CHOP Researchers Unveil TEQUILA-seq: A Versatile and Affordable Tool for Targeted Long-Read...
Researchers from the Children’s Hospital of Philadelphia, Philadelphia, USA, have created a versatile, easy-to-implement, and low-cost novel technique, TEQUILA-seq, for synthesizing large quantities of...
Functional Unknomics: Exploring the Untapped Potential of Unknown Genes Leveraging Unknome...
Unstudied areas of life sciences, including uncharacterized or less characterized genes and proteins, have now got an exclusively dedicated repository through the recent works...
Empowering Medical Research with Drugst.One: A Seamless Plug-and-Play Approach for Online...
Researchers from the University of Hamburg, Germany, in collaboration with researchers from Denmark, Canada, the USA, Spain, Slovakia, and Israel, have designed Drugst.One, a...
Answering Genomics Questions with Precision: GeneGPT Bridges the Gap Between LLMs...
Scientists from the National Library of Medicine (NLM), National Institutes of Health (NIH), and University of Maryland, College Park, US, have presented GeneGPT, a...
Artificial Intelligence: The New Weapon in the Fight Against Infectious Diseases
Infectious diseases have been a persistent challenge to public health despite significant advancements in various scientific disciplines. The emergence of viruses resistant to drugs,...
Advancing Spatial Transcriptomic Cell-Type Deconvolution with SONAR: A Spatially Weighted Poisson-Gamma...
Scientists from the Chinese Academy of Sciences, China, introduce SONAR, a novel model for cell-type deconvolution from spatial transcriptomics data. This method, termed Spatially...
Meet inClinico: Transforming Clinical Trial Outcome Prediction Leveraging Artificial Intelligence
Researchers from Insilico Medicine designed and devised inClinico to predict Phase-II clinical trial outcomes. The transformer-based artificial intelligence software platform, inClinico, conjugates an ensemble...
Exploring Deep Learning Methods for Binding Affinity Prediction Across Proteins and...
To filter promising drug candidates early in the drug discovery process, it is imperative to accurately predict how well a protein and a potential...
Ameliorating the Chromatin Landscape: ChromaFold’s Accurate 3D Contact Map Prediction from...
USA-based researchers have formulated a supervised deep learning model, ChromaFold, that has achieved state-of-the-art performance in cell-type-specific prediction of 3D contact maps and regulatory...
Brock Researchers Develop AI-Powered Tool ‘DAPTEV’ to Design New Aptamer Drugs...
Traditional drug discovery and development methods are quite expensive, cumbersome, and prone to the biases of experts. A revolution in the field of drug...
Large Language Models and Foundation Models in Healthcare: Unveiling the Hype...
Standford researchers have discoursed the critical aspect for the integration of Foundation Models (FM) in the Healthcare system, that is evaluation of the reliability...
UCSD’s uDance: A Scalable Approach for Generating and Updating Phylogenies with...
uDance, a novel method that builds highly accurate and scalable phylogenetic trees using the divide and conquer approach, has been devised jointly by scientists...
Drug-GPT™ vs. ChatGPT: Comparative Analysis of GPT Language Models in Healthcare...
Scientists from Talking Medicine present a comparative analysis of three leading Generative Pre-trained Transformer (GPT) solutions - Drug-GPT™ 3, Drug-GPT™ 4, and ChatGPT -...
Connecting the Cellular Dots with treeArches: How Single-Cell Reference Mapping Constructs...
To deeply understand how tissues work in healthy and diseased conditions, it is imperative to collect vast amounts of data on individual cells. Such...
Unlock Cellular Mysteries with IndepthPathway: An Innovative Tool for Single-cell Sequencing...
Researchers from the University of Pittsburgh, USA, have made a momentous breakthrough in the realm of single-cell sequencing with the creation of IndepthPathway, an innovative...
Beyond Biopsies: Single-Molecule Cell-Free DNA Profiling Fuels Non-Invasive Cancer Screening and...
A new ray of hope for non-invasive cancer detection has emerged. A machine learning algorithm called GEMINI, created by John Hopkins University and Boston...
Decoding the Microbial Orchestra: A Breakthrough in Metaproteomic Data Analysis and...
In groundbreaking research, scientists from Brigham Young University, United States, have developed a cutting-edge deep learning computer model, Kaiko, with the unprecedented capability to...
