Relating billions of proteins across the tree of life remains a challenging task for comparative biosphere genomics and artificial intelligence-driven structure prediction. Here we present DIAMOND ...

Clustering stroke patients with similar characteristics to predict subsequent vascular outcome events is critical. This study aimed to compare several clustering methods, particularly a deep neural ...

Thanks to technological advances, scientists have access to vast amounts of data, but in order to put it to work and draw conclusions, they need to be able to process it. In research recently ...

Objective SLE is a heterogeneous systemic autoimmune disease with diverse clinical manifestations. We aimed to identify ...

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and clustering data. A self-organizing map (SOM) is a data structure that can be used ...

Researchers have developed a new AI algorithm, called Torque Clustering, that is much closer to natural intelligence than current methods. It significantly improves how AI systems learn and uncover ...