Machine Learning models identify gene predictors of waggle dance behaviour in honeybees
| dc.contributor.author | Veiner, Marcell | |
| dc.contributor.author | Morimoto Borges, Juliano | |
| dc.contributor.author | Leadbeater, Ellouise | |
| dc.contributor.author | Manfredini, Fabio | |
| dc.contributor.institution | University of Aberdeen.Biological Sciences | en |
| dc.date.accessioned | 2022-07-04T15:36:01Z | |
| dc.date.available | 2022-07-04T15:36:01Z | |
| dc.date.issued | 2022-08-01 | |
| dc.description | We thank Dr Georgios Leontidis (The School of Natural and Computing Science, University of Aberdeen) for his valuable support during the selection and implementation of the ML models, and the two anonymous reviewers for providing useful feedback that helped improve the clarity and soundness of the manuscript. We are also grateful to NERC (Natural Environment Research Council) for funding this project and supporting MV’s salary over 10 weeks through their Research Experience Placement programme (DTG reference: NE/S007377/1). The honeybee work that was performed to obtain the sequencing data used in this study was funded by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. 638873 to EL). This funding also supported FM during the execution of the field and molecular work. | en |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 1029317 | |
| dc.identifier | 214914822 | |
| dc.identifier | 397ce1ff-c7bc-41ab-9246-f7fe85c0d9d2 | |
| dc.identifier | 35334147 | |
| dc.identifier | 85128281497 | |
| dc.identifier.citation | Veiner, M, Morimoto Borges, J, Leadbeater, E & Manfredini, F 2022, 'Machine Learning models identify gene predictors of waggle dance behaviour in honeybees', Molecular Ecology Resources, vol. 22, no. 6, 14, pp. 2248-2261. https://doi.org/10.1111/1755-0998.13611 | en |
| dc.identifier.doi | 10.1111/1755-0998.13611 | |
| dc.identifier.iss | 6 | en |
| dc.identifier.issn | 1755-098X | |
| dc.identifier.uri | https://hdl.handle.net/2164/18780 | |
| dc.identifier.vol | 22 | en |
| dc.language.iso | eng | |
| dc.relation.ispartof | Molecular Ecology Resources | en |
| dc.subject | bioinfomatics | en |
| dc.subject | feature selection | en |
| dc.subject | genomics | en |
| dc.subject | gene structure and function | en |
| dc.subject | insects | en |
| dc.subject | social evolution | en |
| dc.subject | QH301 Biology | en |
| dc.subject | Natural Environment Research Council (NERC) | en |
| dc.subject | NE/S007377/1 | en |
| dc.subject | European Commission | en |
| dc.subject | 638873 | en |
| dc.subject | Supplementary Data | en |
| dc.subject | Supplementary Information | en |
| dc.subject.lcc | QH301 | en |
| dc.title | Machine Learning models identify gene predictors of waggle dance behaviour in honeybees | en |
| dc.type | Journal article | en |
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