Our cells are supported critically by proteins, which are also highly affected by their 3D structure. The triumph in computational biology is the ability...

RNA sequencing is currently a useful tool for studying the dynamic transcriptional mechanisms that control the operation of eukaryotic cells. Nevertheless, complicated experimental designs...

Acting as enzymes, structural elements, and molecular motors, proteins represent the molecular drive of biological systems, the elucidation of which relies on the explication...

Single-cell RNA sequencing (scRNA-seq) has brought a revolution in biological research by granting scientists a look into the mechanisms inside individual cells within a...

Artemisinin, which is used as a cure for malaria, has remained an effective drug in managing the disease over the years. However, the recent...

Users without prior Machine Learning (ML) experience have difficulties when it comes to training and implementing deep learning models. Regardless of prior experience with...

Unsung heroes of our cells are RNAs. These molecules are responsible for many biological processes, from carrying hereditary material to controlling protein production. However,...

Antibiotic resistance is one of the most pressing challenges in modern medicine. As bacteria evolve to withstand our best treatments, once-manageable infections are becoming...

Genie is a promising method for designing proteins that use expressive SE(3)-equivariant attention and simple Gaussian noise to represent structures asymmetrically during forward and...

In a recent study, scientists from Tsinghua University, China, introduced GeneFormer, a unique system for compressing gene sequences. The technique uses transformers to make...

In the ever-changing environment of computational biology, predicting the structure of protein-ligand complexes remains a vital task with far-reaching ramifications for drug development and...

Drug discovery is a process known for being slow and expensive. A great number of optimistic molecules disappear in clinical trials while patients wait...

Personalized medicine and effective sequence utilization are made possible by protein design, even in cases when numerous sequence alignments are not well constructed. This...

In drug discovery, the accurate prediction of chemical activities is paramount. The conventional forms of QSAR that were initially developed and widely used are...

In the drug discovery process, high-throughput screening quickly evaluates a wide range of chemical compounds to find hit compounds for certain biological targets. False-positive...

Scientists from the University of Missouri, Columbia introduced PoseBench, the first exhaustive benchmark for practical protein-ligand docking, enabling rigorous evaluation of deep learning docking...

Lives would not be made perfect without proteins since they are vital macromolecules that provide stability in their function. The study from Stanford University...

The field of bioinformatics is experiencing a renaissance fueled by Artificial Intelligence (AI). Techniques like deep learning and machine learning can handle complex biological problems...

A typical gigapixel slide may include tens of thousands of picture tiles, which presents special computing issues for digital pathology. The crucial slide-level context...

The discovery of ProtT3 marks a significant recent advance in the fast-developing science of bioinformatics. ProtT3, developed by researchers at the National University of...

Clonal variation emerges across tissues as a result of somatic evolution, with far-reaching consequences for human health. The VEXAS (Vacuoles E1 enzyme X-linked Autoinflammatory...

A recent study by the Chengxin Zhang lab from the University of Michigan introduced StarFunc, an accurate protein function prediction approach integrating cutting-edge deep...

Language models have made a new era of biological sequence modeling possible. However, it is still difficult to extract significant sequence-level embeddings from these...

Scientists have questioned the comparison of genes' organization across various species. Collinearity analysis is a helpful way to go about this task, although it...

The subject of protein engineering has shown great promise for protein language models. Unfortunately, the main size at which the existing protein language models...

Transcriptomics has emerged as a powerful tool in modern biology; it deals with the study of the entire set of RNA transcripts produced by the genome at...

FAIR bioinformatics research relies heavily on standardized analysis pipelines. Point-and-click pipeline programs like Galaxy have gradually given way to command-line programs like Nextflow and...

Scientists from the University of Oxford along with the Technical University of Denmark have introduced AntiFold: a specialized model for antibody design that will...

For years, biocatalysis has depended on bioprospecting – in essence, sieving through Nature's enzyme riches to find the best match. However, this method, though...

The languages of biology and chemistry are difficult for language processing and computer vision systems to grasp, notwithstanding their advances in language processing. Although...

Despite the immense hurdles posed by cancer, technological developments, particularly in medical imaging and biomarker identification, provide a ray of hope. Foundation models have...

Comprehensive data atlases have been made possible by the data-driven nature of biomedical research thanks to large-scale single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics...

Spatial omics involve scientists generating maps of gene expression within tissues as they continue to evolve. This is an extremely important development with significant...

Scientists from Waseda University and Hitachi, Ltd., Japan, developed a novel approach for predicting antibiotic resistance genes (ARGs) resistance mechanisms using Protein-BERT, a protein...

Molecular dynamics (MD) files have accumulated in generalist data repositories due to the rise of open science and the lack of a worldwide repository...

DeepMind and Isomorphic Labs unveil AlphaFold 3, an AI model that predicts structures and interactions of all biomolecules like proteins, nucleic acids, ligands, and...

Drugs with polypharmacology, or substances that block several proteins, offer a wide range of uses but are challenging to create. To overcome this difficulty,...

Have you ever wondered how those dense jungles and tall trees appear? It began with a leap from the water, a colonization attempt by...

The development of single-cell profiling methods has transformed our understanding of the cellular and molecular processes underlying disease states and how they respond to...

AI faces significant obstacles in achieving excellence in a wide range of medical applications since it needs sophisticated reasoning, access to current medical information,...

InstaDeep and BioNTech scientists introduced ChatNT, a multimodal conversational agent that has an advanced understanding of biological sequences like DNA, RNA, and proteins. ChatNT...

An endeavor to create new medicinal compounds that can reach great heights, though challenging, remains vital. The advent of computer tools has led to...

Biological research has been in a golden age ever since the advent of high-throughput technologies. We can now probe deeper into living systems than...

A significant issue in genome research is the Nucleotide Transformer, which makes DNA sequence interpretation accurate only with models such as DNABERT-2. Although these...

The ability to precisely alter genes with CRISPR technology has revolutionized biomedical research. It does, however, take a thorough grasp of CRISPR technology and...

A recent study published in Nature Communications explored the relationship between gene expression prediction and the use of deep learning models, which are the...

Think of a society where daily requirements – such as biofuels for cars and drugs to cure illnesses – are not manufactured in polluting...

Predicting protein-protein interactions (PPIs) is essential to comprehend biological processes and illnesses. Conventional machine learning techniques ignore nonphysical linkages made through intermediary proteins in...

Suppose there was a world in which your doctor could not just see how large and where your tumor is but also know the...

The increasing relevance of protein design across a range of scientific fields drives the creation of integrative computational platforms that improve tool accessibility and...