Deep Learning in Bioinformatics | Recent Advancement

Google Slide: #slide=id.p References 1. Tang, B., Pan, Z., Yin, K. and Khateeb, A., 2019. Recent advances of deep learning in bioinformatics and computational biology. Frontiers in genetics, 10, . 2. Alipanahi, B., Delong, A., Weirauch, M.T. and Frey, B.J., 2015. Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning. Nature biotechnology, 33(8), . 3. Park, S., Koh, Y., Jeon, H., Kim, H., Yeo, Y. and Kang, J., 2020. Enhancing the interpretability of transcription factor binding site prediction using attention mechanism. Scientific reports, 10(1), . 4. Lin, E., Mukherjee, S. and Kannan, S., 2020. A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis. BMC bioinformatics, 21(1), . 5. Wan, J.J., Chen, B.L., Kong, Y.X., Ma, X.G. and Yu, Y.T., 2019. An early intestinal cancer prediction Algorithm Based on Deep Belief network. Scientific reports, 9(1), . 6. Chen, G., Tsoi, A., Xu, H. and Zheng, W.J., 2018. Predict effective drug combination by deep belief network and ontology fingerprints. Journal of biomedical informatics, 85, . Image used in Video 1. Aphex34, CC BY-SA 4.0 , via Wikimedia Commons@ 2. 3. 4. , CC BY-SA 3.0 , via Wikimedia Commons 5. Futher Reading: 1. 2. 3. 4. Email: liquidbrain.r@ Website: Patreon: More information: