Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and...
Deep learning-based virtual screening provides a more effective way to find molecules that resemble drugs, and virtual sources give chemists useful information. Leiden University...
Unveiling Flexiplex: A Versatile and Fast Demultiplexing and Sequence Searching Tool...
Omics datasets generated by high throughput sequencing contain vast amounts of nucleotide data that must be analyzed to extract meaningful biological insights. A common...
NIH’s All of Us Research Program Unveils 275 Million New Genetic...
The All of Us Research Program, with its ambitious objective of creating a diverse cohort of one million volunteers and making their data available...
Cracking the Code of Drug-Drug Interaction: DDIPrompt Unlocks a World of...
Adverse drug-drug interactions (DDIs) pose a major health risk when using drug combinations to treat complex diseases. However, predicting harmful DDIs is extremely challenging...
AlphaFind: A New Frontier in Proteomic Exploration
Effective structure-based search tools are necessary to efficiently organize the massive volume of data in the database. Novel tools like FoldSeek and 3D-surfer have...
Improving Patient Care: The Role of Large Language Models in Doctors’...
The digitization of health records has enabled powerful AI techniques to extract key medical insights from the vast trove of unstructured clinical notes. However,...
Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction...
Compound-protein interaction (CPI) prediction accuracy is crucial for drug discovery. Creating deep learning models that can be applied broadly requires expanding the CPI data...
OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis
OpenFold, an artificial intelligence (AI) research consortium, has announced the release of two new tools that aim to improve protein structure prediction: SoloSeq and...
Accelerating Cancer Research: MuSiCal Offers Accurate and Sensitive Mutational Signature Analysis
Cancer is a complex disease. It is brought on by the accumulation of several gene alterations. Understanding the patterns of these alterations, or mutational...
Unveiling DeepGO-SE: Advancing Protein Function Prediction Leveraging Language Models and GO...
Gene Ontology is an axiomatic theory that describes the molecular roles, biological processes, and cellular placements of proteins using more than 100,000 axioms. Learning...
Meet DNABERT-S: Illuminating Genomic Diversity through Species-Aware DNA Embeddings
For scientists studying the functions of the genome, DNA embedding is a vital tool. Effective investigations like species categorization and metagenomics binning are made...
A Novel GNN Model ‘PathFormer’ Revolutionizes Highly Accurate Disease Diagnosis and...
When analyzing omics data, regression analysis is an essential tool for identifying biomarkers. For the analysis of graph-structured data, graph neural networks (GNNs) are...
University of Michigan Researchers Discover Novel Plant Protein Fold with Potential...
Researchers from the University of Michigan have reported the discovery of a new plant protein fold that catalyzes the formation of macrocyclic peptides through...
Meet Proteus: Transforming the Landscape of Protein Design with Innovation and...
Proteins perform essential functions in living organisms and adopt specific three-dimensional structures dictated by their amino acid sequences. The ability to accurately design novel...
DANCE Unveils Hidden Depths of Protein Movement, Paving the Way for...
One must understand proteins' structural flexibility in-depth to comprehend their role in biological processes and functional systems. It is still challenging to predict various...
Beyond One-Size-Fits-All: Moffitt Unveils First Individualized Predictive Model for the Treatment...
Patients with recently diagnosed non-differentiated multiple myeloma (NDMM) have a wide range of outcomes, with overall survival (OS) spanning from several months to more...
Unlocking the Potential of RNA Design with Generative AI using GenerRNA
A team of researchers from the University of Tokyo developed GenerRNA, the first large-scale pre-trained AI model for automated RNA design that does not...
GPCR-BERT: Revolutionizing GPCR Research with Protein Language Models
Recent advances in large language models (LLMs) and transformers have opened new possibilities for modeling protein sequences as language. Carnegie Mellon University researchers have...
tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling...
The soldiers of our immune system, antibodies, bind to specific targets like viruses and toxins and neutralize them. Predicting antibody-antigen complex structures accurately has...
Choosing the Best Tool for Identifying Transcriptional Regulators: Navigating the NGS...
