What is he best known for?
The fields of study he is best known for:
His scientific interests lie mostly in Multiple sequence alignment, Sequence alignment, Genetics, Algorithm and Genome.
His research in Multiple sequence alignment intersects with topics in Graph, Amino acid, Alignment-free sequence analysis and Sequence analysis.
His Genetics research includes elements of Computational biology and Microbiology.
His Computational biology research is multidisciplinary, relying on both Intron, Genomics, Markov chain, Sequence and Hidden Markov model.
His study on Heuristic, Tree and Greedy algorithm is often connected to Sequence as part of broader study in Algorithm.
To a larger extent, Burkhard Morgenstern studies Gene with the aim of understanding Genome.
His most cited work include:
- MIPS: a database for genomes and protein sequences (1270 citations)
- The genome of the model beetle and pest Tribolium castaneum. (1039 citations)
- AUGUSTUS: ab initio prediction of alternative transcripts (847 citations)
What are the main themes of his work throughout his whole career to date?
Burkhard Morgenstern focuses on Multiple sequence alignment, Sequence alignment, Computational biology, Algorithm and Alignment-free sequence analysis.
His work in Multiple sequence alignment tackles topics such as Pattern recognition which are related to areas like Nucleotide.
Burkhard Morgenstern combines subjects such as Theoretical computer science, Sequence analysis, Information retrieval and Linear space with his study of Sequence alignment.
His Computational biology research incorporates themes from Genetics, Gene prediction, Hidden Markov model and Sequence.
His work deals with themes such as Basis, Word and Pairwise comparison, which intersect with Algorithm.
His Alignment-free sequence analysis research incorporates elements of Speedup and Bioinformatics.
He most often published in these fields:
- Multiple sequence alignment (36.29%)
- Sequence alignment (29.03%)
- Computational biology (26.61%)
What were the highlights of his more recent work (between 2017-2021)?
- Phylogenetic tree (17.74%)
- Word (24.19%)
- Artificial intelligence (16.94%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Phylogenetic tree, Word, Artificial intelligence, Phylogenetics and Pattern recognition.
His Word study frequently links to other fields, such as Sequence alignment.
Much of his study explores Artificial intelligence relationship to Genome.
His study looks at the relationship between Genome and topics such as Pipeline, which overlap with Sequence analysis.
As a member of one scientific family, Burkhard Morgenstern mostly works in the field of Phylogenetics, focusing on Computational biology and, on occasion, Bacterial genome size and Scalable Vector Graphics.
His Pattern recognition research includes themes of Multiple sequence alignment, Nucleotide, Whole genome sequencing and Homology.
Between 2017 and 2021, his most popular works were:
- Benchmarking of alignment-free sequence comparison methods. (88 citations)
- Prot-SpaM: fast alignment-free phylogeny reconstruction based on whole-proteome sequences. (16 citations)
- Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage. (10 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Phylogenetics, Word, Phylogenetic tree, Sequence and Artificial intelligence.
Burkhard Morgenstern has included themes like Algorithm and Pairwise comparison in his Phylogenetics study.
His studies in Word integrate themes in fields like Tree and Sequence alignment.
The study incorporates disciplines such as Computational biology, Binary pattern, Combinatorics and Bacterial genome size in addition to Phylogenetic tree.
His Sequence research incorporates elements of Web service, Sequence comparison, Benchmarking, Inference and Benchmark.
His research integrates issues of Proteome, Machine learning and Pattern recognition in his study of Artificial intelligence.
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