A bioinformatics researcher is trying to visualize the similarities and differences between different genes in a 2D space. The data is high dimensional. Which technique would provide a good visualization emphasizing local similarities?
- t-Distributed Stochastic Neighbor Embedding (t-SNE)
- Principal Component Analysis
- Linear Regression
- A* Search Algorithm
t-SNE is well-suited for visualizing high-dimensional data by preserving local similarities. It maps data points to a 2D space in a way that emphasizes neighborhood relationships, making it ideal for visualizing gene similarities in high-dimensional data.
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