Abacus: A computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis
dc.contributor.author | Fermin, Damian | en_US |
dc.contributor.author | Basrur, Venkatesha | en_US |
dc.contributor.author | Yocum, Anastasia K. | en_US |
dc.contributor.author | Nesvizhskii, Alexey I. | en_US |
dc.date.accessioned | 2011-04-07T18:52:37Z | |
dc.date.accessioned | 2011-04-07T18:52:37Z | |
dc.date.available | 2012-05-14T20:40:08Z | en_US |
dc.date.issued | 2011-04 | en_US |
dc.identifier.citation | Fermin, Damian; Basrur, Venkatesha; Yocum, Anastasia K.; Nesvizhskii, Alexey I. (2011). "Abacus: A computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis." PROTEOMICS 11(7): 1340-1345. <http://hdl.handle.net/2027.42/83477> | en_US |
dc.identifier.issn | 1615-9853 | en_US |
dc.identifier.issn | 1615-9861 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/83477 | |
dc.description.abstract | We describe Abacus, a computational tool for extracting spectral counts from MS/MS data sets. The program aggregates data from multiple experiments, adjusts spectral counts to accurately account for peptides shared across multiple proteins, and performs common normalization steps. It can also output the spectral count data at the gene level, thus simplifying the integration and comparison between gene and protein expression data. Abacus is compatible with the widely used Trans-Proteomic Pipeline suite of tools and comes with a graphical user interface making it easy to interact with the program. The main aim of Abacus is to streamline the analysis of spectral count data by providing an automated, easy to use solution for extracting this information from proteomic data sets for subsequent, more sophisticated statistical analysis. | en_US |
dc.publisher | WILEY-VCH Verlag | en_US |
dc.subject.other | Life and Medical Sciences | en_US |
dc.title | Abacus: A computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Biological Chemistry | en_US |
dc.subject.hlbsecondlevel | Chemical Engineering | en_US |
dc.subject.hlbsecondlevel | Chemistry | en_US |
dc.subject.hlbsecondlevel | Materials Science and Engineering | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Pathology, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Pathology, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Pathology, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Pathology, University of Michigan, Ann Arbor, MI, USA ; Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA ; Department of Pathology, University of Michigan, 4237 Medical Science I, Ann Arbor, MI 48109, USA Fax: +1-734-615-2500 | en_US |
dc.identifier.pmid | 21360675 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/83477/1/1340_ftp.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/83477/2/pmic_201000650_sm_SupplInfo.pdf | |
dc.identifier.doi | 10.1002/pmic.201000650 | en_US |
dc.identifier.source | PROTEOMICS | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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