Finding Our Way through Phenotypes

Deans, Andrew R.; Lewis, Suzanna; Huala, Eva; Anzaldo, Salvatore S.; Ashburner, Michael; Balhoff, James P.; Blackburn, David C.; Blake, Judith A.; Burleigh, J. Gordon; Bruno, Claudio; Cooper, Laurel; Courtot, Mélanie; Csősz, Sándor; Cui, Hong; Dahdul, Wasila; Das, Sandip; Dececchi, T. Alexander; Dettaı̈, Agnès; Diogo, Rui; Druzinsky, Robert E.; Dumontier, Michel; Franz, Nico M.; Friedrich, Frank; Gkoutos, Georgios V.; Haendel, Melissa; Harmon, Luke J.; Hayamizu, Terry F.; He, Yongqun; Hines, Heather M.; Ibrahim, Nizar; Jackson, Leonard A.; Jaiswal, Pankaj; James-Zorn, Christina; Köhler, Sebastian; Lecointre, Guillaume; Lapp, Hilmar; Lawrence, Carolyn J.; Novère, Nicolas Le; Lundberg, John G.; Macklin, James; Mast, Austin; Midford, Peter E.; Mikó, István; Mungall, Christopher J.; Oellrich, Anika; Osumi-Sutherland, David; Parkinson, Helen; Ramı́rez, Martı́n J.; Richter, Stefan; Robinson, Peter N.; Ruttenberg, Alan; Schulz, Katja; Segerdell, Erik; Seltmann, Katja C.; Sharkey, Michael J.; Smith, Aaron D.; Smith, Barry; Specht, Chelsea D.; Squires, R. Burke; Thacker, Robert; Thessen, Anne E.; Fernandez-Triana, Jose; Vihinen, Mauno; Vize, Peter D.; Vogt, Lars; Wall, Christine E.; Walls, Ramona; Westerfeld, M.; Wharton, Robert A.; Wirkner, Christian S.; Woolley, James B.; Yoder, Matthew; Zorn, Aaron M.; Mabee, Paula M.

doi:10.1371/journal.pbio.1002033

Cited by 201 publications

(194 citation statements)

References 85 publications

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“…This is due to the fact that, regardless of how they are collected, phenotype data are inherently complex, given that they can range from populations to individual plants to specific tissues and can be recorded on comparative, discrete, or continuous scales. Because the data are essentially infinite in both diversity and scale, data documentation, integration, representation, and accessibility are critical aspects that present significant challenges (for review, see Deans et al, 2015). In order to be broadly useful, large-scale, high-dimensional data sets must be represented in such a way that data can be easily aggregated and extracted to address biologically questions.…”

Section: Kdsmart])mentioning

confidence: 99%

The quest for understanding phenotypic variation via integrated approaches in the field environment

et al. 2016

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Section: Kdsmart])mentioning

confidence: 99%

The quest for understanding phenotypic variation via integrated approaches in the field environment

et al. 2016

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“…The code and coded is getting manifested into a complex reality of interwoven coding (environment)-encoding (phenom)-decoding (genome) universe of environmentally mediated interactions. The information contents of phenome dwarves those of genome (Deans et al 2015).…”

Section: Phenotype Versus Genotypementioning

confidence: 99%

“…Hightech and high-throughput phenotyping is getting more and more available and employed in several fields of phenomics (Sozzani & Benfey 2011). The vast and diverse landscape of phenotype data need to be processed by cyber-infrastructure broadly accessible and fed by computable phenoltype descriptions based on ontology terms and entity-quality formalism; by semantically represented phenotype data; by sets of processing algorithms combining logics of ontologies with statistics (Deans et al 2015). It is the time to change how we describe biodiversity to ensure phenotype computable and linkable to digital data with semantic, extensible, and broadly accessible 12 contents (Deans et al 2012a).…”

