State of the interactomes: an evaluation of molecular networks for generating biological insights
Abstract Advancements in genomic and proteomic technologies have powered the creation of large gene and protein networks (“interactomes”) for understanding biological systems. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present...
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| Format: | Article |
| Language: | English |
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Springer Nature
2024-12-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.1038/s44320-024-00077-y |
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| author | Sarah N Wright Scott Colton Leah V Schaffer Rudolf T Pillich Christopher Churas Dexter Pratt Trey Ideker |
| author_facet | Sarah N Wright Scott Colton Leah V Schaffer Rudolf T Pillich Christopher Churas Dexter Pratt Trey Ideker |
| author_sort | Sarah N Wright |
| collection | DOAJ |
| description | Abstract Advancements in genomic and proteomic technologies have powered the creation of large gene and protein networks (“interactomes”) for understanding biological systems. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 45 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP, Reactome, and SIGNOR demonstrate stronger performance in interaction prediction. Our study provides a benchmark for interactomes across diverse biological applications and clarifies factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future. |
| format | Article |
| id | doaj-art-60484cc6ff8a4d018f49c8bac8e30f10 |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-60484cc6ff8a4d018f49c8bac8e30f102025-01-05T12:50:43ZengSpringer NatureMolecular Systems Biology1744-42922024-12-0121112910.1038/s44320-024-00077-yState of the interactomes: an evaluation of molecular networks for generating biological insightsSarah N Wright0Scott Colton1Leah V Schaffer2Rudolf T Pillich3Christopher Churas4Dexter Pratt5Trey Ideker6Department of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoDepartment of Medicine, University of California San DiegoAbstract Advancements in genomic and proteomic technologies have powered the creation of large gene and protein networks (“interactomes”) for understanding biological systems. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 45 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP, Reactome, and SIGNOR demonstrate stronger performance in interaction prediction. Our study provides a benchmark for interactomes across diverse biological applications and clarifies factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future.https://doi.org/10.1038/s44320-024-00077-yGene PrioritizationInteraction PredictionInteractomeNetworkSystems Biology |
| spellingShingle | Sarah N Wright Scott Colton Leah V Schaffer Rudolf T Pillich Christopher Churas Dexter Pratt Trey Ideker State of the interactomes: an evaluation of molecular networks for generating biological insights Molecular Systems Biology Gene Prioritization Interaction Prediction Interactome Network Systems Biology |
| title | State of the interactomes: an evaluation of molecular networks for generating biological insights |
| title_full | State of the interactomes: an evaluation of molecular networks for generating biological insights |
| title_fullStr | State of the interactomes: an evaluation of molecular networks for generating biological insights |
| title_full_unstemmed | State of the interactomes: an evaluation of molecular networks for generating biological insights |
| title_short | State of the interactomes: an evaluation of molecular networks for generating biological insights |
| title_sort | state of the interactomes an evaluation of molecular networks for generating biological insights |
| topic | Gene Prioritization Interaction Prediction Interactome Network Systems Biology |
| url | https://doi.org/10.1038/s44320-024-00077-y |
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