This article delves into a recent study undertaken by a team of researchers that examined multiple computer algorithms for transcriptional regulator prediction using Next-Generation...
Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary...
Before understanding RNA biology, one must grasp the three-dimensional structure of RNA. Because experimental procedures require a lot of labor and money, computer approaches...
Making AI-Driven Structural Biology Accessible with Foldy
Recent breakthroughs in AI-based protein structure prediction have enormous potential to accelerate discoveries across the life sciences. However, major barriers persist in making these...
MarkerGeneBERT: Revolutionizing Cell Marker Extraction Utilizing Natural Language Processing
MarkerGeneBERT, a natural language processing (NLP) system to automatically extract cell type markers from single-cell sequencing literature by parsing full text, was recently introduced...
CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms...
Deep learning models like RosettaFold and AlphaFold2 can predict protein structure with high accuracy; however, they still have difficulties when it comes to intricate...
Unleashing nanoBERT: Revolutionizing Nanobody Therapeutics with Deep Learning
Scientists from the University of Southern Denmark, NaturalAntibody and Alector Therapeutics unveil nanoBERT, a nanobody-specific transformer designed to predict amino acids in specific positions...
UChicago Scientists Crack the Code of HIV Entry into the Nucleus...
In a major scientific breakthrough, researchers at the University of Chicago have succeeded in creating a comprehensive model of the nuclear pore complex with...
reguloGPT Unleashed: GPT-Powered Knowledge Graphs Illuminate Molecular Regulatory Pathways
Understanding biological processes and offering organized representations of intricate relationships are made possible by Knowledge Graphs, or KGs. However, the resources available today to...
Has ESM-2 Truly Learned the Language of Protein Folding?
Protein structure prediction and design may be accomplished using protein language models (pLMs). They may not completely comprehend the biophysics of protein structures, though....
Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training...
Harvard University researchers introduce RNA3DB, a dataset crafted from the Protein Data Bank (PDB), addressing challenges in RNA structure prediction. In response to limitations...
Revolutionizing Protein-protein Interaction Prediction with LazyAF: A Breakthrough Pipeline for Medium-scale...
Predicting protein structures has been transformed by artificial intelligence. However, rather than competence, accessibility, and ease of use are increasingly becoming limiting issues for...
Unlocking the Enhancer Code: Deep Learning’s Role in Designing Cell-specific Genetic...
Transcriptional enhancers control the spatiotemporal activation of the target genes they regulate by serving as docking stations for various transcription factor combinations. It has...
Probing Ancestral Genomes Uncovers Unannotated Degenerate Transposable Elements Contributing to Gene...
Transposable elements (TEs) supply genomes with both coding and non-coding sequences and have significant roles in evolution. However, the extent of TE annotations in...
Meet IntegrAO: A Novel Unsupervised Framework for Integrating Incomplete Multi-omics Data...
Advances in high-throughput omics profiling have improved cancer patient classification significantly. However, insufficient data in multi-omics integration is a big problem because conventional techniques...
Unlocking Cellular Mysteries with scPerturb: A Deep Dive into Harmonized Single-cell...
Molecular and phenotypic responses to numerous perturbations are revealed by the increasing number of single-cell perturbation studies. However, variations in format, naming conventions, and...
PepHarmony: An Integrated Sequence and Structure-based Peptide Encoding Framework Employing Multi-view...
Gaining insight into the relationship of the Peptide sequence (the amino acid sequence) and their structure (the way they fold and interact) is a...
Empowering Researchers with ProteomicsML: An Online Oasis of Data Sets and...
The laborious aspects of acquiring and curating data sets for machine learning, especially in proteomics-based systems, present unique difficulties because there is a significant...
The Human Immunome Project: Mapping the Global Landscape of Immune Diversity...
In a landmark initiative, the Human Immunome Project (HIP) commenced at a summit in La Jolla, California, bringing immunology specialists together to address the...
Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis...
The field of biological sequence analysis has lately benefited from the revolutionary changes brought about by the development of self-supervised deep language models for...
