Deep Learning in Bioinformatics | Recent Advancement
Google Slide:
https://docs.google.com/presentation/d/1j_JOlDDKEOukmfq9uDlcrX5mSpLxxGEQmE61JueOaHA/edit#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, p.214.
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), pp.831-838.
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), pp.1-4.
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), pp.1-11.
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), pp.1-13.
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, pp.149-154.
Image used in Video
1. Aphex34, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons@https://upload.wikimedia.org/wikipedia/commons/6/63/Typical_cnn.png
2. https://www.researchgate.net/publication/320658590_Deep_Clustering_with_Convolutional_Autoencoders/figures?lo=1&utm_source=google&utm_medium=organic
3. https://www.sciencedirect.com/science/article/pii/S0019057819302903
4. Glosser.ca, CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons
5. https://www.frontiersin.org/files/Articles/420104/fgene-10-00214-HTML/image_m/fgene-10-00214-g007.jpg
Futher Reading:
1. https://towardsdatascience.com/what-is-deep-learning-and-how-does-it-work-2ce44bb692ac
2. https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0
3. https://www.jeremyjordan.me/autoencoders/
4. https://stats.stackexchange.com/questions/51273/what-is-the-difference-between-a-neural-network-and-a-deep-belief-network
Email: liquidbrain.r@gmail.com
Website: https://www.liquidbrain.org/videos
Patreon: https://www.patreon.com/liquidbrain
More information:
bit.ly/Brandon_Yeo
Видео Deep Learning in Bioinformatics | Recent Advancement канала Liquid Brain
https://docs.google.com/presentation/d/1j_JOlDDKEOukmfq9uDlcrX5mSpLxxGEQmE61JueOaHA/edit#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, p.214.
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), pp.831-838.
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), pp.1-4.
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), pp.1-11.
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), pp.1-13.
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, pp.149-154.
Image used in Video
1. Aphex34, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons@https://upload.wikimedia.org/wikipedia/commons/6/63/Typical_cnn.png
2. https://www.researchgate.net/publication/320658590_Deep_Clustering_with_Convolutional_Autoencoders/figures?lo=1&utm_source=google&utm_medium=organic
3. https://www.sciencedirect.com/science/article/pii/S0019057819302903
4. Glosser.ca, CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons
5. https://www.frontiersin.org/files/Articles/420104/fgene-10-00214-HTML/image_m/fgene-10-00214-g007.jpg
Futher Reading:
1. https://towardsdatascience.com/what-is-deep-learning-and-how-does-it-work-2ce44bb692ac
2. https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0
3. https://www.jeremyjordan.me/autoencoders/
4. https://stats.stackexchange.com/questions/51273/what-is-the-difference-between-a-neural-network-and-a-deep-belief-network
Email: liquidbrain.r@gmail.com
Website: https://www.liquidbrain.org/videos
Patreon: https://www.patreon.com/liquidbrain
More information:
bit.ly/Brandon_Yeo
Видео Deep Learning in Bioinformatics | Recent Advancement канала Liquid Brain
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