Integration of heterogeneous functional genomics data in gerontology research to find genes and pathway underlying aging across species Article Swipe
Jason A. Bubier
,
George L. Sutphin
,
Timothy Reynolds
,
Ron Korstanje
,
Axis Fuksman-Kumpa
,
Erich J. Baker
,
Michael A. Langston
,
Elissa J. Chesler
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0214523
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0214523
Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world's population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data from functional genomics studies of aging. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and applied to several questions in genrontology using. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C. elegans ortholog, tsp-7, demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan.
Related Topics
Concepts
Genomics
Functional genomics
Model organism
Biology
Organism
Computational biology
Biological data
Genome
Population
Bioinformatics
Gene
Genetics
Medicine
Environmental health
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0214523
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214523&type=printable
- OA Status
- gold
- Cited By
- 6
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2896629548
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2896629548Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pone.0214523Digital Object Identifier
- Title
-
Integration of heterogeneous functional genomics data in gerontology research to find genes and pathway underlying aging across speciesWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-04-12Full publication date if available
- Authors
-
Jason A. Bubier, George L. Sutphin, Timothy Reynolds, Ron Korstanje, Axis Fuksman-Kumpa, Erich J. Baker, Michael A. Langston, Elissa J. CheslerList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pone.0214523Publisher landing page
- PDF URL
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214523&type=printableDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214523&type=printableDirect OA link when available
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Genomics, Functional genomics, Model organism, Biology, Organism, Computational biology, Biological data, Genome, Population, Bioinformatics, Gene, Genetics, Medicine, Environmental healthTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2025: 1, 2023: 1, 2022: 2, 2019: 2Per-year citation counts (last 5 years)
- References (count)
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54Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.results. | 138 |
| abstract_inverted_index.extending | 164 |
| abstract_inverted_index.important | 12 |
| abstract_inverted_index.including | 81 |
| abstract_inverted_index.interpret | 50 |
| abstract_inverted_index.knockdown | 150 |
| abstract_inverted_index.lifespan. | 165, 193 |
| abstract_inverted_index.ortholog, | 155 |
| abstract_inverted_index.performed | 148 |
| abstract_inverted_index.questions | 121 |
| abstract_inverted_index.GeneWeaver | 60, 169 |
| abstract_inverted_index.approaches | 37 |
| abstract_inverted_index.biological | 2, 184 |
| abstract_inverted_index.complexity | 31 |
| abstract_inverted_index.databases, | 116 |
| abstract_inverted_index.databases. | 93 |
| abstract_inverted_index.frequently | 132 |
| abstract_inverted_index.functional | 55 |
| abstract_inverted_index.healthspan | 8 |
| abstract_inverted_index.identified | 128 |
| abstract_inverted_index.mechanisms | 3 |
| abstract_inverted_index.population | 19 |
| abstract_inverted_index.processes, | 185 |
| abstract_inverted_index.proportion | 15 |
| abstract_inverted_index.discoveries | 176 |
| abstract_inverted_index.genome-wide | 96, 137 |
| abstract_inverted_index.healthspan, | 191 |
| abstract_inverted_index.integration | 66 |
| abstract_inverted_index.represented | 133 |
| abstract_inverted_index.researchers | 172 |
| abstract_inverted_index.synthesize, | 47 |
| abstract_inverted_index.associations | 179 |
| abstract_inverted_index.experimental | 83 |
| abstract_inverted_index.genrontology | 123 |
| abstract_inverted_index.increasingly | 11 |
| abstract_inverted_index.manipulation | 160 |
| abstract_inverted_index.publications | 101 |
| abstract_inverted_index.Understanding | 0 |
| abstract_inverted_index.aging-related | 136 |
| abstract_inverted_index.demonstrating | 157 |
| abstract_inverted_index.heterogeneous | 52 |
| abstract_inverted_index.investigators | 71 |
| abstract_inverted_index.publications, | 88 |
| abstract_inverted_index.aging-specific | 115 |
| abstract_inverted_index.model-organism | 113 |
| abstract_inverted_index.user-submitted | 82 |
| abstract_inverted_index.bio-gerontologists | 45 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5052749774, https://openalex.org/A5011863644, https://openalex.org/A5052536656, https://openalex.org/A5068389072, https://openalex.org/A5064932278, https://openalex.org/A5022843316, https://openalex.org/A5075996286, https://openalex.org/A5006399938 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I138006243, https://openalex.org/I157394403, https://openalex.org/I4210115256, https://openalex.org/I75027704 |
| citation_normalized_percentile.value | 0.5880558 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |