HAL-X: A Novel Clustering Algorithm for Rapid Single-Cell Data Analysis for Drug Discovery

The novel clustering algorithm HAL-x provides insights into single-cell clustering, bridging the biomedicine sciences for healthcare purposes. With its specificity and sensitivity, it allows the generation of multiple-clustering for in-depth analysis of high-dimensional data. The future directions of algorithms are extremely promising in understanding disease, disease progression, and drug discovery. Throughout the years, clustering has been studied both extensively and intensively in statistics and machine learning. Apart from classical methods, clustering for high-dimensional data is primarily done using non-linear embeddings, which largely lacked visualization and identification of accurate clustering.