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.
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.
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.
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.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres
Andrew H Paterson;Jonathan F Wendel;Heidrun Gundlach;Hui Guo.
iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition
Wei Chen;Peng-Mian Feng;Hao Lin;Kuo-Chen Chou.
Nucleic Acids Research (2013)
iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.
Hao Lin;En-Ze Deng;Hui Ding;Wei Chen.
Nucleic Acids Research (2014)
PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.
Wei Chen;Tian-Yu Lei;Dian-Chuan Jin;Hao Lin.
Analytical Biochemistry (2014)
iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition
Shou-Hui Guo;En-Ze Deng;Li-Qin Xu;Hui Ding.
iACP: a sequence-based tool for identifying anticancer peptides
Wei Chen;Hui Ding;Pengmian Feng;Hao Lin.
iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition.
Wei Chen;Pengmian Feng;Hui Ding;Hao Lin.
Analytical Biochemistry (2015)
Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences
Wei Chen;Hao Lin;Hao Lin;Kuo-Chen Chou.
Molecular BioSystems (2015)
iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition
Peng-Mian Feng;Wei Chen;Hao Lin;Kuo-Chen Chou.
Analytical Biochemistry (2013)
iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC.
Pengmian Feng;Hui Yang;Hui Ding;Hao Lin.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: