Efficiently Identifying Bispecific Antibodies using High Throughput Single-cell BsAb Discovery Pipeline
Bispecific antibodies (BsAbs) are an emerging type of immunotherapy and have great potential to treat various diseases. Recently, researchers have developed a novel single-cell...
Overcoming Challenges in Detecting and Quantifying Splicing Variations in Large RNAseq...
Scientists from UPenn have developed a suite of tools and algorithms for analyzing heterogeneous and large RNAseq datasets for detecting, quantifying, and visualizing the...
KCL Researchers Develop DNAscan2: A Highly Flexible, End-to-End Pipeline for NGS...
Next-generation sequencing (NGS) is becoming increasingly accessible and affordable, illustrating its growing importance and adoption in the field of clinical and biomedical genetics. To...
Transforming Functional Genomics Research using EN-TEx: A Resource of Multi-tissue Epigenomes...
Recently, a paper published on Cell reports the EN-TEx, a system/project that challenges conventional functional genomics research by providing a comprehensive resource that goes...
Recent Research Unveils New Genomic Landscape of the Human Gut Microbiome
Scientists from BGI-Research developed a new version of the Cultivated Genome Reference (CGR), a repository of high-quality draft genomes of the human gut microbiome....
Using Virtual Reality-based Real-time Imaging to Unravel the Complexities of Autism’s...
Neuropsychiatric disorders are a serious public health concern, given that they are the leading cause of disability and account for millions of deaths worldwide....
MIT’s DiffDock: A Breakthrough Diffusion Generative Model-based Approach for Molecular Docking
Researchers at the Abdul Jameel Clinic for Machine Learning in Health, MIT, have developed a novel method, DiffDock, an accelerated drug discovery pipeline using...
Researchers Introduce PALMO: A Novel Software Platform for Longitudinal Multi-omics Data...
In the past few years, there has been a significant increase in multi-omics data generation for biomedical research. However, the analysis of these large-scale,...
Enzyme Function Prediction from Amino Acid Sequence: How AI is Leading...
An innovative artificial intelligence program called CLEAN (contrastive learning–enabled enzyme annotation) has the ability to predict enzyme activities based on their amino acid sequences,...
Enhancing De Novo Drug Design with QADD: A Powerful Combination of Reinforcement Learning...
Scientists from Shanghai have developed a de novo drug design method, QADD (quality assessment-based drug design approach). The multi-objective reinforcement learning-based method is capable of designing...
Precise Protein-Ligand-Binding Site Mapping with ‘SiteRadar’: A Graph Machine Learning Algorithm
The identification of ligand-binding sites on the surface of a protein is a vital aspect of structure-based drug design. SiteRadar is a new algorithm...
Why the Shape of Your Heart Could be the Key to...
Recent findings by the Smidt Heart Institute based on deep learning analysis of medical images suggest, that one's likelihood of developing atrial fibrillation and...
Researchers Offer an Innovative Single Test-Based Approach for Early Stage Cancer...
Conventionally, cancer diagnostic procedures have been known for their invasive nature and enormous cost. However, researchers from KAIST and Korea University have developed a...
LLNL Scientists Introduce Cutting-edge Theoretical Model for More Efficient Simulations of...
Lawrence Livermore National Laboratory, California's scientists have developed a theoretical model based on Dynamic Density Functional Theory (DDFT) for modeling multicomponent cellular membranes as...
Evaluating the Efficacy of Deep Learning Algorithms for Predicting Drug Synergy...
Cancer therapies often become ineffective due to the development of resistance in the tumor cells against the treatment. One potential strategy to overcome this...
Novel Workflow Uses Targeted Computer Modeling to Predict Druggable Targets Against...
Scientists from the University of Tübingen, Germany, have developed a novel workflow for predicting robust druggable targets against emerging viral infections such as the...
Unravelling Spatial Transcriptomics: A Benchmark Study of Cellular Deconvolution Methods
A recent study published in Nature Communications comprehensively evaluated computational methods used for spatial transcriptomics data analysis. The scientists investigated how well various advanced computer methods...
Penn Scientists Introduce ‘PocketMiner’ for Predicting Cryptic Pockets in Proteins and...
The discovery of cryptic pockets has widened the scope of drug development by permitting the targeting of proteins previously deemed undruggable due to the...
Scientists Introduce Integrated-gut-liver-on-a-chip ‘iGLC’ Platform: an Innovative Human Model for Non-Alcoholic...
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...
Revolutionizing Healthcare: Machine Learning Programs Predict Risk of Death based on...
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...
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...
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....
Meet DiNiro: An Interactive Platform for Single-cell RNAseq-based Gene Regulatory Network...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Meet DeepBIO: An Automated Deep Learning Platform for High-Throughput Functional Analysis...
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...
NHGRI’s Verkko Algorithm: An Advancement in Genome Assembly with Notable Limitations
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: State-of-the-Art Technology and Future Prospects
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...
Big Data Analytics Reveals New Causal Pathways in Alzheimer’s Disease
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,...
Whole-Genome Population Genomics Made Easy with “PRAWNS”: A Comprehensive Tool for...
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...
From healthy cell to cancerous growth: the alarming role of “poisoned”...
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....
Meet MinsePIE: A ML Tool to Predict Successful Insertion of Gene-edited...
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...
Local Creek Holds Secret to Fighting Deadly Infections: Newly Discovered Virus...
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...
Must Read
Designer Miniproteins: New Frontier in GPCR-Targeted Drug Development
G protein-coupled receptors (GPCRs) are essential membrane proteins with dynamic conformations that are also major targets for drug development and discovery. However, designing protein...
Meet AgentRxiv: A Collaborative Framework for AI Research Agents to Accelerate Discovery
Hundreds of scientists come together through collaborative efforts to accomplish a shared goal during scientific discovery processes. Current workflows generate research independently, yet they...
MolAI: The Deep Learning Model Transforming Molecular Descriptor Generation
Recent years have witnessed significant advancements in the fields of artificial intelligence (AI) and machine learning (ML), catalyzing a revolution in cheminformatics and drug...
Dyna-1: Unraveling Protein Dynamics with Deep Learning and NMR Data
There are more than 100 NMR relaxation datasets in the Biological Magnetic Resonance Data Bank (BMRB), which show an observable motion in µs-ms. NMR...
A New Roadmap for Precision Medicine: Overcoming Challenges with Post-Genomic Data
Advancements in precision medicine have long promised a future where treatments are tailored to individual genetic profiles. However, despite significant progress in genomics, the...