Section: Phenotype Versus Genotypementioning

confidence: 99%

Limnephilid taxa revised by speciation traits: Rhadicoleptus, Isogamus, Melampophylax genera, Chaetopteryx rugulosa, Psilopteryx psorosa species groups, Drusus bolivari, Annitella kosciuszkii species complexes (Trichoptera: Limnephilidae)

Oláh¹,

Chvojka²,

Coppa³

et al. 2015

Opusc Zool

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Abstract. Speciation traits of paramere, paraproct and aedeagus were applied to find initial split criteria with fine structure analysis in order to prepare diverged trait matrices for delimiting phylogenetic incipient species of unsettled limnephilid taxa in the early stages of reproductive isolation. A brief history is presented how this phenotypic taxonomic tool of the speciation traits was discovered and applied in caddisfly taxonomy. The theoretical basis was elaborated for the phenotypic speciation trait by reviewing several relevant topics in the sciences of taxonomy, molecular genetics and phylogenetics. Perspectives of integrative taxonomy is discussed in context of phenotype versus genotype, immensely complex phenotype versus phenomic challenge, taxonomic impediment versus genetic expedient, taxonomic adaptation of genetic vocabulary versus genetic sophistication and virtualization, New Systematics of Huxley and Mayr versus New Taxonomy of Wheeler. Debates on magic trait, speciation phenotype, speciation trait and super traits are discussed concluding that evolution works with phenotype and why the cryptic species concept is irrelevant. Briefly summarized how speciation traits evolve in sexual selection, through accelerated reproductive isolation with genital evolution through sex-limited speciation traits, including minor sex chromosomes. Why neutral molecular markers are blind compared to the adaptive speciation traits sensitized by fine structure analysis and backed by the potential of high-tech and high-throughput phenotyping and cyber-infrastructure broadly accessible and fed by computable phenotype descriptions. What sort of genetics could really help taxonomy to describe biodiversity of the over 100 million unknown taxa? Collecting new and re-examining old type materials deposited in various collections, the following taxonomic actions were elaborated by speciation traits. Drusus bolivari new species complex has been erected with redescription of Drusus bolivari (McLachlan, 1876), with species status resurrection of D. estrellensis (McLachlan, 1884) stat. restit., with description of five new species: D. carmenae Oláh, sp. nov

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“…While semantic annotation and open access publishing are likely to become an integral part of modern scientific workflows, standardization across data sets and domains remains in its infancy [12]. We expect that the semantic annotation of TraitBank resources will long remain a work in progress.…”

Section: Implications For Interoperabilitymentioning

confidence: 99%

TraitBank: Practical semantics for organism attribute data

Parr

Schulz

Hammock

et al. 2016

Self Cite

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Abstract. Encyclopedia of Life (EOL) has developed TraitBank (http://eol.org/traitbank), a new repository for organism attribute (trait) data. TraitBank aggregates, manages and serves attribute data for organisms across the tree of life, including life history characteristics, habitats, distributions, ecological relationships and other data types. We describe how TraitBank ingests and manages these data in a way that leverages EOL's existing infrastructure and semantic annotations to facilitate reasoning across the TraitBank corpus and interoperability with other resources. We also discuss TraitBank's impact on users and collaborators and the challenges and benefits of our lightweight, scalable approach to the integration of biodiversity data.

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Finding Our Way through Phenotypes

Abstract: Imagine if we could compute across phenotype data as easily as genomic data; this article calls for efforts to realize this vision and discusses the potential benefits.

Cited by 201 publications

References 85 publications

The quest for understanding phenotypic variation via integrated approaches in the field environment

The quest for understanding phenotypic variation via integrated approaches in the field environment

Limnephilid taxa revised by speciation traits: Rhadicoleptus, Isogamus, Melampophylax genera, Chaetopteryx rugulosa, Psilopteryx psorosa species groups, Drusus bolivari, Annitella kosciuszkii species complexes (Trichoptera: Limnephilidae)

TraitBank: Practical semantics for organism attribute data

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