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Domain constraint and curriculum learning were introduced into Enhancer-GAN to alleviate the noise from feedback loop and accelerate the training convergence.
Dec 17, 2023 · Here, we propose an AI-driven enhancer design method, named Enhancer-GAN, to generate high-activity enhancer sequences.
[PDF] High-Activity Enhancer Generation based on Feedback GAN ... - bioRxiv
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Dec 17, 2023 · Abstract—Enhancers are important cis-regulatory elements, enhancing the transcription of target genes. De novo design of high-activity ...
Abstract—Enhancers are important cis-regulatory elements, enhancing the transcription of target genes. De novo design of high-activity enhancers is one of ...
Apr 11, 2024 · Domain constraint and curriculum learning are introduced to alleviate noise and accelerate training convergence. Experimental results show that ...
Enhancer-GAN is firstly pre-trained on a large enhancer dataset that contains both low-activity and high-activity enhancers, and then is optimized to generate ...
This paper designs a GAN framework, partition GAN (PAR-GAN), which consists of one generator and multiple discriminators trained over disjoint partitions of ...
Apr 25, 2024 · High-Activity Enhancer Generation based on Feedback GAN with Domain Constraint and Curriculum Learning. BIBM 2023: 2065-2070. [+][–]. 2010 ...
High-Activity Enhancer Generation based on Feedback GAN with Domain Constraint and Curriculum Learning. Jiahao Li, Liwei Xiao, Jiawei Luo, Xianliang Liu ...
Jun 18, 2020 · In this work we study representations learnt by a GAN generator. First, we show that these representations can be easily projected onto semantic segmentation ...
Missing: Activity Enhancer Feedback Constraint Curriculum