Using published pathway figures in enrichment analysis and machine learning
Abstract Pathway Figure OCR (PFOCR) is a novel kind of pathway database approaching the breadth and depth of Gene Ontology while providing rich, mechanistic diagrams and direct literature support. Here, we highlight the utility of PFOCR in disease research in comparison with popular pathway database...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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BMC
2023-11-01
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| Series: | BMC Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12864-023-09816-1 |
| _version_ | 1797453726880890880 |
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| author | Min-Gyoung Shin Alexander R. Pico |
| author_facet | Min-Gyoung Shin Alexander R. Pico |
| author_sort | Min-Gyoung Shin |
| collection | DOAJ |
| description | Abstract Pathway Figure OCR (PFOCR) is a novel kind of pathway database approaching the breadth and depth of Gene Ontology while providing rich, mechanistic diagrams and direct literature support. Here, we highlight the utility of PFOCR in disease research in comparison with popular pathway databases through an assessment of disease coverage and analytical applications. In addition to common pathway analysis use cases, we present two advanced case studies demonstrating unique advantages of PFOCR in terms of cancer subtype and grade prediction analyses. |
| first_indexed | 2024-03-09T15:27:01Z |
| format | Article |
| id | doaj.art-2a32d59966b440feb6469bc17b297e39 |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-03-09T15:27:01Z |
| publishDate | 2023-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genomics |
| spelling | doaj.art-2a32d59966b440feb6469bc17b297e392023-11-26T12:26:22ZengBMCBMC Genomics1471-21642023-11-0124111310.1186/s12864-023-09816-1Using published pathway figures in enrichment analysis and machine learningMin-Gyoung Shin0Alexander R. Pico1Institute of Data Science and Biotechnology, Gladstone InstitutesInstitute of Data Science and Biotechnology, Gladstone InstitutesAbstract Pathway Figure OCR (PFOCR) is a novel kind of pathway database approaching the breadth and depth of Gene Ontology while providing rich, mechanistic diagrams and direct literature support. Here, we highlight the utility of PFOCR in disease research in comparison with popular pathway databases through an assessment of disease coverage and analytical applications. In addition to common pathway analysis use cases, we present two advanced case studies demonstrating unique advantages of PFOCR in terms of cancer subtype and grade prediction analyses.https://doi.org/10.1186/s12864-023-09816-1Pathway databaseDatabase comparisonEnrichment analysisMachine learningDisease mechanism |
| spellingShingle | Min-Gyoung Shin Alexander R. Pico Using published pathway figures in enrichment analysis and machine learning BMC Genomics Pathway database Database comparison Enrichment analysis Machine learning Disease mechanism |
| title | Using published pathway figures in enrichment analysis and machine learning |
| title_full | Using published pathway figures in enrichment analysis and machine learning |
| title_fullStr | Using published pathway figures in enrichment analysis and machine learning |
| title_full_unstemmed | Using published pathway figures in enrichment analysis and machine learning |
| title_short | Using published pathway figures in enrichment analysis and machine learning |
| title_sort | using published pathway figures in enrichment analysis and machine learning |
| topic | Pathway database Database comparison Enrichment analysis Machine learning Disease mechanism |
| url | https://doi.org/10.1186/s12864-023-09816-1 |
| work_keys_str_mv | AT mingyoungshin usingpublishedpathwayfiguresinenrichmentanalysisandmachinelearning AT alexanderrpico usingpublishedpathwayfiguresinenrichmentanalysisandmachinelearning |