolution mass spectrometry. TDP has an edge over other proteomics protocols in that it allows for: (i) accurate measurement of intact protein mass, (ii) high sequence coverage, and (iii) enhanced identification of post-translational modifications (PTMs). However, the complexity of TDP spectra poses a significant impediment to protein search and PTM characterization. Furthermore, limited software support is currently available in the form of search algorithms and pipelines. To address this need, we propose 'SPECTRUM', an open-architecture and open-source toolbox for TDP data analysis. Its salient features include: (i) MS2-based intact protein mass tuning, (ii) de novo peptide sequence tag analysis, (iii) propensity-driven PTM characterization, (iv) blind PTM search, (v) spectral comparison, (vi) identification of truncated proteins, (vii) multifactorial coefficient-weighted scoring, and (viii) intuitive graphical user interfaces to access the aforementioned functionalities and visualization of results. We have validated SPECTRUM using published datasets and benchmarked it against salient TDP tools. SPECTRUM provides significantly enhanced protein identification rates (91% to 177%) over its contemporaries. SPECTRUM has been implemented in MATLAB, and is freely available along with its source code and documentation at https://github.com/BIRL/SPECTRUM/.
dc.description.sponsorshipWe acknowledge the support provided by Osama Shiraz Shah for the fruitful discussions and suggestions during the development of the toolbox. This work was supported by HEC (21-320SRGP/R&D/HEC/2014, 20-2269/NRPU/R&D/ HEC/12/4792 and 20-3629/NRPU/R&D/HEC/14/585), Ignite (SRG-209), TWAS (RG 14-319 RG/ITC/AS_C) and LUMS (STG-BIO-1008, FIF-BIO-2052 and FIF-BIO-0255) grants.
dc.publisherSpringer Nature
dc.relation.urlhttp://www.nature.com/articles/s41598-019-47724-1
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleSPECTRUM - A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data.
dc.typeArticle
dc.contributor.departmentCompetitive Research Funds
dc.identifier.journalScientific reports
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.
dc.contributor.institutionDepartment of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.
dc.contributor.institutionLahore University of Management Sciences, Lahore, Pakistan. Correspondence and requests for materials should be addressed to S.U.C
dc.contributor.institutionNational Center for Proteomics, University of Karachi, Karachi, Pakistan.
dc.contributor.institutionDepartment of Mechanical Engineering, National University of Sciences and Technology, Islamabad, Pakistan.
dc.contributor.institutionInstitute of Life Sciences, University of Rostock, Rostock, Germany.
dc.contributor.institutionDepartment of Statistics, University of Gujrat, Gujrat, Pakistan.
kaust.personUllah, Zakir
dc.relation.issupplementedbygithub:BIRL/SPECTRUM
refterms.dateFOA2019-08-18T12:22:25Z
display.relations<b>Is Supplemented By:</b><br/> <ul><li><i>[Software]</i> <br/> Title: BIRL/SPECTRUM: A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data. Publication Date: 2019-01-21. github: <a href="https://github.com/BIRL/SPECTRUM" >BIRL/SPECTRUM</a> Handle: <a href="http://hdl.handle.net/10754/668121" >10754/668121</a></a></li></ul>
dc.date.published-online2019-08-02
dc.date.published-print2019-12


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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.