Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.

由于数据不足，神经系统的图论分析通常忽略连接极性方面的问题。秀丽隐杆线虫的化学突触网络是一个重建良好的定向网络，但其连接的迹象尚未阐明。在这里，我们提出了基于基因表达的C离子型化学突触连接组的符号预测。线虫（总共 3,638 个连接和 20,589 个突触），整合了三个主要神经递质系统的可用突触前神经递质和突触后受体基因表达数据。我们对超过三分之二的化学突触进行了预测，并观察到兴奋性抑制 (E:I) 比率接近 4:1，这与在许多现实世界网络中观察到的情况相似。我们的开源工具（http://EleganSign.linkgroup.hu）简单但有效地通过整合神经元连接组和基因表达数据来预测极性。