computational biology
30 articles about computational biology in AI news
OpenAI's 'Autonomous AI Researchers' Vision Sparks Debate on Biology's 'ChatGPT Moment'
A tweet highlights OpenAI's repeated references to 'autonomous AI researchers' as signaling a 'ChatGPT moment for biology,' suggesting AI could accelerate drug discovery by orders of magnitude. The claim draws a direct analogy to AlphaFold's impact on structural biology.
AI Agents Map Resonators Across Domains, Design Bio-Inspired Structure
AI agents have mapped resonators from biology, engineering, and music into a shared latent space, discovered an unexplored design region, and autonomously generated and validated a novel bio-inspired resonator structure.
AI Firms Target Biotech for High-Impact, High-Margin Applications
A trend analysis notes AI companies are shifting focus to biotech, where accurate prediction models can be monetized through drug discovery and synthetic biology, creating a new competitive frontier.
ML Researcher Uses AlphaFold to Design Treatment for Dog's Cancer in Viral Story
A machine learning researcher reportedly used AlphaFold, DeepMind's protein structure prediction AI, to design a potential treatment for his dog's cancer. The story has gained widespread attention online, highlighting real-world applications of AI in biology.
Mirendil: Ex-Anthropic Scientists Launch $1B Venture to Build AI That Thinks Like a Scientist
Former Anthropic researchers are raising $175M at a $1B valuation for Mirendil, a startup aiming to build AI systems for long-term scientific reasoning. The goal is to accelerate breakthroughs in biology and materials science, aligning with a broader industry push toward autonomous AI researchers.
Neurons Playing Doom: How Living Brain Cells Could Revolutionize Computing
Australian startup Cortical Labs is pioneering biological computing with a system that uses living human brain cells to perform computational tasks. Their CL1 computer consumes just 30 watts while learning to play Doom, potentially offering massive energy savings over traditional AI hardware.
Annealed Co-Generation: A New AI Framework Tackles Scientific Complexity Through Pairwise Modeling
Researchers propose Annealed Co-Generation, a novel AI framework that simplifies multivariate generation in scientific applications by modeling variables in pairs rather than jointly. The approach reduces computational burden and data imbalance while maintaining coherence across complex systems.
Beyond General AI: How Liquid Foundation Models Are Revolutionizing Drug Discovery
Researchers have developed MMAI Gym, a specialized training platform that teaches AI the 'language of molecules' to create more efficient drug discovery models. The resulting Liquid Foundation Models outperform larger general-purpose AI while requiring fewer computational resources.
LLM Agents Take the Wheel: How Rudder Revolutionizes Distributed GNN Training
Researchers have developed Rudder, a novel system that uses Large Language Model agents to dynamically prefetch data in distributed Graph Neural Network training, achieving up to 91% performance improvement over traditional methods by adapting to changing computational conditions in real-time.
DARPA Leases 50 Nvidia H100 GPUs for Biological AI Program
DARPA's Biological Technologies Office is procuring 50 Nvidia HGX H100 GPU systems for its NODES program, with hardware delivery required within one month. This represents a significant government investment in AI infrastructure for biological research applications.
Altman: Next-Gen AI Models to Aid 'Career-Defining' Scientific Discovery
OpenAI CEO Sam Altman stated that upcoming AI models will assist researchers in making 'career-defining' discoveries, though he tempered expectations of immediate Nobel-level breakthroughs.
Embedding Matching Distills Genomic Models 200x, Matches mRNA-Bench Performance
A new distillation framework transfers mRNA representations from a large genomic foundation model to a specialized model 200x smaller. It uses embedding-level distillation, outperforming logit-based methods and competing with larger models on mRNA-bench.
Kronos AI Outperforms Leading Time Series Models by 93% on Candlestick Data
Researchers from Tsinghua University released Kronos, an open-source foundation model trained on 12 billion candlestick records from 45 exchanges. It reportedly achieves 93% higher accuracy than leading time series models for price and volatility forecasting, requiring no fine-tuning.
Add 197 Bioinformatics Skills to Claude Code with SciAgent-Skills
A ready-to-use plugin that transforms Claude Code into a bioinformatics expert without fine-tuning or RAG setup.
DeepMind's AlphaGenome AI Decodes Non-Coding DNA for CRISPR Targeting
Demis Hassabis states that while CRISPR can edit DNA, finding the right target is hard. DeepMind's AlphaGenome AI is analyzing the non-coding genome to predict mutation effects and guide precise CRISPR interventions.
Inner Ear Gene Therapy Injection Reverses Deafness in All 10 Patients in Clinical Trial
A clinical trial has reported that a single injection of gene therapy into the inner ear successfully reversed deafness in all ten participating patients. This marks a significant threshold in treating genetic hearing loss, with some patients regaining hearing within weeks.
ASI-Evolve Automates AI Research Loop, Discovers 105 Better Linear Attention Designs and Boosts AMC32 Scores by 12.5 Points
Researchers developed ASI-Evolve, an AI system that automates experimental loops in AI research. It discovered 105 improved linear attention variants and boosted AMC32 scores by 12.5 points, demonstrating automated research acceleration.
BloClaw: New AI4S 'Operating System' Cuts Agent Tool-Calling Errors to 0.2% with XML-Regex Protocol
Researchers introduced BloClaw, a unified operating system for AI-driven scientific discovery that replaces fragile JSON tool-calling with a dual-track XML-Regex protocol, cutting error rates from 17.6% to 0.2%. The system autonomously captures dynamic visualizations and provides a morphing UI, benchmarked across cheminformatics, protein folding, and molecular docking.
Microsoft & CUHK Debut 'Medical AI Scientist' Agent That Generates Ideas, Runs Experiments, and Writes Papers
Microsoft Research and CUHK have developed an autonomous AI agent that can formulate research ideas, execute experiments, and author papers, achieving near-MICCAI quality on 171 clinical cases across 19 tasks.
Ethan Mollick Critiques Scientific Publishing's AI Inertia: PDFs Still Dominate in 2026
Wharton professor Ethan Mollick highlights that scientific papers in 2026 are still primarily uploaded as formatted PDFs to restrictive academic archives, signaling slow adaptation to AI's potential for accelerating research.
OpenAI Targets Autonomous AI Researcher System for Parallel Problem-Solving
OpenAI is reportedly developing an autonomous AI researcher system designed to decompose complex problems, run parallel agents, and synthesize results. This represents a strategic shift toward multi-agent, reasoning-focused architectures.
Microsoft Releases GigaTIME: AI Model Generates Protein Maps from Standard Medical Images
Microsoft has released GigaTIME, an AI model that generates detailed spatial protein maps from standard, low-cost medical images like H&E stains. This could significantly reduce the cost and time of cancer tissue analysis.
The Coming Revolution in AI Training: How Distributed Bounty Systems Will Unlock Next-Generation Models
AI development faces a bottleneck: specialized training environments built by small teams can't scale. A shift to distributed bounty systems, crowdsourcing expertise globally, promises to slash costs and accelerate progress across all advanced fields.
Sam Altman Envisions AI That Thinks for Days: The Dawn of Super-Long-Term Reasoning
OpenAI CEO Sam Altman predicts future AI models will perform "super long-term reasoning," spending days or weeks analyzing complex, high-stakes problems. This represents a fundamental shift from today's rapid-response systems toward deliberate, extended cognitive processes.
Jensen Huang's '5-Layer Cake': Nvidia CEO Redefines AI as Industrial Infrastructure
Nvidia CEO Jensen Huang introduces a revolutionary framework positioning AI as essential infrastructure spanning energy, chips, infrastructure, models, and applications. This industrial perspective reshapes how we understand AI's technological and economic foundations.
AI Teaches Itself to See: Adversarial Self-Play Forges Unbreakable Vision Models
Researchers propose AOT, a revolutionary self-play framework where AI models generate their own adversarial training data through competitive image manipulation. This approach overcomes the limitations of finite datasets to create multimodal models with unprecedented perceptual robustness.
AI's 'Cheap Wins' in Mathematics Signal a New Era of Human-Machine Collaboration
Fields Medalist Terence Tao reveals AI is solving easier Erdős problems, but the real breakthrough is AI as a tireless junior co-author accelerating mathematical discovery through tedious work automation.
BioBridge AI Merges Protein Science with Language Models for Breakthrough Biological Reasoning
Researchers introduce BioBridge, a novel AI framework that combines protein language models with general-purpose LLMs to enable enhanced biological reasoning. The system achieves state-of-the-art performance on protein benchmarks while maintaining general language understanding capabilities.
From $100M to $100: How AI is Driving the Next Diagnostic Revolution
The cost of sequencing a human genome has plummeted from $100 million to under $100 in just 25 years, a milestone powered by AI and automation. This unprecedented price drop signals a coming wave of affordable diagnostic tests that could transform personalized medicine.
Living Architecture: AI-Designed Cyanobacteria Concrete That Repairs Itself and Captures Carbon
Researchers have developed a revolutionary living building material using cyanobacteria that captures atmospheric CO₂ and self-reinforces over time. This bio-concrete, validated by 400+ days of laboratory data, represents a paradigm shift toward regenerative construction.