What is he best known for?
The fields of study he is best known for:
Wei Chen mostly deals with Computational biology, Genome, Genetics, Nucleotide composition and Nucleotide.
The study incorporates disciplines such as DNA, DNA sequencing, Web server and Feature selection in addition to Computational biology.
His Genome research includes elements of Epigenomics, Saccharomyces cerevisiae and Support vector machine.
His Genetics study combines topics in areas such as Benchmark, Feature vector and Identification.
His Nucleotide composition study is related to the wider topic of RNA.
His work investigates the relationship between Nucleotide and topics such as Transcription that intersect with problems in Chromatin, Genetic marker and Cell.
His most cited work include:
- Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres (762 citations)
- iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition (484 citations)
- iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. (364 citations)
What are the main themes of his work throughout his whole career to date?
Wei Chen focuses on Computational biology, Genome, Feature selection, Genetics and Support vector machine.
Wei Chen has included themes like Identification, RNA, Jackknife test, Web server and DNA sequencing in his Computational biology study.
His RNA study integrates concerns from other disciplines, such as Transcriptome and Nucleotide.
His Genome research includes themes of DNA, Saccharomyces cerevisiae and Evolutionary biology.
His Feature selection study incorporates themes from Amino acid, Subcellular localization, Identification and Antioxidant.
His Support vector machine research is multidisciplinary, incorporating perspectives in Data mining and Benchmark.
He most often published in these fields:
- Computational biology (85.49%)
- Genome (36.79%)
- Feature selection (37.82%)
What were the highlights of his more recent work (between 2019-2021)?
- Computational biology (85.49%)
- Genome (36.79%)
- Identification (18.13%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computational biology, Genome, Identification, Web server and RNA.
His Computational biology research is multidisciplinary, relying on both Saccharomyces cerevisiae, Encoding, Transcriptome, Identification and Feature selection.
His Genome study is focused on Gene in general.
His research integrates issues of DNA Modification and Machine learning, Random forest, Artificial intelligence in his study of Identification.
The various areas that Wei Chen examines in his Web server study include Data mining and Support vector machine.
Wei Chen interconnects Nucleotide and Effector in the investigation of issues within RNA.
Between 2019 and 2021, his most popular works were:
- Evaluation of different computational methods on 5-methylcytosine sites identification. (61 citations)
- Evaluation of different computational methods on 5-methylcytosine sites identification. (61 citations)
- The water lily genome and the early evolution of flowering plants (48 citations)
In his most recent research, the most cited papers focused on:
His primary scientific interests are in Computational biology, Genome, Web server, Transcriptome and Saccharomyces cerevisiae.
Wei Chen applies his multidisciplinary studies on Computational biology and Key in his research.
In his work, Random forest is strongly intertwined with Identification, which is a subfield of Genome.
The Web server study combines topics in areas such as Feature selection, Pseudouridine, Data mining and Extreme gradient boosting.
His Transcriptome research is multidisciplinary, incorporating elements of RNA, Nucleotide, DNA and In situ hybridization.
His Saccharomyces cerevisiae research integrates issues from Recombination hotspot, Recombination, Homologous recombination and Chromosome.
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