What is he best known for?
The fields of study he is best known for:
His primary areas of investigation include Genetics, Computational biology, Gene, Drosophila melanogaster and Controlled vocabulary.
His studies in Computational biology integrate themes in fields like Ontology, Genome project, In situ hybridization, Gene expression profiling and OBO Foundry.
His work carried out in the field of OBO Foundry brings together such families of science as Ontology-based data integration and Open Biomedical Ontologies.
His Open Biomedical Ontologies study incorporates themes from Basic Formal Ontology and Ontology for Biomedical Investigations.
His Drosophila melanogaster research includes elements of Fungal protein and Biogeography.
His biological study spans a wide range of topics, including Annotation and Bioinformatics.
His most cited work include:
- Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. (26033 citations)
- A Laboratory manual (7428 citations)
- The genome sequence of Drosophila melanogaster (5233 citations)
What are the main themes of his work throughout his whole career to date?
Michael Ashburner mostly deals with Genetics, Drosophila melanogaster, Gene, Genome and Drosophila.
His research on Genetics frequently connects to adjacent areas such as Computational biology.
His work carried out in the field of Computational biology brings together such families of science as Ontology, Annotation, ENCODE, Genomics and Controlled vocabulary.
His studies deal with areas such as Molecular biology and Mutant as well as Drosophila melanogaster.
Michael Ashburner works mostly in the field of Genome, limiting it down to topics relating to Data science and, in certain cases, Bioinformatics, as a part of the same area of interest.
His work is dedicated to discovering how Melanogaster, Salivary gland are connected with Endocrinology and Secretion and other disciplines.
He most often published in these fields:
- Genetics (56.90%)
- Drosophila melanogaster (40.52%)
- Gene (30.17%)
What were the highlights of his more recent work (between 2004-2015)?
- Genetics (56.90%)
- Computational biology (16.38%)
- Genome (19.40%)
In recent papers he was focusing on the following fields of study:
His main research concerns Genetics, Computational biology, Genome, Ontology and Genomics.
His study in Phenotype, Model organism, Drosophila melanogaster, Drosophila and Chromosomal inversion falls under the purview of Genetics.
Michael Ashburner has researched Computational biology in several fields, including Controlled vocabulary, Genome project, Data warehouse and Annotation.
In general Genome study, his work on Whole genome sequencing, Reference genome, DNA Transposable Elements and Transposable element often relates to the realm of Standardization, thereby connecting several areas of interest.
The study incorporates disciplines such as Zebrafish Information Network genome database, Human Phenotype Ontology and OBO Foundry in addition to Ontology.
His study focuses on the intersection of Open Biomedical Ontologies and fields such as IDEF5 with connections in the field of Biological Ontologies.
Between 2004 and 2015, his most popular works were:
- The OBO Foundry : coordinated evolution of ontologies to support biomedical data integration (1945 citations)
- The minimum information about a genome sequence (MIGS) specification. (986 citations)
- The bacterial symbiont Wolbachia induces resistance to RNA viral infections in Drosophila melanogaster. (867 citations)
In his most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Computational biology, Genomics, Controlled vocabulary, OBO Foundry and Bioinformatics.
Genomics is the subject of his research, which falls under Genetics.
His studies in Gene, GENCODE and Genome are all subfields of Genetics research.
In his study, which falls under the umbrella issue of Controlled vocabulary, The Internet is strongly linked to Annotation.
His Bioinformatics study integrates concerns from other disciplines, such as Ontology and Sequence Ontology.
When carried out as part of a general Ontology research project, his work on Open Biomedical Ontologies is frequently linked to work in Set, therefore connecting diverse disciplines of study.
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.
