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Protocols

PIA specifications

Information


Unique identifier OMICS_09158
Name PIA
Alternative name Protein Inference Algorithms
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Java
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Julian Uszkoreit

Information


Unique identifier OMICS_09158
Name PIA
Alternative name Protein Inference Algorithms
Interface Web user interface
Restrictions to use None
Programming languages Java
Computer skills Basic
Stability Stable
Maintained Yes

Documentation


Maintainer


  • person_outline Julian Uszkoreit

Publication for Protein Inference Algorithms

PIA citations

 (9)
call_split

Proteomic characterization of neuromelanin granules isolated from human substantia nigra by laser microdissection

2016
Sci Rep
PMCID: 5107900
PMID: 27841354
DOI: 10.1038/srep37139
call_split See protocol

[…] ns were subsequently performed as described. To reduce false-positive identifications the false discovery rate (FDR) was set on peptide spectrum match (PSM) level to <0.01, the PSM were exported from PIA (https://github.com/mpc-bioinformatics/pia) and further processed using the “pivot table” function in Microsoft Excel, which yielded a table of the spectral counts for every peptide that belonged […]

library_books

The Exposed Proteomes of Brachyspira hyodysenteriae and B. pilosicoli

2016
Front Microbiol
PMCID: 4955376
PMID: 27493641
DOI: 10.3389/fmicb.2016.01103

[…] e and exoproteome samples were searched setting trypsin as the enzyme and allowing two missed cleavages. Peptide analyses were carried out with no enzyme set.After database search, PeptideShaker uses protein inference algorithms for protein characterization. Peptide Spectrum Matches (PSM), peptides and proteins were validated at 1% FDR estimated using the decoy hit distribution. Post-translational […]

call_split

Mutant desmin substantially perturbs mitochondrial morphology, function and maintenance in skeletal muscle tissue

2016
Acta Neuropathol
PMCID: 4992032
PMID: 27393313
DOI: 10.1007/s00401-016-1592-7
call_split See protocol

[…] ethylation of cysteine was set as fixed modification. One tryptic mis-cleavage was considered in the analysis. Confidence of peptide identification was determined using a protein inference algorithm (PIA) []. The filter cut-off for the identified peptides was set to targeted false discovery rates of <1 %.Ion intensity-based label-free quantification was performed using Progenesis LC-MS software (N […]

call_split

New insights into the protein aggregation pathology in myotilinopathy by combined proteomic and immunolocalization analyses

2016
PMCID: 4739336
PMID: 26842778
DOI: 10.1186/s40478-016-0280-0
call_split See protocol

[…] (M), phosphorylation (S, T, Y) as variable modifications. The quality of identified peptide spectrum matches was evaluated by calculating a FDR threshold of 1 % using the in-house developed software “PIA-Protein Inference Algorithm” [] (http://mpc-bioinformatics.github.io/pia/). Only peptides that were unique within the complete data set were considered for final analysis to prevent an assignment […]

library_books

Identifying novel biomarkers through data mining—A realistic scenario?

2015
Proteomics Clin Appl
PMCID: 4833187
PMID: 25347964
DOI: 10.1002/prca.201400107

[…] their publication. If this effect is not taken into consideration, differences may appear that are only caused by changing protein accessions. Additionally, analysis pipelines generally use different protein inference algorithms as well as different models for protein homologues and isoforms and potentially different false discovery rate thresholds —details that are often not reported. These diff […]

library_books

Utility of RNA seq and GPMDB Protein Observation Frequency for Improving the Sensitivity of Protein Identification by Tandem MS

2014
J Proteome Res
PMCID: 4156250
PMID: 25026199
DOI: 10.1021/pr500496p

[…] searching is comparing MS/MS spectra to peptide sequences to identify the best matching peptide for each spectrum, referred to as peptide-to-spectrum matches (PSMs). These PSMs are then processed by protein inference algorithms to produce a minimal list of proteins that would need to be present in the sample to explain the identified PSMs. The proteins in this list are also assigned a confidence […]


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PIA institution(s)
Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum, Germany

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