Transcriptional Response of SK-N-AS Cells to Methamidophos (Extended Abstract)

Abstract

Transcriptomics response of SK-N-AS cells to methamidophos (an acetylcholine esterase inhibitor) exposure was measured at 10 time points between 0.5 and 48 h. The data was analyzed using a combination of traditional statistical methods, machine learning techniques, and methods to infer causal relations between time profiles. We identified several processes that appeared to be upregulated in cells treated with methamidophos including: unfolded protein response, response to cAMP, calcium ion response, and cell-cell signaling. The data confirmed the expected consequence of acetylcholine buildup. Transcripts with potentially key roles were identified by anomaly detection using convolutional autoencoders and Generative Adversarial Networks, and causal networks relating these transcripts were inferred using Siamese convolutional networks and time warp causal inference.