{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:29Z","timestamp":1772138069018,"version":"3.50.1"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T00:00:00Z","timestamp":1714003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Cincinnati Startup Grant","award":["CCF-2152340"],"award-info":[{"award-number":["CCF-2152340"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The rapid expansion of Bioinformatics research has led to a proliferation of computational tools for scientific analysis pipelines. However, constructing these pipelines is a demanding task, requiring extensive domain knowledge and careful consideration. As the Bioinformatics landscape evolves, researchers, both novice and expert, may feel overwhelmed in unfamiliar fields, potentially leading to the selection of unsuitable tools during workflow development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this article, we introduce the Bioinformatics Tool Recommendation system (BTR), a deep learning model designed to recommend suitable tools for a given workflow-in-progress. BTR leverages recent advances in graph neural network technology, representing the workflow as a graph to capture essential context. Natural language processing techniques enhance tool recommendations by analyzing associated tool descriptions. Experiments demonstrate that BTR outperforms the existing Galaxy tool recommendation system, showcasing its potential to streamline scientific workflow construction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The Python source code is available at https:\/\/github.com\/ryangreenj\/bioinformatics_tool_recommendation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae275","type":"journal-article","created":{"date-parts":[[2024,4,24]],"date-time":"2024-04-24T23:35:51Z","timestamp":1714001751000},"source":"Crossref","is-referenced-by-count":2,"title":["BTR: a bioinformatics tool recommendation system"],"prefix":"10.1093","volume":"40","author":[{"given":"Ryan","family":"Green","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Cincinnati , Cincinnati 45219, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xufeng","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Virginia Commonwealth University , Richmond 23284, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinze","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Virginia Commonwealth University , Richmond 23284, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9461-4251","authenticated-orcid":false,"given":"Tingting","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Connecticut , Storrs 06269, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,4,25]]},"reference":[{"key":"2024051408292867100_btae275-B1","doi-asserted-by":"crossref","first-page":"e0140829","DOI":"10.1371\/journal.pone.0140829","article-title":"Genomics virtual laboratory: a practical bioinformatics workbench for the cloud","volume":"10","author":"Afgan","year":"2015","journal-title":"PLoS One"},{"key":"2024051408292867100_btae275-B2","doi-asserted-by":"crossref","first-page":"W537","DOI":"10.1093\/nar\/gky379","article-title":"The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update","volume":"46","author":"Afgan","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2024051408292867100_btae275-B3","year":"2016"},{"key":"2024051408292867100_btae275-B4","first-page":"103","author":"Cho","year":"2014"},{"key":"2024051408292867100_btae275-B5","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1145\/3486897","article-title":"Methods included: standardizing computational reuse and portability with the common workflow language","volume":"65","author":"Crusoe","year":"2022","journal-title":"Commun ACM"},{"key":"2024051408292867100_btae275-B6","first-page":"4171","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019","author":"Devlin","year":"2019"},{"key":"2024051408292867100_btae275-B33","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1038\/nbt.3820","article-title":"Nextflow enables reproducible computational workflows","volume":"35","author":"Di Tommaso","year":"2017","journal-title":"Nat Biotechnol"},{"key":"2024051408292867100_btae275-B7","volume-title":"ICLR Workshop on Representation Learning on Graphs and Manifolds.","author":"Fey","year":"2019"},{"key":"2024051408292867100_btae275-B8","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1080\/0952813X.2010.490962","article-title":"A semantic framework for automatic generation of computational workflows using distributed data and component catalogs","volume":"23","author":"Gil","year":"2011","journal-title":"J Exp Theor Artif Intell"},{"key":"2024051408292867100_btae275-B9","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MIS.2010.9","article-title":"Wings: intelligent workflow-based design of computational experiments","volume":"26","author":"Gil","year":"2011","journal-title":"IEEE Intell Syst"},{"key":"2024051408292867100_btae275-B10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3458754","article-title":"Domain-specific language model pretraining for biomedical natural language processing","volume":"3","author":"Gu","year":"2021","journal-title":"ACM Trans Comput Healthcare"},{"key":"2024051408292867100_btae275-B11","first-page":"1","article-title":"Graph representation learning","volume":"14","author":"Hamilton","year":"2020","journal-title":"Synth Lect Artif Intell Mach