What is he best known for?
The fields of study he is best known for:
Fredrik Ronquist mainly investigates Bayesian probability, Bayesian inference, Markov chain Monte Carlo, Theoretical computer science and Markov chain.
His biological study spans a wide range of topics, including Character evolution, Inference and Molecular clock.
As part of the same scientific family, Fredrik Ronquist usually focuses on Character evolution, concentrating on Long branch attraction and intersecting with Phylogeography.
The Bayesian inference study combines topics in areas such as Crown group, Phylogenetics, Divergence and Phylogenetic tree.
His research integrates issues of Data mining, Polytomy and Bayes factor, Bayes' theorem in his study of Markov chain.
His work carried out in the field of Bayes' theorem brings together such families of science as Sister group, Executable, Monophyly and Source code.
His most cited work include:
- MrBayes 3: Bayesian phylogenetic inference under mixed models (22741 citations)
- MRBAYES: Bayesian inference of phylogenetic trees (17395 citations)
- MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice across a Large Model Space (12217 citations)
What are the main themes of his work throughout his whole career to date?
Fredrik Ronquist mostly deals with Evolutionary biology, Phylogenetic tree, Phylogenetics, Zoology and Bayesian probability.
His studies in Phylogenetic tree integrate themes in fields like Taxon and DNA sequencing.
The study incorporates disciplines such as Mixed model and Parasitism in addition to Phylogenetics.
His work deals with themes such as Monophyly and Molecular phylogenetics, which intersect with Zoology.
All of his Bayesian probability and Markov chain Monte Carlo, Bayesian inference, Bayes' theorem and Bayes estimator investigations are sub-components of the entire Bayesian probability study.
His Bayes' theorem research incorporates themes from Monte Carlo method, Polytomy and Data mining.
He most often published in these fields:
- Evolutionary biology (20.00%)
- Phylogenetic tree (20.00%)
- Phylogenetics (20.00%)
What were the highlights of his more recent work (between 2017-2021)?
- Probabilistic logic (6.40%)
- Biodiversity (10.40%)
- Particle filter (5.60%)
In recent papers he was focusing on the following fields of study:
Fredrik Ronquist spends much of his time researching Probabilistic logic, Biodiversity, Particle filter, Artificial intelligence and Evolutionary biology.
Fredrik Ronquist focuses mostly in the field of Probabilistic logic, narrowing it down to matters related to Phylogenetics and, in some cases, Phoridae.
His study on Evolutionary biology also encompasses disciplines like
- Host together with Clade,
- Genus which connect with Megaselia, Monophyly, Genomic signature and Gene duplication.
Fredrik Ronquist works mostly in the field of Inference, limiting it down to concerns involving Graphical model and, occasionally, Theoretical computer science and Bayes factor.
His Algorithm research is multidisciplinary, incorporating perspectives in Uniform distribution, Posterior probability and Markov chain Monte Carlo.
His Butterfly research integrates issues from Range, Null model, Phylogenetic tree and Bayesian inference.
Between 2017 and 2021, his most popular works were:
- Automated Taxonomic Identification of Insects with Expert-Level Accuracy Using Effective Feature Transfer from Convolutional Networks (40 citations)
- Establishing arthropod community composition using metabarcoding: Surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches. (23 citations)
- The Swedish Malaise Trap Project: A 15 Year Retrospective on a Countrywide Insect Inventory. (21 citations)
In his most recent research, the most cited papers focused on:
Fredrik Ronquist mainly focuses on Algorithm, Malaise trap, Sampling, Particle filter and Probabilistic logic.
His Algorithm research incorporates elements of Uniform distribution and Bayesian probability.
His Malaise trap research includes elements of Biodiversity, Environmental DNA, Fauna, Community composition and Taxonomy.
His research in Fauna intersects with topics in Mycetophilidae and Phoridae.
The concepts of his Taxonomy study are interwoven with issues in Entomology, Ichneumonidae and Species diversity.
His studies deal with areas such as Tree, Posterior probability and Markov chain Monte Carlo as well as Sampling.
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