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Enregistrement W4396519698 · doi:10.1002/jez.b.23254

In the Spotlight—Established researcher

2024· article· en· W4396519698 sur OpenAlexaboutno aff
Ingo Braasch

Notice bibliographique

RevueJournal of Experimental Zoology Part B Molecular and Developmental Evolution · 2024
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueDevelopmental Biology and Gene Regulation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer sciencePsychologyData science

Résumé

récupéré en direct d'OpenAlex

Ingo is a Guest Coeditor of this special issue on Aquatic Models for Biomedical Evo-Devo. Website: https://www.fishevodevogeno.org/ Google scholar page: https://scholar.google.com/citations?user=xVw8dCAAAAAJ I studied biology at the University of Konstanz, Germany, and worked as an undergraduate on my first comparative fish genomics projects in the group of Axel Meyer with two fantastic postdocs at the time: John S. Taylor, now faculty at the University of Victoria, Canada, and Walter Salzburger, now faculty at the University of Basel, Switzerland. For my doctoral work, I joined Manfred Schartl and Jean-Nicolas Volff at the University of Würzburg, also in Germany, studying the functional genetic impacts of whole genome duplications on the evolution of vertebrate pigmentation. For my postdoc, I worked in the group of John H. Postlethwait at the University of Oregon in Eugene. John's group had just started to use spotted gar as a genomic outgroup to the teleost fishes and the teleost genome duplication. There, I began developing spotted gar as a developmental and functional genomic model system for vertebrate biology and EvoDevo – work that continues in my laboratory at Michigan State University. I grew up in provincial Germany as the son of a high school chemistry and physics teacher and a pharmaceutical technician, so I was exposed to the natural sciences early on. Starting in elementary school, I developed a passion for reading about dinosaurs and prehistoric people, years before Jurassic Park made paleontology cool. Thus, although I didn't know the term then, I had an early appreciation for macroevolution. In high school, I kept all kinds of aquarium fishes (can you ever have too many tanks?), while reading about Darwin's Voyage of the Beagle, evolution, and genetics. This fascination kept going and was a reason I chose the University of Konstanz for undergraduate studies because of its strong curricular focus on molecular biology. Working as an undergraduate researcher in the Meyer Lab and being surrounded by an international crew of world-class molecular evolutionary biologists around me – who even used fish models to answer big questions about the deep evolutionary history of vertebrates – was immensely thrilling. Comparing sequences from diverse organisms and reconstructing their evolutionary change across phylogenies, I could practically look back in time! I knew I had found my path. However, sequencing DNA and analyzing genetic information on the computer was not enough for me. Fondly remembering my childhood fish breeding projects and the beauty of watching fish embryos grow, I successively added developmental biology to my research portfolio. The name of my research group, the Fish Evo Devo Geno Lab, reflects this multipronged approach. Observing the elegance of developmental processes in many different fish species is my happy place. How could anyone ever just want to look at one research organism? Over my research career, I have worked with zebrafish, medaka, cichlids, platyfish and swordtails, killifishes, gars, bowfin, and many others, not to mention all the fish genomes we have analyzed in addition. To me, this is at the core of EvoDevo research – to be able to appreciate, work with, and sometimes unravel some mechanistic underpinnings of the “endless forms most beautiful.” And at the same time, since no single lab can keep all the model organisms or be experts in all necessary methods, comparative EvoDevo research is inherently collaborative, and, I strongly think, also particularly open-minded and mind-opening. There are clearly great times ahead of us with the incredible progress in genomics, genome editing, transgenesis, in vivo imaging, and computational advances including artificial intelligence. Mountains of correlative data need to be functionally tested in diverse research organisms to make actual causal links between genotype and phenotype – and naturally EvoDevo research will lead the charge. Because of the interdisciplinary nature of our field, you might find yourself frequently in situations – be it in graduate school, at conferences, or in the department you newly joined as faculty – in which your way of thinking, your ideas, and your research is considered outside the mainstream of any of the more specialized disciplines we aim to integrate. Make your EvoDevo research attractive to both basic research as well as to more applied and biomedical funding mechanisms. Stay confident, embrace the big picture, and trust in your abilities to see beyond the intellectual silos and blinders of individual research fields. Fortunately, with the formation of the Pan-American Society for Evolutionary Developmental Biology and the European Society for Evolutionary Developmental Biology over the past 20 years that I personally consider my intellectual homes, we now have plenty of opportunities to network within our buzzing community and jointly advocate for the EvoDevo mindset. Come join us!

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,114
Score d'incertitude au seuil0,391

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,284
Écart entre enseignants0,272 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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