Machine Learning Magic: DNABERT-2 Empowers Enhanced Multi-Species Genomic Analysis
The key to unlocking genomic secrets is here. Researchers from Northwestern University, in collaboration with Stony Brook University, have developed DNABERT-2, which is a...
Machine Learning Meets Virology: Scripps Scientists Unveil Tracking and Early Warning...
Imagine possessing the power to foresee the appearance of hazardous viral strains well in advance of their impact. The scientists at Scripps Research...
Predicting Binding Modes with Precision: CHARMM-GUI Empowers Reliable Ligand Binding Predictions
Researchers from Leigh University, United States, have developed a novel technique referred to as CHARMM-GUI protein-ligand docking (CGUI-IFD) to overcome the drawbacks associated with...
Automating CHARMM to GROMACS Force Field Porting with charmm2gmx: A Seamless...
Molecular mechanics (MM) calculations and molecular dynamics (MD) simulations are powerful tools used in biomolecular research, relying on accurate force fields (FFs) for reliable...
Meet TALKIEN: A New Tool to Decipher Molecular Crosstalk Through Ligand-Receptor...
Researchers from Bellvitge Biomedical Research Institute in Spain have designed TALKIEN (crossTALK IntEraction Network), a user-friendly online tool that helps to visualize molecular crosstalk...
Matching RNA Sequencing Alignment Data to Genotypes Made Easy with RNA...
Researchers from the Jackson Laboratory for Mammalian Genetics, USA, have built RNA Strain-Match, a quality control tool helpful in matching RNA data to their...
Exploring Uncharted Territory of Protein Folds Through De Novo Protein Design
Japanese scientists from the National Institute of Natural Sciences (NINS) and Osaka University have discovered novel protein folds. They created a well-defined set of...
ChatGPT meets DNA: DNAGPT, The Ultimate Tool for Multitasking DNA Sequence...
Motivated by the success of the GPT (Generative Pre-trained Transformer) model, researchers from the Southern University of Science and Technology, Tencent AI Lab, Shenzhen,...
Microsoft’s AI2BMD: Transforming Protein Dynamics Simulation with ab initio Accuracy
Microsoft Researchers from Beijing, China, have introduced an AI-Based ab initio Biomolecular Dynamics System (AI2BMD) for large biomolecule simulation by strategizing protein fragmentation scheme...
Treating Rare Cancers with CancerGPT: Cracking the Code on Drug Pair...
CancerGPT, an advanced machine learning model introduced by scientists from the University of Texas and the University of Massachusetts, USA, harnesses the power of...
The Shape Shifters of DNA: Exploring Dynamic Conformational Switching in TFIIH...
Scientists from Georgia State University, The University of Texas, and Lawrence Berkeley National Laboratory, USA, built models of transcription factor IIH (TFIIH) using cryo-electron...
Meet Uni-RNA: Universal Pre-trained Models Transforming the RNA Research Landscape
Uni-RNA, a context-aware deep learning model developed by DP Technology, Beijing, China researchers, delivers state-of-the-art performance in unwrapping structural, functional, and evolutionary information intercalated...
Meet Mapinsights: A New Toolkit for Impeccable Quality Control of High-Throughput...
High-Throughput Sequencing (HTS) has drastically transformed the world of genomics by allowing rapid and accurate detection of genomic variations at the level of individual...
Predicting Immunotherapy Response: Construction and Validation of a Machine Learning-Based Gene...
A recent publication in Nature's Communications Medicine has presented the TNBC (Triple Negative Breast Cancer) ICI (Immune Checkpoint Inhibitors) response predictive classifier (TNBC-ICI) integrating...
HyenaDNA Powers Long-range Genomic Sequence Modeling at Single Nucleotide Resolution
Scientists from Stanford and Harvard Universities have developed a groundbreaking genomic foundation model called HyenaDNA, which promises to transform the analysis of DNA sequences....
MIT’s Data-Efficient Molecular Property Predictor: Leveraging Hierarchical Grammar-Induced Geometry
Researchers at the MIT-IBM Watson AI Lab have achieved a significant breakthrough in the field of molecular property prediction. By introducing the Grammar-Induced Geometry...
Decoding the Epigenomic Puzzle: Evaluating Computational Pipelines for Single-cell Histone Modification...
Single-cell histone post-translational modification (scHPTM) assays, such as scCUT&Tag or scChIP-seq, have emerged as powerful tools for mapping epigenomic landscapes within complex tissues. These...
Meet ColabDock: A New Framework Integrating AlphaFold and Experimental Restraints for...
