KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysis Article Swipe
Pengyi Yang
,
Ellis Patrick
,
Sean J. Humphrey
,
Shila Ghazanfar
,
David E. James
,
Raja Jothi
,
Jean Yang
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1002/pmic.201600068
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1002/pmic.201600068
Mass spectrometry (MS)‐based quantitative phosphoproteomics has become a key approach for proteome‐wide profiling of phosphorylation in tissues and cells. Traditional experimental design often compares a single treatment with a control, whereas increasingly more experiments are designed to compare multiple treatments with respect to a control. To this end, the development of bioinformatic tools that can integrate multiple treatments and visualise kinases and substrates under combinatorial perturbations is vital for dissecting concordant and/or independent effects of each treatment. Here, we propose a hypothesis driven kinase perturbation analysis (KinasePA) to annotate and visualise kinases and their substrates that are perturbed by various combinatorial effects of treatments in phosphoproteomics experiments. We demonstrate the utility of KinasePA through its application to two large‐scale phosphoproteomics datasets and show its effectiveness in dissecting kinases and substrates within signalling pathways driven by unique combinations of cellular stimuli and inhibitors. We implemented and incorporated KinasePA as part of the “directPA” R package available from the comprehensive R archive network (CRAN). Furthermore, KinasePA also has an interactive web interface that can be readily applied to annotate user provided phosphoproteomics data ( http://kinasepa.pengyiyang.org ).
Related Topics
Concepts
Phosphoproteomics
Computational biology
Kinase
Proteome
Computer science
Proteomics
Profiling (computer programming)
Biology
Systems biology
Phosphorylation
Bioinformatics
Cell biology
Protein phosphorylation
Biochemistry
Protein kinase A
Operating system
Gene
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/pmic.201600068
- OA Status
- green
- Cited By
- 36
- References
- 11
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2346694641
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2346694641Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/pmic.201600068Digital Object Identifier
- Title
-
KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-05-05Full publication date if available
- Authors
-
Pengyi Yang, Ellis Patrick, Sean J. Humphrey, Shila Ghazanfar, David E. James, Raja Jothi, Jean YangList of authors in order
- Landing page
-
https://doi.org/10.1002/pmic.201600068Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1002/pmic.201600068Direct OA link when available
- Concepts
-
Phosphoproteomics, Computational biology, Kinase, Proteome, Computer science, Proteomics, Profiling (computer programming), Biology, Systems biology, Phosphorylation, Bioinformatics, Cell biology, Protein phosphorylation, Biochemistry, Protein kinase A, Operating system, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
36Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 5, 2023: 4, 2022: 8, 2021: 6Per-year citation counts (last 5 years)
- References (count)
-
11Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.unique | 135 |
| abstract_inverted_index.within | 130 |
| abstract_inverted_index.(CRAN). | 161 |
| abstract_inverted_index.applied | 174 |
| abstract_inverted_index.archive | 159 |
| abstract_inverted_index.compare | 37 |
| abstract_inverted_index.effects | 73, 101 |
| abstract_inverted_index.kinases | 60, 91, 127 |
| abstract_inverted_index.network | 160 |
| abstract_inverted_index.package | 153 |
| abstract_inverted_index.propose | 79 |
| abstract_inverted_index.readily | 173 |
| abstract_inverted_index.respect | 41 |
| abstract_inverted_index.stimuli | 139 |
| abstract_inverted_index.through | 113 |
| abstract_inverted_index.tissues | 16 |
| abstract_inverted_index.utility | 110 |
| abstract_inverted_index.various | 99 |
| abstract_inverted_index.whereas | 30 |
| abstract_inverted_index.KinasePA | 112, 146, 163 |
| abstract_inverted_index.analysis | 85 |
| abstract_inverted_index.annotate | 88, 176 |
| abstract_inverted_index.approach | 9 |
| abstract_inverted_index.cellular | 138 |
| abstract_inverted_index.compares | 23 |
| abstract_inverted_index.control, | 29 |
| abstract_inverted_index.control. | 44 |
| abstract_inverted_index.datasets | 120 |
| abstract_inverted_index.designed | 35 |
| abstract_inverted_index.multiple | 38, 56 |
| abstract_inverted_index.pathways | 132 |
| abstract_inverted_index.provided | 178 |
| abstract_inverted_index.available | 154 |
| abstract_inverted_index.integrate | 55 |
| abstract_inverted_index.interface | 169 |
| abstract_inverted_index.perturbed | 97 |
| abstract_inverted_index.profiling | 12 |
| abstract_inverted_index.treatment | 26 |
| abstract_inverted_index.visualise | 59, 90 |
| abstract_inverted_index.(KinasePA) | 86 |
| abstract_inverted_index.concordant | 70 |
| abstract_inverted_index.dissecting | 69, 126 |
| abstract_inverted_index.hypothesis | 81 |
| abstract_inverted_index.signalling | 131 |
| abstract_inverted_index.substrates | 62, 94, 129 |
| abstract_inverted_index.treatment. | 76 |
| abstract_inverted_index.treatments | 39, 57, 103 |
| abstract_inverted_index.Traditional | 19 |
| abstract_inverted_index.application | 115 |
| abstract_inverted_index.demonstrate | 108 |
| abstract_inverted_index.development | 49 |
| abstract_inverted_index.experiments | 33 |
| abstract_inverted_index.implemented | 143 |
| abstract_inverted_index.independent | 72 |
| abstract_inverted_index.inhibitors. | 141 |
| abstract_inverted_index.interactive | 167 |
| abstract_inverted_index.(MS)‐based | 2 |
| abstract_inverted_index.Furthermore, | 162 |
| abstract_inverted_index.combinations | 136 |
| abstract_inverted_index.experimental | 20 |
| abstract_inverted_index.experiments. | 106 |
| abstract_inverted_index.incorporated | 145 |
| abstract_inverted_index.increasingly | 31 |
| abstract_inverted_index.perturbation | 84 |
| abstract_inverted_index.quantitative | 3 |
| abstract_inverted_index.spectrometry | 1 |
| abstract_inverted_index.bioinformatic | 51 |
| abstract_inverted_index.combinatorial | 64, 100 |
| abstract_inverted_index.comprehensive | 157 |
| abstract_inverted_index.effectiveness | 124 |
| abstract_inverted_index.large‐scale | 118 |
| abstract_inverted_index.perturbations | 65 |
| abstract_inverted_index.“directPA” | 151 |
| abstract_inverted_index.phosphorylation | 14 |
| abstract_inverted_index.proteome‐wide | 11 |
| abstract_inverted_index.phosphoproteomics | 4, 105, 119, 179 |
| abstract_inverted_index.http://kinasepa.pengyiyang.org | 182 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5028524705 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I129604602 |
| citation_normalized_percentile.value | 0.82075993 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |