Many studies have used single-cell RNA sequencing (scRNA-seq) to infer gene regulatory networks (GRNs), which are crucial for ...

Many conventional computer architectures are ill-equipped to meet the computational demands of machine learning-based models. In recent years, some engineers have thus been trying to design ...

The default mode network (DMN) is a set of interconnected brain regions known to be most active when humans are awake but not ...

Northwestern Medicine scientists have discovered new details about how the human genome produces instructions for creating ...

Jonathan EnudemeJonathan Enudeme Imagine finding yourself lost in a foreign land where no one speaks English or your native language. The streets are unfamiliar, and every turn leads you deeper into ...

Researchers at FORTH have developed a new type of artificial neural network (ANN) that incorporates features of biological ...

A Generative Adversarial Network (GAN) is a type of machine learning model that’s used to generate fake data that resembles ...

China's DeepSeek became OpenAI's competitor - faster, cheaper, better. It's a start of a new reality for business leaders and ...

Proposed architecture reduces the network diameter 50 percent compared to 2D mesh. This ends in less network average latency and power consumption considerably, which are demonstrated by performance ...

This paper proposes an improved gray-box modeling technique that combines the accuracy of the neural network (NN) technique with the physical ... The proposed approach was applied to GaN High Electron ...

GaN is especially well-established in low-power applications ... However, the spacing between devices is still constrained by the need for adequate isolation. Vertical device architectures allow ...

Introduction: Neurosphere culture is widely used to expand neural stem and progenitor cells (NSPCs) of the nervous system. Understanding the identity of NSPCs, such as the principals involved in ...