Expanding on item at end of [another thread](https://www.synapse.org/#!Synapse:syn18666641/discussion/threadId=6022) .
#### PCA
* [Example for Principal Component Analysis (PCA): Iris data](https://www.math.umd.edu/~petersd/666/html/iris_pca.html)
* [Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0574-4)
* [Principal Component Analysis as a Tool for Library Design: A Case Study Investigating Natural Products, Brand-Name Drugs, Natural Product-Like Libraries, and Drug-Like Libraries](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373534/)
* [A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose?Response Curve](https://ascpt.onlinelibrary.wiley.com/doi/10.1002/psp4.9) uses PCA to remove outliers
#### Clustering
* [A two-tiered unsupervised clustering approach for drug repositioning through heterogeneous data integration](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2123-4)
* [A Comparative Study of Cluster Detection Algorithms in Protein?Protein Interaction for Drug Target Discovery and Drug Repurposing](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389713/)
* [Seurat - Guided Clustering Tutorial](https://satijalab.org/seurat/v3.1/pbmc3k_tutorial.html)
#### Graph algorithms
* [iDTI-ESBoost: Identification of Drug Target Interaction Using Evolutionary and Structural Features with Boosting](https://arxiv.org/pdf/1707.00994.pdf)
* [Drug Target Prediction and Repositioning Using an Integrated Network-Based Approach](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0060618)
#### Gradient-boosted classifier tree
* [An integrative machine learning approach for prediction of toxicity-related drug safety](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6262234/)
#### Tensor
* [Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5653784/)
* [Drug candidate identification based on gene expression of treated cells using tensor decomposition-based unsupervised feature extraction for large-scale data](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2395-8)