Citing SynergyFinder:

Please use the most recent reference for citing SynergyFinder:

SynergyFinder 3.0.

          Ianevski, A., Giri, K. A., Aittokallio, T., 2022.

          SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples.

          Nucleic Acids Research. gkac382, https://doi.org/10.1093/nar/gkac382
          

SynergyFinder 2.0. (old version)

	  Ianevski, A., Giri, K. A., Aittokallio, T., 2020.

          SynergyFinder 2.0: visual analytics of multi-drug combination synergies. 

	  Nucleic Acids Research. gkaa216, https://doi.org/10.1093/nar/gkaa216
	  

SynergyFinder 1.0. (old version)

		Ianevski, A., He, L., Aittokallio, T. and Tang, J., 2017. 
		

		SynergyFinder: a web application for analyzing drug combination dose–response matrix data. 

		Bioinformatics, 33(15), pp.2413-2415.
	  

Outlier detection

SynergyFinder uses cNMF algorithm to detect and replace outlier measurments. In case of replacing outlier measurment or predicting the missing response please cite:

		Ianevski, A., Giri, A.K., Gautam, P., Kononov, A., Potdar, S., Saarela, J., Wennerberg, K. and Aittokallio, T., 2019.

		Prediction of drug combination effects with a minimal set of experiments. 

		Nature Machine Intelligence, 1(12), pp.568-577.
	  

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Citation example:

The expected drug combination responses were calculated based on ZIP reference model using SynergyFinder [SynergyFinder reference]. Deviations between observed and expected responses with positive and negative values denote synergy and antagonism respectively.

For estimation of outlier measurments cNMF algorithm [Outlier detection reference] implemented in SynergyFinder was utilized.