PNAS

Diffusive topology preserving manifold distances for single-cell data analysis

Distortions from traditional dimensionality reduction methods obscure relationships in high-dimensional single-cell data, thus impeding biological insights. We introduce DTNE (diffusive topology ...
C&EN

Dynamically Cross-Linked Granular Hydrogels for 3D Printing and Therapeutic Delivery

Biomedical Engineering, College of Engineering, Texas A&M University, College Station, Texas 77843, United States Material Science and Engineering, College of Engineering, Texas A&M University, ...
Frontiers

Co-sparse Non-negative Matrix Factorization

Non-negative matrix factorization, which decomposes the input non-negative matrix into product of two non-negative matrices, has been widely used in the neuroimaging field due to its flexible ...
Frontiers

EEG Feature Selection via Stacked Deep Embedded Regression With Joint Sparsity

In the field of brain-computer interface (BCI), selecting efficient and robust features is very seductive for artificial intelligence (AI)-assisted clinical diagnosis. In this study, based on an ...
PNAS

Link prediction using low-dimensional node embeddings: The measurement problem

Link prediction is a fundamental machine learning task on complex networks, used to evaluate the central technique of low-dimensional embeddings. Our results question the common wisdom that ...
Nature

Merlin—rapid analysis of dense genetic maps using sparse gene flow trees

Efforts to find disease genes using high-density single-nucleotide polymorphism (SNP) maps will produce data sets that exceed the limitations of current computational tools. Here we describe a new, ...