What is he best known for?
The fields of study he is best known for:
Knut Reinert mainly focuses on Genetics, Genome project, Hybrid genome assembly, Genome and Human genome.
His research on Genetics focuses in particular on Reference genome.
His studies deal with areas such as Genome evolution and Shotgun sequencing as well as Genome project.
His study explores the link between Hybrid genome assembly and topics such as Sequence assembly that cross with problems in Contig, Cancer genome sequencing and Algorithm.
He combines subjects such as Evolutionary biology and Low copy repeats with his study of Genome.
In his work, Bacterial artificial chromosome and Whole genome sequencing is strongly intertwined with Genome size, which is a subfield of Gene density.
His most cited work include:
- The sequence of the human genome. (10608 citations)
- The genome sequence of Drosophila melanogaster (5233 citations)
- A Whole-Genome Assembly of Drosophila (1342 citations)
What are the main themes of his work throughout his whole career to date?
Knut Reinert focuses on Algorithm, Genome, Computational biology, Mass spectrometry and Data mining.
His Algorithm research incorporates themes from Mathematical optimization and Integer.
His Genome research is under the purview of Genetics.
His work deals with themes such as DNA sequencing theory, Shotgun sequencing, Gene isoform and Breakpoint, which intersect with Computational biology.
His study in Mass spectrometry is interdisciplinary in nature, drawing from both Wavelet and Bioinformatics.
His work investigates the relationship between Data mining and topics such as Software that intersect with problems in Embedded system.
He most often published in these fields:
- Algorithm (24.84%)
- Genome (27.39%)
- Computational biology (24.84%)
What were the highlights of his more recent work (between 2015-2021)?
- Genome (27.39%)
- Algorithm (24.84%)
- Computational biology (24.84%)
In recent papers he was focusing on the following fields of study:
His main research concerns Genome, Algorithm, Computational biology, Data structure and Bioinformatics.
Knut Reinert does research in Genome, focusing on Genomics specifically.
The study incorporates disciplines such as Set, FM-index and Source code in addition to Algorithm.
His Computational biology research is multidisciplinary, relying on both Transcriptome, Gene expression, Differentially expressed genes, Rna expression and Phylogenetic tree.
The concepts of his Data structure study are interwoven with issues in Field, Hardware acceleration and Bloom filter.
His studies examine the connections between Bioinformatics and genetics, as well as such issues in Workflow, with regards to Python, Application programming interface, Software and Software engineering.
Between 2015 and 2021, his most popular works were:
- OpenMS: a flexible open-source software platform for mass spectrometry data analysis (245 citations)
- OpenMS: a flexible open-source software platform for mass spectrometry data analysis (245 citations)
- Computational pan-genomics: status, promises and challenges. (139 citations)
In his most recent research, the most cited papers focused on:
Knut Reinert mostly deals with Bioinformatics, Genome, Data structure, Computational biology and Parallel computing.
His research integrates issues of Python, Application programming interface, Mass spectrometry, Software and Workflow in his study of Bioinformatics.
The Genome study combines topics in areas such as Annotation, RNA splicing and Gene expression profiling.
His Data structure research is multidisciplinary, incorporating perspectives in Bottleneck, Search engine indexing, Database and Bloom filter.
His Computational biology research includes themes of Shotgun sequencing, Lowest common ancestor and Metagenomics.
Knut Reinert interconnects Word and Byte in the investigation of issues within Parallel computing.
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