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Meet DiNiro: An Interactive Platform for Single-cell RNAseq-based Gene Regulatory Network Analysis

Scientists from the University of Hamburg, Germany, have developed a novel methodology, DiNiro, for unraveling differential regulatory disease mechanisms from single-cell RNA-seq data. Computational...

New Study Aims to use Machine Learning to Explore the Surprising Relationship Between Oral Infections and Cardiovascular Disease

According to a new study presented at the 52nd Annual Meeting & Exhibition of the AADOCR, held in conjunction with the 47th Annual Meeting...

Exploring the Potential of DALL-E 2 for AI-driven Image Generation in Radiology

In the field of radiology, generative models, notably DALL-E 2, have tremendous promise for image production and modification. Scientists have shown that DALL-E 2...

The Future of Cancer Care: Explainable AI Detects Diagnostic Cells of Genetic AML Subtypes

Scientists from Germany have developed SCEMILA, an inherently explainable AI tool for identifying diagnostic cells of acute myeloid leukemia (AML) subtypes. The authors find...

Meet PAthreader: A Powerful Tool for Protein Structure and Folding Pathway Prediction using Remote Homologs Recognition

Scientists from the Zhejiang University of Technology, China, have proposed a new method, PAthreader, to improve the recognition accuracy of remote homologous structures by...

New Study Reveals Gene Mutation that Controls Pain Sensitivity

The experience of pain is complicated, subjective, and unique to each person. While some people have a high pain tolerance, others may regard even...

Pushing the Limits of Protein Detection: The Role of Machine Learning

The detection of biomolecules at the nanoscale is of great significance in fundamental biology research, just as it is for biomedical investigations. The evolution...

New Study Shows Pan-variant mRNA-LNP T Cell Vaccine Proves Effective Against SARS-CoV-2 Beta

Current COVID-19 vaccines induce neutralizing antibodies that can inhibit viral entry, but their efficiency decreases when new variations arise. On the basis of short...

Bridging the Gap between Cheminformatics and Machine Learning to Investigate Androgen Receptor Antagonists in the Fight Against Prostate Cancer

Researchers from Thailand perform a systematic cheminformatics analysis and machine learning modeling to study how human Androgen Receptors (AR) antagonists combat Prostate cancer, one...

AI-Powered Structural Proteomics Unveils New Insights into Protein Complexes in Cells

Molecular biology is being revolutionized by the application of artificial intelligence to simulate the structures of proteins and their complexes. Researchers utilized a combination...

Scientists Introduce “MZmine3” for Processing Big Data to Identify Hidden Chemicals in Complex Mixtures

Scientists from Prague have developed MZmine3, a scalable platform for the analysis of mass spectrometry (MS) data from different instrumental setups. The platform supports...

Predicting Drug-target Interactions using Protein Features and Wrapper Feature Selection

The prediction of drug-target interactions (DTI) plays a significant role in drug development by helping in the identification of new drug targets, the repurposing...

Transformers in Action: Deep Learning Aided Cardiac Patient Mortality Risk Prediction using Electronic Health Records

Scientists from Finland have studied and explored two transformers (deep learning models), BERT and XLNet, in the context of predicting 6-month mortality in cardiac...

Insight into Structural Features of Hepatitis E: Princeton Researchers Discover New Path for Treatment

Scientists from Princeton University have developed a comprehensive model of the structure and function of the open reading frame (ORF) 1 of Hepatitis E...

NeuronChat Sheds Light on Neuron-Neuron Communication in the Brain through Single-cell Transcriptomics Analysis

Scientists from the University of California, Irvine, have developed NeuronChat for inferring inter-neuronal communication using single-cell transcriptomics data. Previous cell-cell communication inference methods are...

From Cell Cultures to Intelligent Systems: “Organoid Intelligence” is the New Energy-efficient Biocomputing Alternative to Artificial Intelligence

Scientists from Johns Hopkins University lay out the possibility of energy-efficient biocomputing using brain organoids (3D brain cell cultures) that surpass in-silico computing capabilities. The recent...

Improving the Accuracy of RNA-protein Complex Structure Prediction with DRPScore: A Deep Learning Algorithm

Scientists have developed a new deep-learning-based approach called DRPScore for identifying native-like RNA-protein complexes essential for understanding cellular processes. DRPScore outperforms existing methods in...

Repurposing Drugs Simplified with ASGARD: A Single-cell Guided Pipeline

Scientists from the University of Michigan have developed a single-cell guided pipeline to aid the repurposing of drugs (ASGARD) by defining a drug score...

Designing High-Activity Luciferases with Deep Learning: A Promising Approach for Enzyme Design

For many years, scientists have been baffled by the difficult task of designing enzymes, which is regarded as one of the most difficult challenges...

LongBondEliminator: A Novel Approach to Streamlining Molecular Dynamics Simulations

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

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Penn Scientists Introduce 'PocketMiner' for Predicting Cryptic Pockets in Proteins and Expanding the Druggable Proteome

Penn Scientists Introduce ‘PocketMiner’ for Predicting Cryptic Pockets in Proteins and Expanding the Druggable...

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The discovery of cryptic pockets has widened the scope of drug development by permitting the targeting of proteins previously deemed undruggable due to the...
Integrated Gut-Liver-on-a-chip 'iGLC' Platform: an Innovative Human Model for Non-Alcoholic Fatty Liver Disease

Scientists Introduce Integrated-gut-liver-on-a-chip ‘iGLC’ Platform: an Innovative Human Model for Non-Alcoholic Fatty Liver Disease

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Scientists from Kyoto University, Japan, have developed an integrated gut-liver-on-a-chip platform as an in-vitro human model for the study of non-alcoholic fatty liver disease...
Machine Learning Programs Predict Risk of Death based on Routine Hospital Tests Data

Revolutionizing Healthcare: Machine Learning Programs Predict Risk of Death based on Routine Hospital Tests...

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Healthcare providers have been using routine hospital tests to evaluate patients' health for decades. Electrocardiogram (ECG) tests are frequently a part of these tests....
Machine Learning-aided Multiscale Transcriptomics Results in Pediatric Cancer Atlas for Diagnostic Classification

Machine Learning-aided Multiscale Transcriptomics Results in Pediatric Cancer Atlas for Diagnostic Classification

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Scientists from The Hospital for Sick Children, Toronto, have developed an atlas for childhood cancer diagnostic classification using machine learning approaches. Pediatric cancers are...
Transforming Protein Design with "ProT-VAE": A Novel Approach Made Protein Engineering Easier with Deep Learning

Transforming Protein Design with “ProT-VAE”: A Novel Approach Made Protein Engineering Easier with Deep...

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Due to the absence of adequate theoretical models and the enormous protein sequence space, the data-driven design of proteins with particular functions is difficult....