Researchers developed DiscERN, a genome-mining platform that combines four complementary algorithms to identify ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Abstract: To address the challenge of rapidly tracking the new Pareto optimal set (PS) after environmental changes in dynamic multi-objective optimization problems (DMOPs), this paper proposes a ...

When I first started working with integral field spectroscopic (IFU) data, I was struck by how much complexity was being averaged out or masked by traditional processing techniques. Most segmentation ...

Abstract: Spectral clustering algorithms rely on graphs where edges are defined based on the similarity between the vertices (data points). The effectiveness and fairness of spectral clustering depend ...

Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.