Examination of (a)periodic brain activity has gained particular interest in the last few years in the neuroscience fields relating to cognition, disorders, and brain states. Using large EEG/MEG ...

When a dataset contains thousands¾or even millions¾of features, it is considered high-dimensional data. While more features may seem helpful, high dimensionality introduces several challenges in ...

This manuscript reports a useful computational study of information encoding across the monkey prefrontal and pre-motor cortices during decision making. While many of the conclusions are supported ...

Single-cell RNA sequencing (scRNA-seq) maps heterogeneity in gene expression in large cell populations. This heterogeneity can be attributed to various factors, both observed and hidden 1. We can ...

Mathematics is one of the oldest disciplines of study. For all its antiquity, however, it is a modern, rapidly growing field. Only 70 years ago, mathematics might have been said to consist of algebra, ...

Analysis of population structure and genomic ancestry remains an important topic in human genetics and bioinformatics. Commonly used methods require high-quality genotype data to ensure accurate ...

In light of the rapid accumulation of large-scale omics datasets, numerous studies have attempted to characterize the molecular and clinical features of cancers from a multi-omics perspective. However ...

We demonstrate that a neural network automatically solves, explains, and generates university-level problems from the largest Massachusetts Institute of Technology (MIT) mathematics courses at a human ...

In order to evaluate brain changes in young children with Pierre Robin sequence (PRs) using machine learning based on apparent diffusion coefficient (ADC) features, we retrospectively enrolled a total ...

Little had been known about whether the ongoing climate changes had already affected observed global tropical cyclones (TCs). This study revealed that a climate change in global TC activity over 1980 ...