Large Language Models Offering Solutions to Tackle Biological Complexity
Large Language Models (LLMs) have emerged as dynamic tools with the ability to transform the landscape of biological research in a world driven by...
Meet Flow: An Ultimate Bioinformatics Data Analysis and Management Solution
Scientists at King's College London, UK, and collaborators have introduced 'Flow,' an open-access web platform to perform bioinformatics analysis. Flow provides the capability to...
ChatGPT Empowers Clinical Decision Making with Impressive Accuracy
The large-language model (LLM)-based model, ChatGPT, had its clinical decision-making abilities put to the test in a joint study by researchers from Harvard Medical...
Revolutionizing Parkinson’s Care: Harnessing Artificial Intelligence to Detect Disease Severity at...
A team of researchers has recently developed an Artificial Intelligence (AI) based model for detecting the severity of the disease's progression and its symptoms...
Oxford Researchers Develop a Machine Learning Model to Predict 10-Year Breast...
A group of researchers affiliated with Oxford University, UK, have developed a prognostic model backed by the most extensive information set spanning a national,...
Meet FateMap: A Barcoding Approach to Decode Why Certain Cells Resist...
A collaborative research effort led by scientists and engineers at the University of Pennsylvania and Northwestern University led to the development of FateMap, a...
Decoding Thoughts into Words: A Breakthrough Brain-Computer Interface Lets Paralyzed Woman...
In a groundbreaking advancement, researchers from Stanford University have developed a speech brain-computer interface (BCI) that holds significant promise for individuals with paralysis. By...
From Algorithms to Antibiotics: Harnessing Artificial Intelligence in the Search for...
Faculties of the Mathematics Department at the University of Warsaw, Poland, have presented a review of the past two years progress of Artificial Intelligence...
Scientists Assemble the First Complete Human Y Chromosome Sequence: A Milestone...
The sequencing and assembly of the human Y chromosome have been challenging due to its intricate repeat structure, which encompasses lengthy palindromes, tandem repeats,...
Unveiling Cellular Secrets: Visualizing Dynamic Biomolecular Machinery with CryoDRGN-ET
The advancement of cryo-electron tomography (cryo-ET) has opened novel avenues for visualizing the intricate structures of dynamic macromolecular assemblies within their natural cellular surroundings....
AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein...
The University of Toronto researchers have explored the potential of Chemical Language Models (CLMs) to thrive as Biological Learning Models. In contrast to popular...
Stanford’s GEARS: An Innovative Approach to Predicting Transcriptional Outcomes of Multigene...
Understanding cellular responses to genetic changes holds vital importance in various biomedical contexts, such as uncovering cancer-related genetic interactions and advancing regenerative medicine. However,...
Meet DeepTracer-Refine: An Automated Refinement Approach for AlphaFold2 Predicted Protein Structures
Scientists of the DeepTracer project have formulated DeepTracer-refine, an automated pipeline that consolidates the advantages of sequence-to-model and map-to-model strategies, complements their shortcomings, and...
Meet OpenFold: Reimplementing AlphaFold2 to Illuminate Its Learning Mechanisms and Generalization
Columbia University and Harvard University researchers have developed OpenFold—a swift, memory-efficient, trainable AlphaFold2 implementation. They aimed to address the shortcomings of the revolutionary AlphaFold2,...
Tuft’s Researchers Unveil MELISSA: Revolutionizing Protein Function Prediction Through Semi-Supervised Embedding
Tufts University researchers have developed MELISSA, a groundbreaking approach for predicting protein functions through protein-protein association networks. Existing methods such as Mashup and deepNF...
Astrocyte-Powered Transformers: A Biological Blueprint for High-Performance Neural Architectures
Researchers affiliated with the MIT-IBM Watson AI Lab and Harvard Medical School have proposed a hypothesis of Transformer’s core computational schemes in order to...
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...
Must Read
Solving a Long-Standing Genomics Bottleneck: KAIST Proposes AI-Powered Strategy for Gene Function Prediction
KAIST and UCSD researchers proposed AI-driven strategies for microbial gene function discovery, addressing the long-standing bottleneck where many microbial genes remain uncharacterized despite advances...
AI-Powered Metagenomics: How MetagenBERT Predicts Disease From Raw DNA Sequences
Researchers from Sorbonne University and Dauphine University, France, introduced MetagenBERT, a Transformer-based framework for disease prediction directly from raw metagenomic DNA without relying on...
ToposBio Unveils Topos-1: An All-Atom Foundation Model for Intrinsically Disordered Proteins
Intrinsically disordered proteins (IDPs) are proteins that are central to neurodegenerative diseases and aggressive cancers like prostate cancer, have been considered ‘undruggable’ as structures...
CleaveNet Enables Scalable and Targeted Protease Substrate Design for Diagnostics and Therapeutics
Scientists from MIT and Microsoft Research present CleaveNet, an AI-based pipeline that merges predictive and generative modeling for end-to-end peptide (short protein) design. By...
Advancing Peptide Therapeutics with PeptiVerse’s Unified Prediction Framework
Researchers at the University of Pennsylvania developed PeptiVerse, a single platform that predicts drug-related properties of therapeutic peptides using either amino acid sequences or...