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In addition to deep learning, reinforcement learning (RL) is another approach that is strongly linked to AI and neuroscience to understand how learning is implemented in the brain. In a recently published article, Botvinick et al. (Neuron, 107:603鈥 616, 2020) explain why deep reinforcement ...
29.TPGS-based and S-thanatin functionalized nanorods for overcoming drug resistance in Klebsiella pneumonia. 基于TPGS和S-thanatin的功能化纳米棒克服肺炎克雷伯菌的抗药性. 30.Deep learning to diagnose Hashimoto’s thyroiditis from sonographic images. ...
11.Prediction of designer-recombinases for DNA editing with generative deep learning. 用生成式深度学习预测用于DNA编辑的设计者-重组酶。 12.The lipid flippase SLC47A1 blocks metabolic vulnerability to ferroptosis. 脂质翻转酶SLC47A1阻断了新陈代谢对铁锈病的脆弱性。
Recent works in the machine learning community show that the use of gradient methods produces better interpretations of a neural network than an analysis of their weights [17]. The principle of gradient methods is to backpropagate the activation of the output neuron through the network and to est...
Metabolomics and transcriptomics analysis of prefrontal cortex in the Pax2 neuron-specific deletion mice. January 10, 2024 [MEDLINE Abstract] The contribution of polyamine pathway to determinations of diagnosis for treatment-resistant depression: A metabolomic analysis. ...
work ofJohn O’Keefeand others, many hippocampal cells fire only when the animal is physically located in a specificplace. In early experiments,ratsran the length of a single corridor or circular track, so researchers could easily determine which neuron coded for each position within the corridor...
Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration Loss-of-function variants in thyroid hormone transporter MCT8 cause a neurodevelopmental and metabolic disorder. Here the authors identify genotype-phenotype...