Scientists from Michigan State University have introduced the LongBondEliminator, a tool designed to detect and correct ring penetrations in molecular simulations. Ring penetrations is...

Scientists from China have developed DeepBIO, an automated and interpretable deep learning platform for high-throughput biological sequence functional analysis. The first-of-its-kind platform enables researchers...

Substantial progress has been made in assembling the first complete human genome sequence by the Telomere-to-Telomere consortium. However, complex repetitions in diploid genomes are...

Single-cell RNA sequencing (scRNA-seq) has proved to be a powerful tool for deciphering the entire repertoire of transcripts in a single cell. Traditional sequencing...

King's College London scientists examined biological samples from hundreds of participants in a European study. The researchers studied the biological data at different stages,...

Scientists from the University of Maryland have developed PRAWNS, a scalable and efficient tool for multi-genome analysis. With the unprecedented number of complete and...

Researchers from Scripps Research and Japan have discovered how a protein's "poisoned" form can set off a chain of events promoting specific cancers' growth....

Scientists from the Wellcome Sanger Institute, Hinxton, UK, and the University of Tartu, Estonia, have developed a machine learning-based algorithm, MinsePIE, to predict prime...

Scientists from the University of Southern Denmark have made an interesting discovery that may help in the fight against antibiotic-resistant bacteria. The research team...

Scientists from Purdue University unravel cell migration direction under the influence of environmental cues using a ternary logic gate system. Cells detect several environmental...

The biological activity of a protein is determined not only by its static, three-dimensional structure but also by its dynamic characteristics, which form a...

Scientists from the Genome Institute of Singapore and A*STAR Singapore have developed a neural network-based method that implements a multi-instance learning framework, "m6Anet," to...

Autism Spectrum Disorder (ASD), also known as autism, is a global health issue affecting millions of children worldwide. According to the World Health Organization...

Structure-based drug discovery (SBDD) is a standard method for identifying prospective medications for a target by leveraging its structural information. AlphaFold, a technique for...

Scientists from Edinburgh have solved the mystery behind the formation and variation in fingerprint patterns. Fingerprints are complex patterns, unique to every individual, and...

Researchers from Skoltech, MIPT, the National Academy of Sciences of Belarus' Institute of Bioorganic Chemistry (IBOCH NAS), and the Russian Academy of Sciences' Institute...

Scientists from China have recently performed pan-3D genome analysis for soybean genomes to investigate the interplay among 3D genomic variations, structural variations (SV) as...

Scientists at Jinhua Advanced Research Institute and Harbin University of Science and Technology have developed a deep-learning algorithm that can identify depression through speech....

All organisms depend on protein-protein interactions (PPIs) for cellular and biological activities. This paper introduces a novel method for building peptide binders for "undruggable"...

Scientists from Barcelona have discovered a new hexameric protein structure for the RepB protein, which is involved in catalyzing replication initiation in Streptococcal plasmid...

The POPDx model does not require extensive patient datasets, which makes it potentially useful for patients with rare diseases. The POPDx framework was created to...

The digestive system is home to trillions of bacteria, which are very different in each person based on their gender, age, race, lifestyle, and...

Researchers from the Jun Qu lab at SUNY Buffalo, New York, have developed a revolutionary method for in-depth mapping of protein localization in whole...

Cancer is one of the prominent causes of death globally, and discovering new methods to prevent and cure it is important for public health....

Scientists from UCSD have devised an efficient AI-based pipeline, RESP, for identifying high-affinity antibodies. Typically, researchers would employ directed evolution to enable iterative mutagenesis...

According to Levinthal's paradox, each protein may adopt around 10300 distinct structures. We now know 3-D structures for about 98% of the human proteome...

Scientists from Shaanxi Normal University, China, developed a novel Drug-Drug-Interactions (DDI) prediction tool that implements a dual graph neural network architecture to incorporate chemical...

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...

Scientists at the University of Toronto advanced drug formulation development by utilizing machine learning techniques to predict and guide the design of long-acting injectable...

Finding cancer subtypes is a crucial first step in creating individualized care. In particular, RNA splicing change-based sub-typing has been encouraged by a number...

The mechanical properties of DNA are affected by various processes, including local sequence and epigenetic modifications. It has been challenging to understand the relationship...