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The harnessing of machine learning, especially deep generative models, has opened up promising avenues in the field of synthetic DNA sequence generation.
How proteins recognize the tata box
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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The eukaryotic promoter database: expansion of epdnew and new promoter analysis tools
René Dreos, Giovanna Ambrosini, Rouayda Cavin Périer, and Philipp Bucher · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Multi-scale convolutional neural networks for time series classification
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Unrolled generative adversarial networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Generating and designing dna with deep generative models
Nathan Killoran, Leo J Lee, Andrew Delong, David Duvenaud, and Brendan J Frey · 2017
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Feedback gan for dna optimizes protein functions
Anvita Gupta and James Zou · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Epd in 2020: enhanced data visualization and extension to ncrna promoters
Patrick Meylan, René Dreos, Giovanna Ambrosini, Romain Groux, and Philipp Bucher · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Synthetic promoter design in escherichia coli based on a deep generative network
Ye Wang, Haochen Wang, Lei Wei, Shuailin Li, Liyang Liu, and Xiaowo Wang · 2020
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Advances in promoter engineering: novel applications and predefined transcriptional control
Andrew P Cazier and John Blazeck · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Diffusion autoencoders: Toward a meaningful and decodable representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, and Supasorn Suwajanakorn · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Score-based generative modeling in latent space
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Semi-parametric neural image synthesis
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A continuous time framework for discrete denoising models
Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, and Arnaud Doucet · 2022
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A sequence-based global map of regulatory activity for deciphering human genetics
Kathleen M Chen, Aaron K Wong, Olga G Troyanskaya, and Jian Zhou · 2022
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Analog bits: Generating discrete data using diffusion models with self-conditioning
Ting Chen, Ruixiang Zhang, and Geoffrey Hinton · 2022
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Continuous diffusion for categorical data
Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, et al · 2022
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Controlling gene expression with deep generative design of regulatory dna
Jan Zrimec, Xiaozhi Fu, Azam Sheikh Muhammad, Christos Skrekas, Vykintas Jauniskis, Nora K Speicher, Christoph S Börlin, Vilhelm Verendel, Morteza Haghir Chehreghani, Devdatt Dubhashi, et al · 2022
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Dirichlet diffusion score model for biological sequence generation
Pavel Avdeyev, Chenlai Shi, Yuhao Tan, Kseniia Dudnyk, and Jian Zhou · 2023
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Audioldm: Text-to-audio generation with latent diffusion models
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De novo design of protein structure and function with rfdiffusion
Joseph L Watson, David Juergens, Nathaniel R Bennett, Brian L Trippe, Jason Yim, Helen E Eisenach, Woody Ahern, Andrew J Borst, Robert J Ragotte, Lukas F Milles, et al · 2023
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