Learn"},{"key":"2024051408292867100_btae275-B12","author":"Hidasi"},{"key":"2024051408292867100_btae275-B13","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1093\/bioinformatics\/btt113","article-title":"EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats","volume":"29","author":"Ison","year":"2013","journal-title":"Bioinformatics"},{"key":"2024051408292867100_btae275-B14","doi-asserted-by":"crossref","first-page":"D38","DOI":"10.1093\/nar\/gkv1116","article-title":"Tools and data services registry: a community effort to document bioinformatics resources","volume":"44","author":"Ison","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2024051408292867100_btae275-B15","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1007\/978-3-030-50436-6_34","volume-title":"Computational Science \u2013 ICCS 2020","author":"Kasalica","year":"2020"},{"key":"2024051408292867100_btae275-B16","volume-title":"3rd International Conference on Learning Representations, ICLR 2015","author":"Kingma","year":"2015"},{"key":"2024051408292867100_btae275-B17","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"Imagenet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun ACM"},{"key":"2024051408292867100_btae275-B18","doi-asserted-by":"crossref","first-page":"giaa152","DOI":"10.1093\/gigascience\/giaa152","article-title":"Tool recommender system in galaxy using deep learning","volume":"10","author":"Kumar","year":"2021","journal-title":"Gigascience"},{"key":"2024051408292867100_btae275-B19","first-page":"1419","author":"Li","year":"2017"},{"key":"2024051408292867100_btae275-B20","volume-title":"4th International Conference on Learning Representations, ICLR 2016","author":"&gt;Li","year":"2016"},{"key":"2024051408292867100_btae275-B21","doi-asserted-by":"crossref","first-page":"e1011319","DOI":"10.1371\/journal.pcbi.1011319","article-title":"Ten quick tips for harnessing the power of chatgpt in computational biology","volume":"19","author":"Lubiana","year":"2023","journal-title":"PLoS Comput Biol"},{"key":"2024051408292867100_btae275-B22","first-page":"2291","author":"Ma","year":"2020"},{"key":"2024051408292867100_btae275-B23","first-page":"2","article-title":"Docker: lightweight linux containers for consistent development and deployment","volume":"239","author":"Merkel","year":"2014","journal-title":"Linux J"},{"key":"2024051408292867100_btae275-B24","doi-asserted-by":"crossref","first-page":"33","DOI":"10.12688\/f1000research.29032.2","article-title":"Sustainable data analysis with snakemake","volume":"10","author":"M\u00f6lder","year":"2021","journal-title":"F1000Res"},{"key":"2024051408292867100_btae275-B25","first-page":"349","article-title":"A focused backpropagation algorithm for temporal pattern recognition","volume":"3","author":"Mozer","year":"1995","journal-title":"Complex Systems"},{"key":"2024051408292867100_btae275-B26","author":"OpenAI"},{"key":"2024051408292867100_btae275-B27","first-page":"8024","author":"Paszke","year":"2019"},{"key":"2024051408292867100_btae275-B28","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1093\/bioinformatics\/btq033","article-title":"BEDTools: a flexible suite of utilities for comparing genomic features","volume":"26","author":"Quinlan","year":"2010","journal-title":"Bioinformatics"},{"key":"2024051408292867100_btae275-B29","author":"Reimers"},{"key":"2024051408292867100_btae275-B30","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","article-title":"The graph neural network model","volume":"20","author":"Scarselli","year":"2009","journal-title":"IEEE Trans Neural Netw"},{"key":"2024051408292867100_btae275-B31","doi-asserted-by":"crossref","first-page":"105","DOI":"10.15302\/J-QB-023-0327","article-title":"Empowering beginners in bioinformatics with chatgpt","volume":"11","author":"Shue","year":"2023","journal-title":"Quant Biol"},{"key":"2024051408292867100_btae275-B32","doi-asserted-by":"crossref","first-page":"W345","DOI":"10.1093\/nar\/gkac247","article-title":"The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update","volume":"50","author":"The Galaxy Community","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"2024051408292867100_btae275-B34","author":"Vaswani","year":"2017"},{"key":"2024051408292867100_btae275-B35","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1038\/s41592-021-01254-9","article-title":"Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers","volume":"18","author":"Wratten","year":"2021","journal-title":"Nat Methods"},{"key":"2024051408292867100_btae275-B36","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1609\/aaai.v33i01.3301346","article-title":"Session-based recommendation with graph neural networks","volume":"33","author":"Wu","year":"2019","journal-title":"AAAI"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae275\/57334065\/btae275.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae275\/57572745\/btae275.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae275\/57572745\/btae275.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T04:44:54Z","timestamp":1715661894000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btae275\/7658303"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2024,4,25]]},"references-count":36,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btae275","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.10.13.562252","asserted-by":"object"}]},"ISSN":["1367-4811"],"issn-type":[{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,5,1]]},"published":{"date-parts":[[2024,4,25]]},"article-number":"btae275"}}