含有工程菌的單層人工神經網路（Emerging Technologies）
- 2020 年 1 月 8 日
- 筆記
通過電子電腦、光子學和體外DNA計算，我們建立了人工神經網路的抽象數學規則。在這裡，我們演示了人工神經網路在活的細菌細胞中的物理實現。我們使用工程菌創建了單層人工神經網路，單個細菌作為一個人工神經元，並演示了一個2- to-4解碼器和一個1-to-2解復用器來處理化學訊號。輸入細胞外的化學訊號後，這些訊號線性結合，通過一個非線性的雙彎曲激活函數進行處理，產生熒光蛋白輸出。激活函數由合成的遺傳電路生成，對每個人工神經元，通過設計細菌神經元內的分子相互作用，手動調整其權值和偏置值，以表示特定的邏輯函數。人工細菌神經元被連接成人工神經網路結構，以實現2- to-4化學解碼器和1-to-2化學解復用器。據我們所知，這是第一個由人工細菌神經元產生的神經網路。這為人工神經網路的研究開闢了新的方向，工程生物細胞可以作為人工神經網路的硬體。
原文題目：A single layer artificial neural network with engineered bacteria
原文： The abstract mathematical rules of artificial neural network (ANN) are implemented through computation using electronic computers, photonics and in-vitro DNA computation. Here we demonstrate the physical realization of ANN in living bacterial cells. We created a single layer ANN using engineered bacteria, where a single bacterium works as an artificial neuron and demonstrated a 2- to-4 decoder and a 1-to-2 de-multiplexer for processing chemical signals. The inputs were extracellular chemical signals, which linearly combined and got processed through a non-linear log-sigmoid activation function to produce fluorescent protein outputs. The activation function was generated by synthetic genetic circuits, and for each artificial neuron, the weight and bias values were adjusted manually by engineering the molecular interactions within the bacterial neuron to represent a specific logical function. The artificial bacterial neurons were connected as ANN architectures to implement a 2- to-4 chemical decoder and a 1-to-2 chemical de-multiplexer. To our knowledge, this is the first ANN created by artificial bacterial neurons. Thus, it may open up a new direction in ANN research, where engineered biological cells can be used as ANN enabled hardware.
原文作者：Kathakali Sarkar, Deepro Bonnerjee, Sangram Bagh
原文地址： https://arxiv.org/abs/2001.00792
