Transcriptional Response of SK-N-AS Cells to Methamidophos (Extended Abstract)
| Autor: | Peter Avar, Lida Parvin, Maria I. Zavodszky, Brian Michael Davis, Merrill Knapp, Mark-Oliver Stehr, Christine A. Morton, Albert-Baskar Arul, Ziad J. Sahab, Akos Vertes, Andrew R. Korte, Christopher J. Sevinsky, Andrew Poggio, Deborah I. Bunin, Denise Nishita, Carolyn L. Talcott |
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| Rok vydání: | 2019 |
| Předmět: |
050101 languages & linguistics
Causal relations Methamidophos 05 social sciences 02 engineering and technology Computational biology Biology Transcriptome chemistry.chemical_compound Downregulation and upregulation chemistry Causal inference 0202 electrical engineering electronic engineering information engineering medicine Unfolded protein response Transcriptional response 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Acetylcholine medicine.drug |
| Zdroj: | Computational Methods in Systems Biology ISBN: 9783030313036 CMSB |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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