A neural network approach to chemical and gene/protein entity recognition in patents.
Ling LuoZhihao YangPei YangYin ZhangLei WangJian WangHongfei LinPublished in: J. Cheminformatics (2018)
Keyphrases
- neural network
- chemical compounds
- sequence alignment
- drug discovery
- regulatory networks
- cellular processes
- protein protein interaction networks
- genomic sequences
- molecular level
- chemical reactions
- homo sapiens
- protein interaction
- virtual screening
- interaction networks
- gene prediction
- nucleotide sequences
- gene expression
- amino acids
- protein protein interactions
- signaling pathways
- chemical reaction
- neural network model
- information retrieval
- artificial neural networks
- gene ontology
- protein sequences
- back propagation
- biological entities
- protein function
- prior art
- gene regulatory networks
- microarray
- dna binding
- saccharomyces cerevisiae
- protein structure
- gene expression data
- biological knowledge
- gene selection
- protein folding
- gene function
- dna sequences
- united states
- molecular biology
- protein structure prediction
- biomedical literature
- genome sequences
- network model
- self organizing maps
- gene expression profiles