Sequencing

Most SARS-CoV-2 patients experience anosmia, or a loss of smell, which can linger for months after recovery. According to olfactory epithelium samples taken from...

Controlling gene expression by engineering Cys2His2 zinc finger (ZF) domains to bind particular target sequences in the genome has many therapeutic applications. However, due...

Accurately identifying somatic mutations and differentiating them from germline variations is critical for precision oncology and precise tumor-mutational burden (TMB) computation. For this purpose,...

Scientists from the University of California, San Francisco, have created an inventive AI system that can create entirely new enzymes from scratch. Even though...

There has been an increase in research in numerous areas of biology and medicine due to the development of mass spectrometry lipidomics. As a...

Chemical language models (CLMs) can be used to construct molecules with desired features. Textual representations of novel chemical structures, such as simplified molecular input...

Scientists from University College London, UK, study the Machine Learning (ML) approaches that have successfully closed the ever-widening gap between large amounts of protein...

Scientists from the University of Cambridge have introduced a cutting-edge DNA sequencing method that can precisely pinpoint the location and mechanism of small molecule...

Aston University scientists have made a groundbreaking discovery in the field of virology. They were able to create a 3D model of the virus...

The Children's Hospital of Philadelphia (CHOP) scientists have created ESPRESSO, a new computational tool for analyzing RNA-seq data. ESPRESSO aims to improve the detection...

Owkin, an AI biotech company, has successfully used federated learning (FL) for the first time to train deep learning models on histopathology data from...

According to a recent study from Karl Landsteiner University of Health Sciences (KL Krems), using radiomics and deep learning algorithms can quickly and accurately...

Scientists from Case Western Reserve University, Cleveland, USA, developed a self-supervised image representation learning framework, "ImageMol," for predicting molecular properties and drug targets with...

BioNTech, a leading biopharmaceutical company, has announced plans to fully acquire InstaDeep, an artificial intelligence company specializing in drug discovery, design, and development. This...

Researchers from MIT have created a comprehensive map of over 300 protein kinases and their targets, with the goal of potentially discovering new cancer...

Lung cancer is one of the most common and deadly types of cancer worldwide, and the ability of cancer cells to evade the body's immune system poses a significant challenge in treating it. A team of Weill Cornell Medicine scientists recently made a significant breakthrough in understanding this process. They discovered a genetic signature that can predict patient survival and identified a key mechanism lung cancer cells use to avoid immune attacks. This groundbreaking discovery could hasten the development of treatments that can circumvent tumor defense mechanisms, increasing the chances of survival for lung cancer patients. The signaling pathway involving IRE1 and XBP1 is becoming increasingly recognized as a key player in cancer progression and immune system suppression in various...

Scientists from Carnegie Mellon University developed SPICEMIX, a machine learning method that allows researchers to better understand the contribution of various spatial patterns to...

A recent study utilized digital twin technology to identify new markers for atherosclerotic coronary artery disease (ASCAD). The study was conducted by G3 Therapeutics,...

When it comes to developing new drugs, one of the most important considerations is how well a candidate drug will bind to its target...

The ability to predict cancer has advanced with the recent release of a new database that includes information on cancer proteins and was developed...