What is he best known for?
The fields of study he is best known for:
Michael Gribskov focuses on Genetics, Sequence analysis, Sequence, Sequence alignment and Biochemistry.
Gene, Whole genome sequencing, Conserved sequence, Genome and Peptide sequence are among the areas of Genetics where the researcher is concentrating his efforts.
His Sequence analysis research incorporates elements of Field, Biotechnology, Gene sequence, Data manipulation language and Computational biology.
His study looks at the intersection of Sequence and topics like Multiple sequence alignment with Nucleic acid sequence, Multiple EM for Motif Elicitation, Set, Homology and Algorithm.
He focuses mostly in the field of Sequence alignment, narrowing it down to matters related to Sigma factor and, in some cases, Bacteriophage, Phagemid, DNA and Phage display.
Protein kinase A, Kinase and Arabidopsis are the subjects of his Biochemistry studies.
His most cited work include:
- Sequence Analysis Primer (1444 citations)
- Profile analysis: detection of distantly related proteins. (1159 citations)
- Combining evidence using p-values: application to sequence homology searches. (997 citations)
What are the main themes of his work throughout his whole career to date?
Michael Gribskov mainly focuses on Genetics, Computational biology, Gene, Biochemistry and Genome.
His study in Arabidopsis, Peptide sequence, Sequence alignment, Conserved sequence and DNA microarray are all subfields of Genetics.
He interconnects Arabidopsis thaliana and Phylogenetic tree in the investigation of issues within Arabidopsis.
Michael Gribskov combines subjects such as Protein structure, Protein primary structure, Sequence analysis and Sequence with his study of Computational biology.
Michael Gribskov has included themes like Algorithm, Software and Multiple sequence alignment in his Sequence analysis study.
His research investigates the link between Protein kinase A and topics such as Proteomics that cross with problems in Hidden Markov model.
He most often published in these fields:
- Genetics (34.12%)
- Computational biology (29.41%)
- Gene (16.47%)
What were the highlights of his more recent work (between 2008-2020)?
- Gene (16.47%)
- Genetics (34.12%)
- Genome (12.94%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Gene, Genetics, Genome, Computational biology and RNA.
His study in Selaginella extends to Genetics with its themes.
His Genome research integrates issues from Fungal genetics, RNA editing and Fusarium solani.
His research in Computational biology intersects with topics in Chromatin, Regulation of gene expression, Gene expression and Sequence.
Gene expression connects with themes related to Long non-coding RNA in his study.
His RNA research is multidisciplinary, relying on both Biophysics, Nucleobase, Whole genome sequencing and Protein secondary structure.
Between 2008 and 2020, his most popular works were:
- The Selaginella genome identifies genetic changes associated with the evolution of vascular plants. (579 citations)
- The genome of Nectria haematococca: contribution of supernumerary chromosomes to gene expansion. (326 citations)
- A Physical Interaction Network of Dengue Virus and Human Proteins (122 citations)
In his most recent research, the most cited papers focused on:
Michael Gribskov mostly deals with Gene, Genome, Genetics, Protein–protein interaction and Viral replication.
His work on Fungal genetics as part of general Gene study is frequently linked to Population, Gene mapping and B chromosome, therefore connecting diverse disciplines of science.
His work deals with themes such as RNA, Small RNA and RNA editing, which intersect with Genome.
Many of his studies on Genetics involve topics that are commonly interrelated, such as Selaginella.
His Protein–protein interaction research includes elements of NS3, Replicon and Virology.
Michael Gribskov merges Viral replication with Transport protein in his study.
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