iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks - Nguyen, Quang H.; Nguyen-Vo, Thanh-Hoang; Le, Nguyen Quoc Khanh; Do, Trang T.T.; Rahardja, Susanto; Nguyen, Binh P. (BMC genomics, 2019)
Keywords: Accuracy; Algorithms; Analysis; Animal Genetics and Genomics; Artificial neural networks; Benchmarking; Biomedical and Life Sciences; Cable television broadcasting industry; Classification; Comparative analysis; Computer applications; Convolutional neural network; Correlation coefficient; Correlation coefficients; Datasets; Deoxyribonucleic acid; DNA; DNA sequencing; Enhancer; Enhancer Elements, Genetic; Enhancers; Ensemble; Gene expression; Gene regulation; Gene sequencing; Genes; Genetic factors; Genetic regulation; Genetic research; Genetic transformation; Genomes; Genomics; Identification; Learning; Life Sciences; Microarrays; Microbial Genetics and Genomics; Model accuracy; Neural networks; Neural Networks, Computer; Noncoding DNA; Nucleotide sequence; One-hot encoding; Plant Genetics and Genomics; Proteomics; Scientists; Sequence Analysis, DNA - methods; Studies; Support vector machines; Transcription; Transcription (Genetics); United States; Deep learning; One-hot encoding; Enhancer; Convolutional neural network; Classification; Ensemble; Identification