PROTACs (PROteolysis TArgeting Chimeras) are small molecules capable of degrading target proteins. They have wide applications in designing drugs with therapeutic effects, especially in...

A recent paper authored by researchers from the University of California, USA, and the University of Cambridge, UK, introduced an open-source Machine Learning framework,...

Cotton, the primary source of natural fiber worldwide, has played a significant role in the textile industry. While several cotton species exist, only four...

BioAutoMATED, a novel, automated machine-learning tool, has eliminated the biggest barrier preventing life scientists from effectively utilizing machine learning (ML) in the analysis and...

The multi-adaptive Support Vector Machine Learning Algorithm (maSVM) can improve comparisons between binary Protein-Protein interaction datasets gathered in different laboratories and can be utilized...

Chromatin conformation capture techniques have revolutionized our understanding of genome organization and its impact on gene regulation. Hi-C, the gold standard method for investigating...

In a recent Nature publication by Algavi and Elhanan, faculties from Tel Aviv University, Israel, have tackled the challenge of fully understanding the adverse...

Large-scale proteome and genomic investigations play a crucial role in understanding the molecular causes of cancer. The National Cancer Institute's Clinical Proteomic Tumor Analysis...

The researchers managed the challenge of quantification, simulation, and weight appointment to counterfactuals and diversely heterogeneous sets of factors accountable for the dynamism of...

Transcriptomics has revolutionized our understanding of gene expression and its impact on biological processes. High-dimensional transcriptomics data provides researchers with much information, but analyzing...

The Human Lung Cell Atlas (HLCA) represents comprehensive single-cell transcriptomics of the human respiratory system, which aims to resolve the limitations in previous atlases....

The field of cell biology is undergoing rapid advancement, necessitating a comprehensive comprehension of the intricate dynamics and heterogeneity exhibited by individual cells in...

Drugs often impact intracellular off-targets, i.e., targets that are unintended. Identifying drug off-targets is extremely important for understanding the mechanism of drug action and...

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...