Advancing Protein Function Prediction: ProtEx’s Exemplars-based Retrieval-Augmented Approach
The challenge of connecting a protein sequence to its fundamental biological function is becoming more and more significant in the field of biology. The...
DeltaDock: Streamlining Molecular Docking with a Unified, Reliable Framework
DeltaDock is a novel two-stage framework capable of performing molecular docking, which has not been achieved before. It does so by combining the strengths...
Deep Learning Models in Pathogenicity Prediction: Insights from Hereditary Breast Cancer...
Deep learning models have been used to predict the pathogenicity of mutations in hereditary breast cancer gene variants in the UK Biobank. Here, researchers...
Meet BioFunctional: A Comprehensive Tool for KEGG Pathway and Gene Ontology...
In the field of biological research, understanding the relationship between different biological components and their function is complicated. Functional analysis, a part of computational...
InstructBioMol: Empowering Researchers to Design Biomolecules through AI and Human Collaboration
Drug discovery, synthetic biology, and enzyme engineering are all dependent on the ability to comprehend and create biomolecules, such as proteins and tiny molecules....
Computing the Human Interactome: A Deep Dive into Protein Interactions
A recent study by a team of researchers has made significant strides in unraveling this complex puzzle of human interaction. The human interactome encompasses...
Understanding FlexLMM: A Nextflow Framework for Genome-Wide Association Studies
Genome-wide association Studies (GWAS) consider sequencing the DNA of a person and then comparing it with a population to find genetic markers associated with...
Meet metagWGS: A Flexible Workflow for Comprehensive Metagenomic Data Processing
An increasing number of studies employ metagenomic analyses to investigate the taxonomy and function of microorganism communities. In many microbial research, one typical job...
Cleveland Clinic and IBM Leverage AI to Revolutionize Drug Discovery for...
In drug development, it isn't easy to learn molecular representation from chemical structures since traditional molecular representation techniques, such as sequence-based and graph-based approaches,...
The Protein Revolution: 2024 Nobel Prize in Chemistry Pioneers Protein Design...
In a groundbreaking announcement that has sent ripples through the scientific community, the Royal Swedish Academy of Sciences has awarded the 2024 Nobel Prize...
PlasmidGPT: Transforming Plasmid Design with Generative AI
Recent research shows that within the domain of synthetic biology, there have been tremendous improvements, especially in designing and engineering biological systems. Plasmids, crucial...
BindCraft: Redefining Protein Binder Design with AI and One-Shot Precision
All important biological processes revolve around protein-protein interactions (PPIs'). Designing PPIs' is difficult, nonetheless, because of the intricate structural characteristics that define them. Researchers...
ProteusAI: Making Protein Design and Engineering Accessible to All
Protein structure prediction is a pretty big challenge in the field of bioinformatics as it depends on a multitude of factors. Imagine trying to...
Malaria Research Milestone: Scientists Design New Drug to Fight Drug-Resistant Malaria
Researchers from Yale University and other institutions have identified MED6-189 as a new antimalarial drug, a new development that might change the dynamics of...
The Future of Protein Engineering: Exploring the Potential of CodonMPNN
Making synthetic protein sequences from protein structures is a powerful use of protein engineering technology. It can be challenging to create designed proteins, though,...
MedChem Game: Gamifying Drug Discovery with AI on Your Android
Improved computational tools and artificial intelligence significantly improve drug discovery. This process has automated activities like molecular docking and predictive modeling to discover candidates...
Expansion in situ Genome Sequencing: A New Tool for Studying Nuclear...
The investigation of nuclear anomalies and how they influence the regulation of genes warrants analysis of various cellular functions and diseases. The researchers from...
How ChemNet is Revolutionizing Protein-Small Molecule Conformational Modeling
Modeling of protein-small molecule systems offers advantages in speed and generality for exploring interactions with small molecules in the folded state; the modeling of...
Top 5 Laptops for Bioinformatics
Bioinformatics is a rapidly growing field that blends biology, computer science, and data analysis to make sense of biological data. This field is growing...
Breaking New Ground in Protein Function Prediction with Protein-Mamba
Determining the function of proteins is one defining aspect of molecular biology that also carries great potential in drug discovery and development. A better...
The Future of Cell Modeling: Building Virtual Cells with Artificial Intelligence
One of the most important concepts in biology is the cell, which is perhaps the smallest unit of life. This understanding and identifying the...
Unleashing the Power of Dynamics: A 4D Diffusion Approach to Protein...
The ability to anticipate the structure of proteins is essential for improving biological research, developing new pharmaceuticals, and designing experiments. It also helps to...
Everlasting Memory: Storing the Human Genome on a 5D Crystal
In a remarkable corridor of achievement, the scientists of the University of Southampton have reputedly gotten the ability to conserve the complete human genomic...
Unveiling Druggable Pockets with PocketVec: A Comprehensive Approach with Binding Site...
Target-based drug development depends heavily on characterizing druggable pockets, which are protein areas with the capacity to bind organic small molecules. Nevertheless, the process...
WikiPathways 2024: A Next-Generation Pathway Database
WikiPathways is an open-access biological pathway database that was first launched in 2007. It is still being developed and updated by a group of...
Speed and Precision in Medical Imaging: The Promise of ScribblePrompt
Clinical care as well as scientific research depend heavily on biomedical image segmentation. Certain biomedical picture segmentation tasks can be accurately automated by deep...
Personalizing Pangenomes: A New Approach to Reduce Reference Bias
In a groundbreaking study published in Nature Methods, a group of scientists consisting of the UC Santa Cruz Genomics Institute, University of Ferrara, Google...
ProteinBench: Unveiling the True Potential of Protein Foundation Models
A notable progress in protein prediction and generative tasks, such as 3D structure prediction, protein design, and conformational dynamics, has been made in recent...
How Are Transformer Models Bridging the Gap Between Data and Drug...
A recently published work by researchers from the Wuhan Textile University, China, and Michigan State University, USA, has addressed the use of transformer models...
Unlocking Molecular Dynamics: Dynaformer, a Graph-Based Deep Learning Model for Binding...
One major obstacle in structure-based drug design is accurately predicting the affinities of protein-ligand interaction. The accuracy of data-driven affinity prediction methods has improved...
Can We Measure Protein Interactions at Unprecedented Scale? MP3-seq Says Yes!
Numerous biological processes are regulated by protein-protein interactions (PPIs), and modified PPIs have uses in gene and cell therapy. Here, researchers from the University...
ChatMol: Pioneering Conversational Molecular Design with AI
ChatMol, an innovative AI model designed by Tsinghua University, PingAn Technology, and Beijing University of Posts and Telecommunications researchers, shapes the contours of the...
AlphaProteo: Google DeepMind’s AI Revolution in Protein Design
Protein-binding protein computational design is a key skill with many applications in biotechnology and biological research. While some target proteins have been successfully targeted...
Breakthrough in Virtual Screening: OpenVS a Game-Changer for AI-Powered Drug Discovery
In a recent study published in Nature Communications, researchers at the University of Washington, University of California, San Francisco, and University of Michigan, along...
Shaping the Future of Enzyme Catalysis: Advances in the Computational Design...
Enzymes can mediate discrete chemical reactions with sub-angstrom precision by employing complex, polar active sites to ensure a precise and effective response. Using the...
How Scripps Research Is Pioneering New Approaches to Slow Cancer Growth
To fight cancer, we must stop their metastasis or uncontrolled multiplication. Hence, it is important to understand what proteins these cancer cells need for...
Are We Closer to Mapping the Full Conformational Landscape of Proteins?
Proteins perform enormous tasks in our cells as molecular machines. These functions rely on the structural plasticity or the ability to adopt multiple shapes...
Unlocking Protein Secrets: AlphaFold-SFA’s Breakthrough in Cryptic Pocket Discovery
Rare events in proteins, which are essential for comprehending intricate phenomena like transitory structural changes and protein-ligand interactions, are frequently missed by unbiased molecular...
Navigating the AlphaFold Universe with DPCstruct’s Domain-Level Classification
AlphaFold is a database of protein structures and predictions. It contains predictions for ~214 million proteins. AlphaFold2, developed by DeepMind, has dramatically scaled our...
Revolutionary One-Step Approach: Predicting and Screening Protein-Ligand Complexes with Geometric Deep...
Deep learning is being utilized in the course of drug development to understand the structure of the protein-ligand complex, utilizing the technique of virtual...
ProteinGPT: Streamlining Complex Protein Analysis Through Conversational AI
ProteinGPT was developed jointly by specialists from the University of California in Los Angeles and the Georgia Institute of Technology and Meta AI. The...
CellTracksColab: A Breakthrough Platform for Cell Tracking Data Analysis
Understanding complex cellular behaviors quantitatively is essential for gaining in-depth insights into cell biology. Tracking the movement and interactions (movies) of cells over time...
WebAtlas: A Powerful Tool for Integrated Single Cell and Spatial Transcriptomic...
A recent study by Tong Li and colleagues from the Wellcome Sanger Institute and other institutions introduces WebAtlas, an innovative pipeline aimed at addressing...
DeepEnzyme Improves Enzyme Turnover Prediction Accuracy Leveraging Deep Learning and Protein...
In synthetic biology, turnover numbers (kcat) — a critical measure of an enzyme's efficiency—have a variety of applications. On the other hand, kcat measurement...
Streamlining Gene Identification: UnigeneFinder’s Automated Approach to Reference-Free Transcriptome Analysis
The availability of genome data is of great importance in this day and age. But, transcriptome data (which is a subset of the entire...
Revolutionizing Molecular Representation: A Deep Dive into Fragment and Geometry-Aware Tokenization
Targeted and efficient treatments for identified protein targets necessitate the use of structure-based drug design (SBDD); this is still a challenge owing to the...
A DNA Damage Repair Superhero ‘DdrC’
A recent study published in Nucleic Acids Research has unveiled a critical role played by DdrC. The researchers found out that it can work...
Revolutionizing Drug Discovery: Predicting Pharmacokinetics from SMILES Using Diffusion Models and...
The use of artificial intelligence (AI) in all phases of medication development is growing rapidly. Drug pharmacokinetic (PK) datasets are frequently acquired independently of...
Breaking Down Cancer Genomes: The Innovative Visualization Toolkit GenomeSpy
Trying to visualize available genomic data is of great interest. Currently, there exists a lot of specialized visualization tools, but most need to be...
Oxford Researchers Breakthrough in Predicting Protein Function from Sequence Alone Using...
Understanding the complex mechanisms behind many essential biological activities is essential for developing new drugs and has broad ramifications in the disciplines of biotechnology,...
Must Read
Fast, Accurate, and Flexible: How FLOWR is Transforming Molecular Design
In a recent breakthrough in AI-driven drug discovery, researchers from Pfizer, AstraZeneca, and Chalmers University unveiled a new generative framework called FLOWR, designed to...
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...