Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps
In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze conn...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2025
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| Online Access: | https://hdl.handle.net/10356/182064 |
| _version_ | 1824454161470586880 |
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| author | Arulprakasam, Karthick Raja Toh, Janelle Wing Shan Foo, Herman Kumar, Mani R. Kutevska, An-Nikol Davey, Emilia Emmanuelle Mutwil, Marek Thibault, Guillaume |
| author2 | School of Biological Sciences |
| author_facet | School of Biological Sciences Arulprakasam, Karthick Raja Toh, Janelle Wing Shan Foo, Herman Kumar, Mani R. Kutevska, An-Nikol Davey, Emilia Emmanuelle Mutwil, Marek Thibault, Guillaume |
| author_sort | Arulprakasam, Karthick Raja |
| collection | NTU |
| description | In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze connectivity information from the full-texts and abstracts of 24,237 and 150,538 research publications concerning Caenorhabditis elegans and Drosophila melanogaster, respectively. This approach has effectively identified 200,219 and 1,194,587 interactions within the C. elegans and Drosophila biomaps, respectively. Utilizing Cytoscape Web, we have developed a searchable online biomaps that link relevant keywords to their corresponding PubMed IDs, thus providing seamless access to an extensive knowledge network encompassing C. elegans and Drosophila. Our work highlights the transformative potential of integrating artificial intelligence with bioinformatics to deepen our understanding of complex biological systems. By revealing the intricate web of relationships among key entities in C. elegans and Drosophila, we offer invaluable insights that promise to propel advancements in genetics, developmental biology, neuroscience, longevity, and beyond. We also provide details and discuss significant nodes within both biomaps, including the insulin/IGF-1 signaling (IIS) and the notch pathways. Our innovative methodology sets a robust foundation for future research aimed at unravelling complex biological networks across diverse organisms. The two databases are available at worm.bio-map.com and drosophila.bio-map.com. |
| first_indexed | 2025-02-19T03:17:55Z |
| format | Journal Article |
| id | ntu-10356/182064 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:17:55Z |
| publishDate | 2025 |
| record_format | dspace |
| spelling | ntu-10356/1820642025-01-13T15:32:32Z Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps Arulprakasam, Karthick Raja Toh, Janelle Wing Shan Foo, Herman Kumar, Mani R. Kutevska, An-Nikol Davey, Emilia Emmanuelle Mutwil, Marek Thibault, Guillaume School of Biological Sciences Mechanobiology Institute, NUS Medicine, Health and Life Sciences Genetic interactions Text mining In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze connectivity information from the full-texts and abstracts of 24,237 and 150,538 research publications concerning Caenorhabditis elegans and Drosophila melanogaster, respectively. This approach has effectively identified 200,219 and 1,194,587 interactions within the C. elegans and Drosophila biomaps, respectively. Utilizing Cytoscape Web, we have developed a searchable online biomaps that link relevant keywords to their corresponding PubMed IDs, thus providing seamless access to an extensive knowledge network encompassing C. elegans and Drosophila. Our work highlights the transformative potential of integrating artificial intelligence with bioinformatics to deepen our understanding of complex biological systems. By revealing the intricate web of relationships among key entities in C. elegans and Drosophila, we offer invaluable insights that promise to propel advancements in genetics, developmental biology, neuroscience, longevity, and beyond. We also provide details and discuss significant nodes within both biomaps, including the insulin/IGF-1 signaling (IIS) and the notch pathways. Our innovative methodology sets a robust foundation for future research aimed at unravelling complex biological networks across diverse organisms. The two databases are available at worm.bio-map.com and drosophila.bio-map.com. Ministry of Education (MOE) Published version This work was supported by funds from the Singapore Ministry of Education Academic Research Fund Tier 1 (RG96/22 to G.T.) and Tier 3 (MOET32022-0002 to M.M.) as well as the Research Scholarship to K.R.A [predoctoral fellowship from Singapore Ministry of Education Academic Research Fund Tier 3 (MOE-MOET32020-0001)]. 2025-01-07T01:13:21Z 2025-01-07T01:13:21Z 2024 Journal Article Arulprakasam, K. R., Toh, J. W. S., Foo, H., Kumar, M. R., Kutevska, A., Davey, E. E., Mutwil, M. & Thibault, G. (2024). Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps. BMC Genomics, 25(1), 1080-. https://dx.doi.org/10.1186/s12864-024-10997-6 1471-2164 https://hdl.handle.net/10356/182064 10.1186/s12864-024-10997-6 39538127 2-s2.0-85209171186 1 25 1080 en RG96/22 MOET32022-0002 MOE-MOET32020-0001 BMC Genomics © 2024 The Author(s). Open Access. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creati vecommons.org/licenses/by-nc-nd/4.0/. application/pdf |
| spellingShingle | Medicine, Health and Life Sciences Genetic interactions Text mining Arulprakasam, Karthick Raja Toh, Janelle Wing Shan Foo, Herman Kumar, Mani R. Kutevska, An-Nikol Davey, Emilia Emmanuelle Mutwil, Marek Thibault, Guillaume Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title | Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title_full | Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title_fullStr | Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title_full_unstemmed | Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title_short | Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps |
| title_sort | harnessing full text publications for deep insights into c elegans and drosophila biomaps |
| topic | Medicine, Health and Life Sciences Genetic interactions Text mining |
| url | https://hdl.handle.net/10356/182064 |
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