Protein complex structures form the foundation for understanding the complexities of molecular biology. While deep learning-based methods have significantly enhanced the prediction of single...

Scientists at the Massachusetts Institute of Technology and Tufts University introduced a deep-learning model named ConPLex that executes sequence-based predictions of Drug Target Interaction...

Researchers at the Chemical Engineering Department of the University of Rochester, New York, introduce three deep learning sequence-based models for peptide properties prediction implementing...

The discovery of novel molecules with desired properties is a long-standing challenge in medicinal chemistry. On the other hand, de novo drug design tools...

Burn injuries often incite substantial morbidity and lethality aftermath. Severe burn injuries due to hot liquids or solids and fire induce pathophysiological and inflammatory...

Mount Sinai researchers have revealed a groundbreaking artificial intelligence (AI) model for electrocardiogram (ECG) analysis. This pioneering approach allows ECGs to be interpreted as...

Researchers at the University of Missouri upgraded the MULocDeep web application by integrating animal, fungi, and plant species-specific models that meet competitive performance at...

Snekmer, an innovative software developed to better understand protein function in microbes, emerged from the collaborative efforts of researchers from the Pacific Northwest National...

Recent research has demonstrated that generative AI has the ability to greatly speed up drug development in the pharmaceutical industry. Currently, it can take...

As the integration of genome sequencing in scientific research, government policy, and personalized medicine continues to grow, the primary challenge for researchers has shifted...

Comprehensive introspection of cellular and molecular level aberrations that prompted the worldwide prevalence of life-threatening Non Communicable Diseases like Diabetes, Obesity, Hypertension, Nonalcoholic Fatty...

Scientists from the Hengyang Normal University, China, designed a stacked autoencoder (SAE) with a multi-head attention mechanism-based microbe drug association prediction model named MDASAE....

Resilient weeds, impervious to herbicides, present a grave danger to both the environment and the agricultural sector. The pressing demand for fresh herbicides, armed...

Scientists from the Microsoft Research Lab, Cambridge, have designed a Self-Supervised Neural Network Masked Language Model named BiGCARP to accelerate the identification and classification...

Genomic analysis plays a vital role in various areas, such as disease detection, drug development, and genetic disease identification. With the exponential growth of...

Malaria, a parasitic disease transmitted by mosquitoes, poses a grave global health menace. With countless annual cases and the escalating defiance of traditional antimalarial...

A groundbreaking study conducted by scientists from MIT and McMaster University has unveiled a revolutionary artificial intelligence-based antibiotic that effectively eliminates a specific strain...

Artificial intelligence (AI) has significantly changed the scientific research landscape in recent years, yet structure-based drug development has not been significantly affected. However, a...

A team of UCSF, UCSD, and Brown University scientists has produced a multi-scale map of protein assemblies pertaining to damage response. The DNA Damage...

In recent years, significant advancements in machine learning, particularly AlphaFold 2 (AF2), have revolutionized protein structure prediction. These breakthroughs have generated excitement in the...

Scientists from CHOP, Philadelphia, and UCLA have developed an integrated computational workflow to discover novel cancer immunotherapy targets from pre-mRNA alternative splicing (AS). The...

Genomics to Notebook (g2nb) is a new environment that combines the popular JupyterLab notebook system with well-established bioinformatics platforms to provide a seamless and...

Artificial intelligence nowadays dominates our news feeds, capturing public interest as ChatGPT and similar AI advancements take center stage. Biologists are actively investigating novel...

A consortium of scientists from across the globe has undertaken a massive computational effort to produce predictive models on the effect of phosphorothioate (PS)...

Mount Sinai researchers have developed a machine learning algorithm that allows healthcare facilities to forecast the chance of death for specific patients undergoing cardiac...

Scientists from the Max Planck Institute of Molecular Physiology, Germany, have developed a method, TomoTwin, an open-source general picking model for cryogenic-electron tomograms. The...

The University of Queensland researchers have developed a comprehensive plan outlining the integration of smartwatches into Australia's healthcare system. However, the researchers agree that...

Scientists from Seoul National University, South Korea, and the Max Planck Institute for Multidisciplinary Sciences, Germany, have developed a deep learning-based method called Foldseek,...

The genetic mechanisms underlying cancer have been the focus of research by scientists and medical professionals worldwide. The human genome has undergone random insertions...

Artificial intelligence (AI) and cellular biology have combined to change several sectors, including the mapping and monitoring of cellular activity within the human body,...

Neuroscientists from the University of Pittsburgh extend a previously developed hierarchical model of auditory categorization by including several adaptive neural mechanisms that aid auditory...

The emerging field of biocomputing holds immense promise for transforming both the realms of computing and medicine. With its potential applications ranging from early...

Scientists from the University of Washington, USA, studied how deep learning boosts and improves de novo protein binder design and devised a protocol for...

Recent achievements in the field of artificial intelligence (AI) have helped to develop effective medical imaging frameworks that can achieve professional clinical expertise. However,...

Machine learning-based methods have played a significant role in detecting RNA modifications. The advent of new high-throughput experimental and computational techniques has propelled the...

The primary objective of modern proteomics studies is to analyze and isolate the proteome of individual cells from a pool of similar cells. Existing...

Scientists from Amsterdam, Netherlands, have developed an automated and open-source workflow for the design of 3D fragment libraries in the KNIME software. Fragment-based drug...

Recent developments in comparative genomics studies, along with the availability of cutting-edge computational tools, have revived the study of evolutionary biology and genetics in...

Scientists from the University of Toronto, Canada, have developed a foundation model for single-cell analysis, scGPT, by generative pre-training on over ten million cells....

Using the heart as an investigational model, scientists at the Broad Institute of MIT and Harvard have designed an autoencoder-based machine-learning pipeline that can...

Scientists from the University of Saskatchewan, Canada, have performed a benchmarking analysis of the self-supervised contrastive learning methods used in image-based plant phenotyping. Plant...

The molecular surface of a protein is represented in the form of geometric and chemical attributes that create the unique fingerprint for identifying protein...

Scientists from the University of Southern California, USA, shed light on the computational approaches that are transforming the drug discovery process from computer-aided to...

Advancements in fluorescence microscopy-based imaging techniques have made it possible for researchers to view and analyze mitochondrial networks in 4D. Researchers at UCSD have...

Scientists from Columbia University, New York, have reported the possibility of automated cell type annotation in single-cell RNA seq (scRNA-seq) analysis using GPT-4, a...

Protein identification has gained much importance over the last few years. In the shotgun proteomics-based approach, peptide fragments are used to identify proteins. The...

There is a growing number of incidences of colorectal cancer in people under the age of 50 (EOCRC), but the intrinsic molecular mechanisms underpinning...

Advancement in the field of genome sequencing has seen an increase in the amount of sequence data. In spite of that knowledge regarding the...

Scientists from the University of Cambridge present Multifideity PubChem Bioassay, MF-PCBA, a collection of 60 molecular datasets with multiple modalities, reflecting the real-world nature...

The human microbiome is an essential aspect of the human body and could be responsible for several health conditions. Yet, much of microbiome transmission...