What is she best known for?
The fields of study she is best known for:
Her primary scientific interests are in Genetics, Genome, Gene, Microsatellite and Genetic marker.
Her Genetics study typically links adjacent topics like Computational biology.
Her Computational biology research integrates issues from Comparative genomics and Transposable element.
Genome and DNA sequencing are commonly linked in her work.
Gene mapping, Genomic library, Mendelian inheritance and Polymerase chain reaction is closely connected to Genetic linkage in her research, which is encompassed under the umbrella topic of Genetic marker.
Her Whole genome sequencing research includes themes of Paleopolyploidy, Monocotyledon, Botany, Plant evolution and Gene duplication.
Her most cited work include:
- The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. (2586 citations)
- The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis (1988 citations)
- A unified classification system for eukaryotic transposable elements (1725 citations)
What are the main themes of her work throughout her whole career to date?
Michele Morgante mostly deals with Genetics, Genome, Gene, Botany and Microsatellite.
In her study, Comparative genomics is inextricably linked to Computational biology, which falls within the broad field of Genetics.
As a part of the same scientific family, Michele Morgante mostly works in the field of Genome, focusing on Genetic diversity and, on occasion, Genotyping and Genetic variability.
She interconnects Amplified fragment length polymorphism, Picea abies, DNA profiling and Restriction fragment length polymorphism, Polymerase chain reaction in the investigation of issues within Microsatellite.
The concepts of her Genetic marker study are interwoven with issues in Genetic linkage and Gene mapping.
Her Genetic variation study integrates concerns from other disciplines, such as Evolutionary biology and Linkage disequilibrium.
She most often published in these fields:
- Genetics (60.52%)
- Genome (30.90%)
- Gene (20.17%)
What were the highlights of her more recent work (between 2013-2020)?
- Genetics (60.52%)
- Botany (18.45%)
- Genome (30.90%)
In recent papers she was focusing on the following fields of study:
Genetics, Botany, Genome, Gene and Downy mildew are her primary areas of study.
Her study in Single-nucleotide polymorphism, Locus, DNA sequencing, Genetic variation and Genomics is done as part of Genetics.
Her Single-nucleotide polymorphism research is multidisciplinary, incorporating perspectives in Quantitative trait locus and Loss of heterozygosity.
Her Botany study combines topics in areas such as Phylogenetics, Plant nutrition, Bioenergy and Transcription factor.
Her study in Computational biology extends to Genome with its themes.
Her research investigates the connection with Genotyping and areas like Genetic marker which intersect with concerns in Microsatellite.
Between 2013 and 2020, her most popular works were:
- Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array (995 citations)
- Sequencing of diverse mandarin, pummelo and orange genomes reveals complex history of admixture during citrus domestication (337 citations)
- Regeneration of the entire human epidermis using transgenic stem cells. (295 citations)
In her most recent research, the most cited papers focused on:
Michele Morgante focuses on Genetics, Genome, Gene, Genetic variation and Reference genome.
Genetics is closely attributed to Genetic diversity in her study.
Her research is interdisciplinary, bridging the disciplines of DNA sequencing and Genome.
Her Transcriptome study, which is part of a larger body of work in Gene, is frequently linked to Secondary metabolism, bridging the gap between disciplines.
Her Genetic variation research focuses on subjects like Evolutionary biology, which are linked to Heterosis, Plant breeding, Family-based QTL mapping and Candidate gene.
Her Reference genome research includes elements of Annotation, GenBank, Gene Annotation, Gene prediction and Vitis vinifera.
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.