IntelliGenes Unveiled: A New Paradigm for AI-Driven Biomarker Discovery from Multi-genomic...
IntelliGenes is a new machine learning pipeline developed by researchers at The State University of New Jersey that integrates multi-genomics, clinical, and demographic data...
Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models...
The drug development process involves a winding trail across the enormous chemical wilderness, looking for compounds that interact ideally with their target proteins. Traditional...
Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution
Protein design has seen significant progress, but a comprehensive deep-learning framework for protein design, including de novo binder design and higher-order symmetric architectures, remains...
Cleveland Clinic and IBM’s Blueprint for Discovering Novel Immunotherapy Targets Using...
Predicting the immunogenicity of peptide antigens attached to major histocompatibility complex (MHC) molecules is critical for developing new immunotherapies and better understanding human immune...
Transforming Protein Engineering with UW-Madison’s Self-Driving Labs ‘SAMPLE’: A Cutting-edge, AI-driven...
Although the field of protein engineering offers countless applications in chemistry, energy, and medicine, the process of designing new proteins with enhanced or unique...
Meet ChatDrug: A New ChatGPT-powered Conversational Drug Editing Framework
Drug discovery is one of the many fields where recent developments in conversational large language models (LLMs), like ChatGPT, have shown incredible promise. However,...
MIT Introduces PRISM: Advancing Early Detection of Lethal Pancreatic Cancer with...
Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive cancer with a poor prognosis, owing mostly to late diagnosis. Expanding screening beyond the 10% now...
Unlocking Brain Mysteries with BrainLM: A Versatile Foundation Model for Recording...
The Brain Language Model (BrainLM), a foundation model for brain activity dynamics trained on 6,700 hours of functional magnetic resonance imaging (fMRI) scans, was...
MIT’s Noninvasive Technique “Raman2RNA” Reveals Cells’ Gene Expression Dynamics Over Time
Understanding cell dynamics, regulation, and characteristics has been revolutionized by profiling tests at a previously unheard-of resolution. Nevertheless, the destructive nature of these techniques...
The Glue that Heals: St. Jude’s Researchers Unveil Molecular ‘Super-Glue’ Propelling...
Scientists at St. Jude Children's Research Hospital have published their findings on SJ3149, a chemical with broad efficacy against various cancer types, particularly acute...
Fighting Pathogens Smarter: How Machine Learning and Data Integration Improves Bacterial...
CRISPR interference (CRISPRi) is one of the most widely used CRISPR technologies in bacteria. In this, a catalytically dead Cas protein incapable of DNA...
Mapping Cancer’s Weaknesses: A Comprehensive Map of Cancer Cell Dependencies Accelerates...
Cancer, a simple name for a complicated group of diseases, has long perplexed scientists and healthcare professionals alike. Despite years of research and medical...
Must Read
D-I-TASSER Outperforms AlphaFold? A New Frontier in Protein Structure Modeling
The requirement and utility of conventional force field-based folding simulations have been called into question by the overwhelming success of deep learning techniques in...
Unlocking Biomolecular Secrets with AF3Score: A Leap Forward in Structural Evaluation
Researchers from Changping Laboratory in Beijing introduced AF3Score, a novel adaptation of AlphaFold3 designed to evaluate biomolecular structures with unprecedented accuracy. This innovation addresses...
Overlapping Genes, Unfolding Insights: Synthetic Biology Meets AI
Given that the sharing of codon nucleotides dramatically reduces the size of protein sequences, viruses in nature often generate overlapping genes (OLG) in alternate...
PhysDock: A New Era in Protein-Ligand Docking with AI and Physics
In a breakthrough that could transform drug discovery, a team of researchers from ShanghaiTech University has introduced PhysDock, a novel AI-powered model designed to...
Advancing Enzyme Design: RFdiffusion2 Enables Atomic-Level Scaffold Generation
In de novo enzyme design, the functional groups surrounding reaction transition states are described in the optimal active site. There are drawbacks to the...