Scientists from Peking University, China, presented a new protein-protein docking framework, ColabDock, that incorporates experimental restraints into protein complex structure modeling with an aim...
AI Transforms CRISPR Technology: Accurately Predicting On- and Off-Target Activity of...
Artificial intelligence (AI) and CRISPR gene editing technological advancements have transformed the study of genetics. While CRISPR enables scientists to precisely change genes, AI...
Multiscale Pangenome Analysis: A New Tool “PGR-TK” Improves Representation of Repetitive...
An article published recently in Nature Journal introduced the PanGenome Research Tool Kit (PGR-TK) with the purpose of facilitating analysis of structural and haplotype...
GPT-powered Drug Discovery: Meet DrugGPT, the Game-Changing “ChatGPT” for Ligand Design
ChatGPT has become a rage all over the globe ever since its launch. From brainstorming business ideas to explaining complex code in the most clear-cut...
A Synergistic Approach: AlphaFold and Symmetrical Docking for Precise Protein Assembly...
Mads Jeppesen and Ingemar André from Lund University, Sweden, have demonstrated a protein complex assembly structure prediction pipeline conjugating Alphafold and symmetrical docking method....
Predicting Heart Attack Risk Faster and More Accurately than Current Methods:...
Occlusion myocardial infarction (OMI) impacts a large number of people, yet fewer get diagnosed. This is because their ECG fails to show an elevation in...
Guardians of Immunity: How T Cells Fight Diseases and Keep Us...
T cells are a category of immune cells. They play an important role in maintaining normal bodily functions and battling diseases. When faced with...
Innovating Molecular Simulations: Unleashing the Power of Artificial Intelligence for Revolutionary...
In a recently published paper by Peking University, China, researchers have outlined an analogy between the advancement of Artificial Intelligence (AI) technologies and the...
Predicting Childhood ADHD Symptoms: The Promising Role of Neurocognitive Assessments and...
A recent paper published in the Nature Journal has outlined a machine learning approach that predicts childhood attention-deficit/hyperactivity disorder (ADHD) symptoms by deploying information...
Deep Encoder-Decoder Network: A Tool for Fragment Linker Prediction in PROTACs...
PROTACs (PROteolysis TArgeting Chimeras) are small molecules capable of degrading target proteins. They have wide applications in designing drugs with therapeutic effects, especially in...
Transforming Healthcare: Empowering Clinicians with AutoPrognosis 2.0’s Democratized Machine Learning Models
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,...
Uncovering the Genetic Blueprint of Cotton: Scientists Sequence the Cotton Genome
Cotton, the primary source of natural fiber worldwide, has played a significant role in the textile industry. While several cotton species exist, only four...
Meet BioAutoMATED: Empowering Life Scientists with Automated Machine Learning for Analyzing...
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...
AI-Powered Protein-Protein Interaction Drug Discovery Pipeline Yields a Promising SARS-CoV-2 Inhibitor
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...
Discovering Genome-Wide Chromatin Contacts: Multiplex-GAM vs. Hi-C Showdown!
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...
Drug-Microbiome Interactions: Machine Learning Model Predicts How Drugs Affect Gut Microbiome
In a recent Nature publication by Algavi and Elhanan, faculties from Tel Aviv University, Israel, have tackled the challenge of fully understanding the adverse...
Must Read
Placing Every Atom Right: PEARL’s Deep Learning Approach to Drug Discovery
Genesis Molecular AI and NVIDIA have introduced PEARL (Placing Every Atom in the Right Location), a deep learning foundation model designed for large-scale protein–ligand cofolding...
Agentic AI Meets RNA‑seq: A New Co‑Pilot For Downstream Analysis
Next-generation sequencing has transformed gene expression profiling into a routine experiment, but interpreting those matrices remains a challenge for many labs. Researchers from Kyungpook...
Teaching Genomics Made Easy: Meet eduomics, the Automated Omics Simulation Pipeline
When researchers at the Department of Biology and Biotechnology, the University of Pavia, set out to rethink bioinformatics teaching. They started from a simple...
Unlocking Cellular Mysteries with CellReasoner: A New AI Tool for Biologists
In the rapidly evolving field of single-cell biology, accurately identifying cell types from complex datasets remains a cornerstone of research. A team of scientists...
Minimal Data, Maximal Impact: The Future of Peptide Design with MDMI
Peptides, which are short chains of amino acids, have become increasingly important in the world of medicine and biotechnology. Their unique properties make them...