Alain B. Tchagang
Orcid: 0000-0001-8619-9441
According to our database1,
Alain B. Tchagang
authored at least 40 papers
between 2005 and 2023.
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Bibliography
2023
Examining multi-objective deep reinforcement learning frameworks for molecular design.
Biosyst., October, 2023
J. Comput. Chem., 2023
Understanding the Structure of QM7b and QM9 Quantum Mechanical Datasets Using Unsupervised Learning.
CoRR, 2023
Approximating the Atomic Composition of Drug-like Molecules from Quantum Derived Properties: Inverse Design.
Proceedings of the International Joint Conference on Neural Networks, 2023
Target-learning the Latent Space of a Variational Autoencoder model for the Inverse Design of Stable Perovskites.
Proceedings of the 36th Canadian Conference on Artificial Intelligence, 2023
2022
Towards a Classification Scheme for Inferring the Atomic Composition of Drug-like Molecules from their Quantum Derived Electronic Properties.
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2022
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2022
2021
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2021
Time Frequency Representations and Deep Convolutional Neural Networks: A Recipe for Molecular Properties Prediction.
Proceedings of the 34th IEEE Canadian Conference on Electrical and Computer Engineering, 2021
2020
Deterministic Numeric Simulation and Surrogate Models with White and Black Machine Learning Methods: A Case Study on Inverse Mappings.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
Deterministic Numeric Simulation and Surrogate Models with White and Black Machine Learning Methods: A Case Study on Direct Mappings.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
2019
Characterization of Quantum Derived Electronic Properties of Molecules: A Computational Intelligence Approach.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019
Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019
Discrete Fourier Transform Improves the Prediction of the Electronic Properties of Molecules in Quantum Machine Learning.
Proceedings of the 2019 IEEE Canadian Conference of Electrical and Computer Engineering, 2019
Proceedings of the 2019 IEEE Canadian Conference of Electrical and Computer Engineering, 2019
2018
Bioinformatics Identification of Drug Gene Modules: Application to Clear Cell Carcinoma of the Ovary.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
2017
Bioinformatics identification of new targets for improving low temperature stress tolerance in spring and winter wheat.
BMC Bioinform., 2017
2016
Integration of 3D gene expression patterns and gene regulatory networks for clinical applications in epithelial ovarian cancer.
Proceedings of the 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics, 2016
2015
Digitization of trait representation in microarray data analysis of wheat infected by fusarium graminearum.
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2015
2014
Int. J. Comput. Model. Algorithms Medicine, 2014
2013
A generic model of transcriptional regulatory networks: Application to plants under abiotic stress.
Proceedings of the 2013 IEEE International Workshop on Genomic Signal Processing and Statistics, 2013
2012
Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.
BMC Bioinform., 2012
2011
Proceedings of the Handbook of Research on Computational and Systems Biology, 2011
2010
BMC Bioinform., 2010
Integrative Data Mining in Functional Genomics of <i>Brassica napus</i> and <i>Arabidopsis thaliana</i>.
Proceedings of the Trends in Applied Intelligent Systems, 2010
Towards a temporal modeling of the genetic network controlling Systemic Acquired Resistance in Arabidopsis thaliana.
Proceedings of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2010
2009
Extracting biologically significant patterns from short time series gene expression data.
BMC Bioinform., 2009
Towards the reconstruction of Brassica napus seed development FA metabolism dynamic regulatory map.
Proceedings of the 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, 2009
2008
Biological evaluation of biclustering algorithms using Gene Ontology and chIP-chip data.
Proceedings of the IEEE International Conference on Acoustics, 2008
2007
Proceedings of the IEEE International Conference on Acoustics, 2007
Proceedings of the 15th European Signal Processing Conference, 2007
2006
IEEE Trans. Signal Process., 2006
EURASIP J. Adv. Signal Process., 2006
Parallel Biclustering of Genes with Coherent Evolutions: Algorithm and Biological Significance of the Biclusters.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006
Proceedings of the 14th European Signal Processing Conference, 2006
2005
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005
Proceedings of the 13th European Signal Processing Conference, 2005