What is he best known for?
The fields of study he is best known for:
His primary scientific interests are in Genetics, Genome, Gene, Whole genome sequencing and Computational biology.
His Genome research is multidisciplinary, incorporating elements of Archaea, Phylogenetic tree and Metagenomics.
In his study, which falls under the umbrella issue of Gene, Northern blot is strongly linked to Molecular biology.
His work deals with themes such as Phylum and Microbial population biology, which intersect with Computational biology.
His studies in Cancer genome sequencing integrate themes in fields like Chimpanzee genome project, Transcriptome and Gene expression profiling.
The study incorporates disciplines such as Cancer Genome Project, DNA sequencing theory, Hybrid genome assembly and Personal genomics in addition to Gene density.
His most cited work include:
- Initial sequencing and analysis of the human genome. (18816 citations)
- Insights into the phylogeny and coding potential of microbial dark matter (1378 citations)
- A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. (811 citations)
What are the main themes of his work throughout his whole career to date?
Jan Fang Cheng mainly investigates Genetics, Genome, Gene, Whole genome sequencing and Type species.
His Genetics and Plasmid, Chromosome, Genome project, DNA sequencing and Sequence investigations all form part of his Genetics research activities.
His studies deal with areas such as Phylum, Computational biology, Archaea and Phylogenetic tree as well as Genome.
His Computational biology research includes themes of Metagenomics, CRISPR, Genome engineering and Genomics.
Jan Fang Cheng combines subjects such as Thermophile and Molecular biology with his study of Gene.
His research investigates the connection with Whole genome sequencing and areas like Bacteria which intersect with concerns in Biochemistry.
He most often published in these fields:
- Genetics (75.08%)
- Genome (70.27%)
- Gene (65.47%)
What were the highlights of his more recent work (between 2014-2021)?
- Genome (70.27%)
- Computational biology (15.32%)
- Gene (65.47%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Genome, Computational biology, Gene, Whole genome sequencing and Genetics.
In his work, Phylogenetic tree and Microbial metabolism is strongly intertwined with Phylogenetics, which is a subfield of Genome.
His Computational biology research includes elements of Genome engineering, Genomic library, Illumina dye sequencing, Microbial ecology and Metagenomics.
Jan Fang Cheng interconnects Synthetic biology and Enzyme in the investigation of issues within Gene.
His Whole genome sequencing study combines topics in areas such as Shewanella algae, Pontibacter actiniarum, Microbiology, Comparative genomics and Rhizosphere.
The concepts of his Genetics study are interwoven with issues in Natural selection and Phycomyces.
Between 2014 and 2021, his most popular works were:
- High-resolution phylogenetic microbial community profiling (135 citations)
- Expansion of Signal Transduction Pathways in Fungi by Extensive Genome Duplication. (114 citations)
- Cryptic inoviruses revealed as pervasive in bacteria and archaea across Earth's biomes. (69 citations)
In his most recent research, the most cited papers focused on:
Jan Fang Cheng mainly focuses on Genome, Computational biology, Gene, Genetics and Metagenomics.
His biological study spans a wide range of topics, including Bacteria, CRISPR and Genomic library.
His Genomic library study integrates concerns from other disciplines, such as Consensus sequence, Genomic island, Whole genome sequencing and Contig.
His Computational biology research incorporates elements of Metabolic engineering, Microbial population biology, Photorhabdus luminescens, Phylum and Microbial ecology.
His studies in Gene family, Mutant, Phycomyces blakesleeanus, Signal transduction and Gene duplication are all subfields of Genetics research.
His research in Metagenomics intersects with topics in Microbiome, DNA sequencing and GC-content.
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