What is he best known for?
The fields of study he is best known for:
David W. Ussery mostly deals with Genetics, Genome, Gene, Genomics and Comparative genomics.
His research ties Computational biology and Genetics together.
His Genome study combines topics in areas such as Phylogenetics, Multilocus sequence typing and DNA sequencing.
His work on Escherichia coli, Chromatin and Promoter as part of general Gene research is frequently linked to Azorhizobium caulinodans, thereby connecting diverse disciplines of science.
His Genomics research is multidisciplinary, incorporating elements of Evolutionary biology, Data science and Metagenomics.
His Gene prediction research is multidisciplinary, incorporating perspectives in Minimal genome and Intron.
His most cited work include:
- RNAmmer: consistent and rapid annotation of ribosomal RNA genes (3810 citations)
- The genome sequence of Schizosaccharomyces pombe (1415 citations)
- Multilocus Sequence Typing of Total-Genome-Sequenced Bacteria (1016 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Genome, Genetics, Computational biology, Gene and Comparative genomics.
His research brings together the fields of Phylogenetic tree and Genome.
His Genetics study frequently draws connections to other fields, such as Microbiology.
David W. Ussery has researched Computational biology in several fields, including Bioinformatics, RNA, Nanopore sequencing, Taxonomy and Pan-genome.
Multilocus sequence typing, Virulence, Gene family, Transcription and Sequence analysis are the primary areas of interest in his Gene study.
The study incorporates disciplines such as Evolutionary biology and Metagenomics in addition to Genomics.
He most often published in these fields:
- Genome (68.87%)
- Genetics (59.14%)
- Computational biology (33.46%)
What were the highlights of his more recent work (between 2015-2021)?
- Genome (68.87%)
- Computational biology (33.46%)
- Gene (30.35%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Genome, Computational biology, Gene, Genetics and Nanopore sequencing.
The concepts of his Genome study are interwoven with issues in Enterococcus faecium, Virology and Phylogenetic tree.
His Computational biology study combines topics from a wide range of disciplines, such as Gut flora, RNA, Transcriptome, Virus classification and GenBank.
His study on Protein family, Strain and Metagenomics is often connected to Clostridium difficile toxin A as part of broader study in Gene.
His is doing research in Plasmid, Comparative genomics, Pseudomonas chlororaphis, Phylogenetics and Phylogenetic diversity, both of which are found in Genetics.
The Nanopore sequencing study combines topics in areas such as Mutation, Glioma, Temozolomide and 2019-20 coronavirus outbreak.
Between 2015 and 2021, his most popular works were:
- Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D (70 citations)
- Global Genomic Epidemiology of Salmonella enterica Serovar Typhimurium DT104. (58 citations)
- Global Genomic Epidemiology of Salmonella enterica Serovar Typhimurium DT104. (58 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Genome, Computational biology, Genetics, Phylogenetic tree and RNA.
His work carried out in the field of Genome brings together such families of science as Lineage, Pseudomonas fluorescens, Pregnancy, Pseudomonas putida and Pseudomonas.
His work deals with themes such as GenBank, Taxonomy and Genomics, which intersect with Computational biology.
The study of Genetics is intertwined with the study of Serotype in a number of ways.
His Phylogenetic tree study incorporates themes from Virology, Genotype and Bioinformatics.
His study on RNA also encompasses disciplines like
- Nanopore sequencing together with Subgenomic mRNA, Single-Stranded RNA, Illumina dye sequencing and Sequence assembly,
- Messenger RNA that intertwine with fields like Ribosomal RNA, DNA and Epitranscriptomics.
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