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Predicting novel microRNA: a comprehensive comparison of machine learning approaches.

, , , , , , , , , and . Briefings Bioinform., 20 (5): 1607-1620 (2019)

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Predicting Activities in Business Processes with LSTM Recurrent Neural Networks., , , and . Kaleidoscope, page 1-7. IEEE, (2018)Knowledge discovery through ontology matching: An approach based on an Artificial Neural Network model., , , , and . Inf. Sci., (2012)Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches., , , , , , , , , and 3 other author(s). Briefings Bioinform., (2022)Compressing arrays of classifiers using Volterra-neural network: application to face recognition., , and . Neural Comput. Appl., 23 (6): 1687-1701 (2013)DL4papers: a deep learning approach for the automatic interpretation of scientific articles., , , , , , , , , and . Bioinform., 36 (11): 3499-3506 (2020)Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series., , and . IEEE ACM Trans. Comput. Biol. Bioinform., 12 (6): 1365-1373 (2015)Extreme learning machines for reverse engineering of gene regulatory networks from expression time series., , and . Bioinform., 34 (7): 1253-1260 (2018)Predicting novel microRNA: a comprehensive comparison of machine learning approaches., , , , , , , , , and . Briefings Bioinform., 20 (5): 1607-1620 (2019)Knowledge Source Discovery: An Experience Using Ontologies, WordNet and Artificial Neural Networks., , , , and . KES (2), volume 5712 of Lecture Notes in Computer Science, page 66-73. Springer, (2009)Compressing a neural network classifier using a Volterra-Neural Network model., , and . IJCNN, page 1-7. IEEE, (2010)