What is he best known for?
The fields of study he is best known for:
His primary areas of study are Genetics, Ecology, Gene, Transcriptome and Genetic marker.
His studies in Genetics integrate themes in fields like Computational biology and Aquaculture.
His Computational biology research includes themes of SNP, Molecular Inversion Probe, Contig, Microsatellite enrichment and Dna genetics.
His research integrates issues of Gene flow and Population genetics in his study of Ecology.
His study in Gene is interdisciplinary in nature, drawing from both Amino acid, Superoxide dismutase and Cytochrome P450.
His Transcriptome course of study focuses on Gene expression profiling and DNA microarray.
His most cited work include:
- Strategies for microsatellite isolation: a review. (1684 citations)
- Pollutants bioavailability and toxicological risk from microplastics to marine mussels. (477 citations)
- European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation (288 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Genetics, Transcriptome, Ecology, Gene and Zoology.
His work is connected to Genome, Genomics, Genetic marker, Phylogenetic tree and Quantitative trait locus, as a part of Genetics.
His work deals with themes such as Gene expression profiling, Aquaculture, Microarray, DNA microarray and Computational biology, which intersect with Transcriptome.
The study incorporates disciplines such as Genotyping, Reference genome and Bioinformatics in addition to Computational biology.
The various areas that Luca Bargelloni examines in his Ecology study include Evolutionary biology and Introgression.
In his study, Mussel, Bioavailability and Pharmacology is inextricably linked to Mytilus, which falls within the broad field of Zoology.
He most often published in these fields:
- Genetics (24.85%)
- Transcriptome (23.64%)
- Ecology (23.64%)
What were the highlights of his more recent work (between 2017-2021)?
- Zoology (16.97%)
- Aquaculture (10.91%)
- Transcriptome (23.64%)
In recent papers he was focusing on the following fields of study:
Luca Bargelloni mainly focuses on Zoology, Aquaculture, Transcriptome, Genotyping and Selective breeding.
The concepts of his Zoology study are interwoven with issues in Mytilus, Veliger, Larva, Genetic structure and Mussel.
Luca Bargelloni interconnects Zebrafish and Genomic selection in the investigation of issues within Aquaculture.
His study on Transcriptome is covered under Gene.
His Genotyping study introduces a deeper knowledge of Genetics.
His Selective breeding research is multidisciplinary, incorporating perspectives in Genetic correlation, Sea bass, Rainbow trout, Atlantic cod and Heritability.
Between 2017 and 2021, his most popular works were:
- Applications of genotyping by sequencing in aquaculture breeding and genetics (103 citations)
- Long-term exposure of Mytilus galloprovincialis to diclofenac, Ibuprofen and Ketoprofen: Insights into bioavailability, biomarkers and transcriptomic changes. (31 citations)
- Ecotoxicological effects of the herbicide glyphosate in non-target aquatic species: Transcriptional responses in the mussel Mytilus galloprovincialis. (31 citations)
In his most recent research, the most cited papers focused on:
His primary scientific interests are in Genotyping, Mytilus, Genetics, Reference genome and Genetic association.
His research integrates issues of Zoology, Diclofenac, Bioavailability, Mussel and Lipid metabolism in his study of Mytilus.
His work carried out in the field of Zoology brings together such families of science as Glyphosate, Endoplasmic reticulum and Gene.
Genome-wide association study, Genetic variation, Heritability, Quantitative trait locus and Linkage disequilibrium are the primary areas of interest in his Genetics study.
His studies in Reference genome integrate themes in fields like SNP genotyping, Genotype, Allele frequency, Deep sequencing and Computational biology.
His Transcriptome research includes elements of Ecology, Pollutant, Metabolic pathway and Microbial population biology.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
