NDLI: Data from: Deep learning on butterfly phenotypes tests evolution's oldest mathematical model (Dataset)

Please wait, while we are loading the content...

Data from: Deep learning on butterfly phenotypes tests evolution's oldest mathematical model (Dataset)

Content Provider	Dryad
Author	Hoyal Cuthill, Jennifer F. Guttenberg, Nicholas Ledger, Sophie Crowther, Robyn Huertas, Blanca
Abstract	Traditional anatomical analyses captured only a fraction of real phenomic information. Here, we apply deep learning to quantify total phenotypic similarity across 2468 butterfly photographs, covering 38 subspecies from the polymorphic mimicry complex of Heliconius erato and Heliconius melpomene. Euclidean phenotypic distances, calculated using a deep convolutional triplet network, demonstrate significant convergence between interspecies co-mimics. This quantitatively validates a key prediction of Müllerian mimicry theory, evolutionary biology’s oldest mathematical model. Phenotypic neighbor-joining trees are significantly correlated with wing pattern gene phylogenies, demonstrating objective, phylogenetically informative phenome capture. Comparative analyses indicate frequency-dependent, mutual convergence with coevolutionary exchange of wing pattern features. Therefore, phenotypic analysis supports reciprocal coevolution, predicted by classical mimicry theory but since disputed, and reveals mutual convergence as an intrinsic generator for the surprising diversity of Müllerian mimicry. This demonstrates that deep learning can generate phenomic spatial embeddings which enable quantitative tests of evolutionary hypotheses previously only testable subjectively.
File Size	42521698
File Format	HTM / HTML
ISSN	23752548
DOI	10.5061/dryad.2hp1978
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/105939
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/105941
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/105942
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/105940
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/107610
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/107612
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/107613
Alternate Webpage(s)	https://datadryad.org/stash/downloads/file_stream/107611
Language	English
Publisher Date	2019-08-21
Access Restriction	Open
Subject Keyword	Coevolution Heliconius Erato Mimicry Heliconius Melpomene
Content Type	Text
Resource Type	Data Set
Subject	Multidisciplinary

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Data from: Wing patterning gene redefines the mimetic history of Heliconius butterflies (Dataset)

Data from: Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies (Dataset)

Data from: Butterfly genome reveals promiscuous exchange of mimicry adaptations among species (Dataset)

Data from: Transcriptome analysis reveals novel patterning and pigmentation genes underlying Heliconius butterfly wing pattern variation (Dataset)

Data from: Mimicry refinement: Phenotypic variations tracking the local optimum (Dataset)

Data from: Population genomics of parallel hybrid zones in the mimetic butterflies, H. melpomene and H. erato (Dataset)

Data from: Genomic architecture and introgression shape a butterfly radiation (Dataset)

Data from: Comparative transcriptomics provides insights into reticulate and adaptive evolution of a butterfly radiation (Dataset)

Deep learning on butterfly phenotypes tests evolution's oldest mathematical model

Data from: Deep learning on butterfly phenotypes tests evolution's oldest mathematical model (Dataset)

Similar Documents

Data from: Wing patterning gene redefines the mimetic history of Heliconius butterflies (Dataset)

Data from: Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies (Dataset)

Data from: Butterfly genome reveals promiscuous exchange of mimicry adaptations among species (Dataset)

Data from: Transcriptome analysis reveals novel patterning and pigmentation genes underlying Heliconius butterfly wing pattern variation (Dataset)

Data from: Mimicry refinement: Phenotypic variations tracking the local optimum (Dataset)

Data from: Population genomics of parallel hybrid zones in the mimetic butterflies, H. melpomene and H. erato (Dataset)

Data from: Genomic architecture and introgression shape a butterfly radiation (Dataset)

Data from: Comparative transcriptomics provides insights into reticulate and adaptive evolution of a butterfly radiation (Dataset)

Deep learning on butterfly phenotypes tests evolution's oldest mathematical model

Data from: Deep learning on butterfly phenotypes tests evolution's oldest mathematical model (Dataset)