Modeling and interpretation of single-cell proteogenomic data. Article Swipe
Biological functions stem from coordinated interactions among proteins, nucleic acids and small molecules. Mass spectrometry technologies for reliable, high throughput single-cell proteomics will add a new modality to genomics and enable data-driven modeling of the molecular mechanisms coordinating proteins and nucleic acids at single-cell resolution. This promising potential requires estimating the reliability of measurements and computational analysis so that models can distinguish biological regulation from technical artifacts. We highlight different measurement modes that can support single-cell proteogenomic analysis and how to estimate their reliability. We then discuss approaches for developing both abstract and mechanistic models that aim to biologically interpret the measured differences across modalities, including specific applications to directed stem cell differentiation and to inferring protein interactions in cancer cells from the buffing of DNA copy-number variations. Single-cell proteogenomic data will support mechanistic models of direct molecular interactions that will provide generalizable and predictive representations of biological systems.
Related Topics
Concepts
Proteogenomics
Computational biology
Computer science
Proteomics
Biological data
Genomics
Biology
Bioinformatics
Genome
Biochemistry
Gene
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://pubmed.ncbi.nlm.nih.gov/37645043
- OA Status
- green
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386272431
All OpenAlex metadata
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- Title
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Modeling and interpretation of single-cell proteogenomic data.Work title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
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2023-11-04Full publication date if available
- Authors
-
Andrew Leduc, Hannah Harens, Nikolai SlavovList of authors in order
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-
https://pubmed.ncbi.nlm.nih.gov/37645043Publisher landing page
- Open access
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YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
- OA URL
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https://pmc.ncbi.nlm.nih.gov/articles/PMC10462161/pdf/nihpp-2308.07465v2.pdfDirect OA link when available
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Proteogenomics, Computational biology, Computer science, Proteomics, Biological data, Genomics, Biology, Bioinformatics, Genome, Biochemistry, GeneTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.requires | 48 |
| abstract_inverted_index.specific | 106 |
| abstract_inverted_index.systems. | 148 |
| abstract_inverted_index.different | 69 |
| abstract_inverted_index.functions | 1 |
| abstract_inverted_index.highlight | 68 |
| abstract_inverted_index.including | 105 |
| abstract_inverted_index.inferring | 115 |
| abstract_inverted_index.interpret | 99 |
| abstract_inverted_index.molecular | 35, 137 |
| abstract_inverted_index.potential | 47 |
| abstract_inverted_index.promising | 46 |
| abstract_inverted_index.proteins, | 7 |
| abstract_inverted_index.reliable, | 17 |
| abstract_inverted_index.technical | 65 |
| abstract_inverted_index.Biological | 0 |
| abstract_inverted_index.approaches | 87 |
| abstract_inverted_index.artifacts. | 66 |
| abstract_inverted_index.biological | 62, 147 |
| abstract_inverted_index.developing | 89 |
| abstract_inverted_index.estimating | 49 |
| abstract_inverted_index.mechanisms | 36 |
| abstract_inverted_index.molecules. | 12 |
| abstract_inverted_index.predictive | 144 |
| abstract_inverted_index.proteomics | 21 |
| abstract_inverted_index.regulation | 63 |
| abstract_inverted_index.throughput | 19 |
| abstract_inverted_index.Single-cell | 128 |
| abstract_inverted_index.coordinated | 4 |
| abstract_inverted_index.copy-number | 126 |
| abstract_inverted_index.data-driven | 31 |
| abstract_inverted_index.differences | 102 |
| abstract_inverted_index.distinguish | 61 |
| abstract_inverted_index.measurement | 70 |
| abstract_inverted_index.mechanistic | 93, 133 |
| abstract_inverted_index.modalities, | 104 |
| abstract_inverted_index.reliability | 51 |
| abstract_inverted_index.resolution. | 44 |
| abstract_inverted_index.single-cell | 20, 43, 75 |
| abstract_inverted_index.variations. | 127 |
| abstract_inverted_index.applications | 107 |
| abstract_inverted_index.biologically | 98 |
| abstract_inverted_index.coordinating | 37 |
| abstract_inverted_index.interactions | 5, 117, 138 |
| abstract_inverted_index.measurements | 53 |
| abstract_inverted_index.reliability. | 83 |
| abstract_inverted_index.spectrometry | 14 |
| abstract_inverted_index.technologies | 15 |
| abstract_inverted_index.computational | 55 |
| abstract_inverted_index.generalizable | 142 |
| abstract_inverted_index.proteogenomic | 76, 129 |
| abstract_inverted_index.differentiation | 112 |
| abstract_inverted_index.representations | 145 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile |