"Quantum protein folding breakthrough in Ubiquitin C"

Quantum meets Genomics. The Sanger Institute has selected Quantinuum as a key partner in its bid for the Q4Bio challenge—an initiative led by the University of Oxford and backed by Wellcome Leap to push quantum computing into genomics. The goal? Process the full PhiX174 genome on a quantum computer—potentially a world-first in demonstrating quantum's practical value in biology. Backed by Quantinuum’s H2 system, the collaboration will explore how quantum algorithms can tackle genomic problems beyond the reach of classical machines. 🧬 This marks a critical step in quantum for biology—bringing together algorithmic innovation, next-gen hardware, and one of the most storied research institutions in genomics. Full article in comments. #QuantumComputing #Genomics #BioTech #Quantinuum #Q4Bio #SangerInstitute #ComputationalBiology #DeepTech

The ultimate playlist for AI in biology is here! 🎧🧪 Thrilled to see MIT's MLCB24 lecture series available online. Covering everything from protein language models and molecular generation to disease mechanisms and comparative genomics. A huge resource for learning how #MachineLearning is transforming life sciences. #ComputationalBiology #AI #GenAI #Bioinformatics #DrugDiscovery

Quantum computing may have just taken a leap into the living world. Researchers have shown that enhanced yellow fluorescent protein (EYFP), a staple in biological imaging, can act as a quantum bit, or qubit, not just in purified samples but inside mammalian and bacterial cells. That’s a staggering shift. It means quantum behavior isn’t confined to sterile labs or exotic materials anymore. It’s happening inside the messy, dynamic environment of biology, with implications for sensing, imaging, and computation at the molecular level. What makes EYFP truly remarkable isn’t just its quantum properties, it’s that it can be genetically encoded. Unlike superconducting circuits, EYFP qubits can be inserted into cells using standard genetic engineering techniques, allowing scientists to build quantum systems from the inside out. While these protein-based qubits aren’t ready to replace today’s quantum processors, they offer a radically different path forward. This could be the beginning of hybrid platforms where biology and quantum logic co-evolve. Worth keeping an eye on. #QuantumBiology #BiotechInnovation #QuantumComputing #SyntheticBiology #MolecularEngineering #FutureOfScience #GeneticEngineering

A new approach to computing genetic minimal cut sets replaces MILP with linear programming, significantly reducing runtime while maintaining accuracy. The method introduces k-representative subsets to streamline analysis of genome-scale metabolic models and has been benchmarked across E. coli and human GEMs.  Explore the full study in Bioinformatics Advances: https://lnkd.in/grdkhXBt

Quantum Computing Meets Biology: EYFP Proteins as Qubits Researchers at the University of Chicago have shown that enhanced yellow fluorescent protein (EYFP)—commonly used in molecular biology—can serve as an optically addressable spin qubit, even within living cells. By leveraging EYFP’s metastable triplet state, they achieved measurable spin coherence times, opening the door to biologically embedded quantum systems. This represents a potential shift in nanoscale sensing and quantum imaging—where life sciences and quantum information science intersect. This research hints at a future where quantum technologies can be encoded directly into biological systems, unlocking new possibilities in diagnostics, imaging, and fundamental understanding of life at the quantum level. 📎 Full article in comments. #QuantumBiology #QuantumComputing #MolecularBiology #QuantumImaging #UniversityofChicago

Researchers from Purdue and NC State introduce a multimodal quantum vision transformer that predicts enzyme function by integrating four distinct biochemical representations: protein sequences, quantum-derived electronic descriptors, molecular graphs, and 2D molecular images. This model may address a long-standing challenge in computational biology, which is how to predict enzyme function when structural data or homology is limited. https://lnkd.in/ecJNXbeG

🎓 International Course “Multiscale Integration in Biological Systems” 📍 Institut Curie, Paris 📅 November 12 – 18, 2025 One of the fundamental issues in biology is the understanding of the relationship between the multiple spatial and temporal scales observed in a biological system. From molecules to a cellular function, from a collection of cells to an organism, or from individuals to a population, the complex interactions between singular elements can give rise to “emergent” properties at the ensemble level. To what extent can the spatial and temporal order seen at the system level be explained by subscale properties? The course will give an overview of modern physical tools that have been developed to address the issue of scale integration (mornings) and will show how these tools can be applied to specific biological systems (afternoons). More specific topics will be tackled such as: ✔️ Physical concepts and modeling for biology, ✔️ Collective effects, self-organization and morphogenesis, ✔️ Cell and tissue mechanics, ✔️ Evolution in microbial communities, ✔️ Machine learning, information theory, image analysis 🔗 Register: https://urlr.me/RJEMa6 Selection criteria: Participants will be selected based on their research interest (CV). Each participant will give a 15-20 min oral presentation on his/her work or will have the opportunity to give a flash presentation and a poster.

In a first-of-its-kind breakthrough, researchers have turned a protein found in living cells into a functioning quantum bit, or qubit, the foundation of quantum technologies. The protein qubit can be used as a quantum sensor capable of detecting minute changes and ultimately offering unprecedented insight into biological processes. Beyond biology, protein qubits could also open new frontiers for advancing quantum technology itself. #scienceandtechnology #biology #quantum #quantumtechnology #qubits #scientificresearch #breakthrough #proteinqubit #bioqubits #quantumsensing #quantumfuture #futuretech #biotech #quantumphysics #biologicalqubit #UChicagoPME #worldfirst #spinqubit #quantummaterials #healthtech

Pick the wrong orbital, and your excited-state simulation can miss the physics entirely, meaning a cancer drug candidate that looks promising on paper could fail in practice. A new workflow, AEGISS, systematically identifies the right orbitals, keeping quantum models both accurate and reliable. Every week, I track the quantum research that’s intended for real-world performance, resilience, and utility. These are early steps, but they point toward where quantum may prove its worth. ⚇ AEGISS for quantum chemistry: Researchers from Algorithmiq, Cleveland Clinic, and other collaborators present AEGISS, a Python-based workflow for selecting active orbital spaces. By combining orbital entropy analysis with atomic orbital projections it helps map only the most chemically relevant orbitals onto qubits, making high-accuracy excited-state simulations more systematic and scalable. ⚇ QROCODILE hunts dark matter: The University of Zurich leads the first sub-MeV dark matter search using superconducting nanowire single-photon detectors. With thresholds down to 0.11 eV, QROCODILE sets new global limits on light dark matter interactions, exploring regions of parameter space unreachable by prior experiments. ⚇ Quantum vision for enzymes: Purdue University and North Carolina State University researchers developed a multimodal quantum vision transformer that predicts enzyme function with 85.1% top-1 accuracy. By fusing quantum-derived electronic descriptors with sequence, graph, and image data, the model outperforms prior QML architectures in one of biology’s hardest classification problems. If you want these kinds of insights in your inbox every morning, subscribe to the Daily Qubit and never miss a qubit -- link in the comments. #quantumcomputing #quantumsensing #quantumchemistry

🚀 Big news! We are thrilled to announce that the first case study of the ChemBioML Platform has just been published in Nanoscale Horizons (Royal Society of Chemistry). 🎉 In this work, we: 🔹 Compressed >5000 genes into a single, interpretable and reversible Transcriptomic Response Index (TRI) — introducing a novel omics endpoint for nanotoxicology. 🔹 Leveraged ChemBioML Platform to train and validate a regulatory-acceptable nano-QSAR model. 🔹 Integrated Unreal Engine 5 to bridge academic science and the game industry, showcasing interactive science communication in a whole new way. 💡 Our study made modeling of complex transcriptomic space over 5000× faster, while validating the open-source ChemBioML Platform as a tool ready for researchers worldwide. 🔗 Read the accepted manuscript here: https://lnkd.in/dbuTuYEe