All Bioinformatics articles – Page 2
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NewsCloneSeq-SV: new blood test tracks ovarian cancer recurrence
Researchers have developed a new blood test method, CloneSeq-SV, that tracks treatment-resistant ovarian cancer cells over time. The approach could help predict recurrence and guide targeted therapies.
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ArticleBeyond templates: advancing protein–protein interaction structure prediction with AI
Dr Alan Nafiiev evaluates template-based, docking and template-free approaches to PPI prediction, highlighting how AI can enhance structural accuracy.
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ArticleMaking sense of AI: bias, trust and transparency in pharma R&D
AI is increasingly used in drug discovery, but hidden bias and ‘black box’ models threaten trust and transparency. This article explores how explainable AI can turn opaque predictions into clear, accountable insights.
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ArticleBeyond the hype: a veteran’s honest assessment of AI in drug discovery – Part 3
AI is starting to transform drug discovery, but progress is still slow and big challenges remain. Thibault Géoui explores the gaps, hurdles and breakthroughs needed before it can truly change pharma R&D.
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ArticleWhat if drug discovery took months, not decades?
Drug discovery is slow, costly and often unsuccessful. DTR hears how GATC Health is applying AI and multiomics to make the process faster, more precise and less reliant on trial and error.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 3
What role could large language models and AI agents play in drug safety? In Part 3, Layla Hosseini-Gerami of Ignota Labs discusses how emerging technologies might make toxicity analysis faster, more accessible and part of the drug discovery workflow from day one.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 2
Why do so many drug candidates fail before reaching patients – and can AI help stop the losses? In Part 2, Layla Hosseini-Gerami of Ignota Labs outlines the scope of the toxicity problem and explains why failures often come too late to fix.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 1
Why do so many drug candidates fail before reaching patients – and can AI help stop the losses? In Part 1, Layla Hosseini-Gerami of Ignota Labs outlines the scope of the toxicity problem and explains why failures often come too late to fix.
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ArticleWhat single cells are revealing about brain disorders
Single-cell and spatial technologies are giving researchers an unprecedented view of how brain diseases like Alzheimer’s really work. The result? Faster discovery, clearer targets and a new path towards more effective treatments.
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ArticleMachine Learning and AI in Enhancing Image Analysis of 3D Samples
Want to understand the real impact of AI in 3D sample analysis? This episode cuts straight to how machine learning is accelerating research and overcoming current limitations.
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NewsTurning AI into a biological design engine
DenovAI has unveiled a powerful AI-driven protein design platform capable of creating new, functional synthetic proteins from scratch - marking a big step forward for drug discovery.
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NewsAI just made protein design smarter and faster
Meet the AI tool that creates proteins that fold better, bind tighter and perform more reliably. Find out why it matters for next-generation medicines.
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NewsK Navigator: an AI co-pilot transforming biomedical research
K Navigator, a new AI-powered research co-pilot, is set to transform biomedical science by helping researchers explore complex data and accelerate discoveries.
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News
Enedra secures funding to advance AI-driven cancer platform
Enedra Therapeutics has secured new funding to advance its AI-driven CASPAROV platform, aimed at developing therapies for difficult-to-treat cancers
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NewsOutsmarting cancer by exploiting DNA repair flaws
Researchers at ETH Zurich in Switzerland have mapped the complex network cells use to repair their genetic material, revealing previously hidden vulnerabilities in cancer cells.
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ArticleNavigating the AI revolution: a roadmap for pharma's future
AI-driven drug development, powered by advanced models and expanding data access, is becoming a reality. Learn why navigating regulatory hurdles and mastering biology’s inherent complexities are crucial to fully unlocking its potential.
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ArticleScientific workflow for hypothesis testing in drug discovery: part 3 of 3
Drug discovery scientists develop and test complex hypotheses using data and expertise, and build workflows to support this. In this third and final article, Dr Raminderpal Singh and Nina Truter summarise the tools used in the scientific workflow – and include key considerations.
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NewsUVA’s computer models target antibiotics to combat resistance
Researchers at the University of Virginia School of Medicine have developed computer models to create more targeted antibiotics. This approach aims to fight antibiotic resistance by focusing on specific bacteria in different parts of the body, reducing the reliance on broad-spectrum antibiotics.
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NewsBoltz-1: A new open-source AI tool for drug discovery
MIT's new open-source AI model, Boltz-1, could transform drug discovery by accurately predicting protein structures, offering global access to researchers.
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ArticleScientific workflow for hypothesis testing in drug discovery: Part 1 of 3
Explore the step-by-step scientific workflow behind drug discovery, from formulating hypotheses to analysing data, ensuring accurate and reliable results.
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