Personal Genomics Zone

Dr Manuel Corpas presents the HEIM framework and Bias Amplification Cascade at the Molecular Science Research Hub seminar (12 March 2026). The talk covers three dimensions of compounding neglect in biomedical research: discovery (70 biobanks, 38,595 publications), translation (563,725 clinical trials), and knowledge (13.1M PubMed abstracts). Key findings: no neglected tropical disease has generated a single biobank publication; 93.5% of biobank research comes from high-income countries; and structural metrics predict 66.6% of LLM performance variance across 175 diseases. Six frontier LLMs benchmarked on 10,500 standardised queries show identical blind spots, proving the bias originates in shared training data, not model architecture. The talk concludes with the HIV/AIDS case as proof that sustained investment can reverse semantic isolation.

A deep dive into agentic AI for bioinformatics: what agents are, how they work, the state of the art in 2026, and why ClawBio's specification layer — SKILL.md — changes how we package and share computational biology methods. Covers the OpenClaw architecture, MCP protocol, Galaxy integration, 7 hard challenges, 6 opportunities, and ClawBio's roadmap from 25 skills to a full platform. Includes a call to action for the ClawBio Hackathon: Agentic Genomics at Imperial College on 19 March 2026.

Dr Manuel Corpas introduces Agentic Genomics — a framework for how AI agents are transforming bioinformatics. Covers the HEIM equity framework, bias amplification in genomic AI, ClawBio skill library, and why deep human intelligence remains the bottleneck. Recorded 9 March 2026.

Live demo of ClawBio, the first bioinformatics-native AI agent skill library, presented at DoraHacks Demo Day at Imperial College London on 7 March 2026. Covers pharmacogenomics, intelligent routing, multi-channel agents (Telegram and WhatsApp), and the Drug Photo feature. 21 skills, 14 production-ready, built on OpenClaw.

Peter Steinberger delivers the keynote at the UK AI Agent Hack at Imperial College London. He discusses building open-source AI agent tooling, setting up a foundation with David Morin to accept donations and hire full-time contributors, learning by building rather than reading, the exchange loop as the 'hello world' of AI agents, and why prompt injection remains an unsolved industry problem that should discourage one-click installations for non-technical users.

How I built a complete AI research infrastructure -- from personal knowledge base to automated pipelines -- without software engineering training. Practical lessons on vibe coding, the six-layer RAG architecture, and leveraging domain expertise to build tools that matter.

Seven actionable insights for researchers on using AI as a learning partner: pair-programming with LLMs, handoff documents, project organisation, autonomous agents, voice interfaces, AI-to-AI orchestration, and context-first prompting.

What separates casual AI users from the top 1%? Drawing on lessons from building a personal agentic AI system over six months and insights from Calvin French-Owen (co-founder of Segment, former OpenAI Codex team), this episode covers ten practical strategies: building persistent memory systems, mastering context management, test-driven AI workflows, moving from chatbots to agents, automating intelligence pipelines, clearing context aggressively, thinking like an engineering manager, keeping your workspace clean, shipping citable artifacts weekly, and building for sovereignty over your own AI.

A 71-minute lecture on how genomics is transforming medicine from trial-and-error to targeted, predictive care. Covers the paradigm shift from population averages to personalised treatment, variant interpretation using ACMG guidelines, the distinction between Mendelian and complex diseases, genome-wide association studies, and next-generation sequencing. Examines the critical equity gap: 86% of genomic research participants are of European ancestry yet Europeans represent only 16% of the global population. Introduces the HEIM framework for quantifying genomic data representativeness. Includes pharmacogenomics, liquid biopsy, direct-to-consumer testing, and ethics of genomic data. Delivered at the University of Westminster, 30 January 2026.

Architecture, a nine-tool Telegram agent, six automated daily jobs, cost engineering with three-tier model routing, and seven lessons from running a personal agentic AI system at production scale.

What I have learned from using LLMs to support academic writing. Observations that might save you from some painful mistakes.

A personal manifesto on harnessing artificial intelligence as an enabler for a new era of human wisdom and understanding, proposing principles for AI-augmented intellectual work grounded in equity, transparency, and scientific rigour.

A deep dive into quantitative confidence in genomics and precision medicine — exploring confidence intervals, p-values, Bayesian methods, calibration, and why honest uncertainty quantification is essential for good science and patient care.

Presented at the UK-Indonesia Health Genomics Forum, London. The real foundation of precision medicine is something much more fundamental than technology.

Precision medicine is built on a contradiction. The field promises individualised care yet its foundations rest on data representing a fraction of humanity.

A recap of my presentation to Britcham Brazil on health data equity in Latin America in the age of AI and genomics.

Lectures from Biobanking for Data Science at the University of Westminster. How large language models perform on biobank-related queries.

When I'm asked how I became a scientist, I usually smile, because the truth is, I've been aspiring to be one for over 30 years.

Despite breathtaking advances in genomics, we are failing to answer a fundamental question: who benefits from this progress?

Genomics holds the promise to revolutionize healthcare. But this vision remains dangerously incomplete without diversity.

A deep conversation with Professor Yves Moreau from KU Leuven on the intersections of artificial intelligence, genomics, and society.

Imagine two people walk into a hospital. Same symptoms. Same diagnosis. One receives a treatment that works. The other? Nothing.

A detailed practitioner's guide to building personal agentic AI systems. Covers the technical stack, embedding pipelines, agent architecture, memory systems, mistakes made, real costs, and why sovereignty over your own AI matters. Built by one academic with a Mac Studio and an unwillingness to wait.

A distillation of the key ideas from a nearly three-hour conversation between Elon Musk, Peter Diamandis, and Dave Blundin at Tesla's Giga Texas, covering AGI timelines, AI safety through truth, curiosity and beauty, the white-collar displacement thesis, Universal High Income, energy as civilisational currency, humanoid robots, and the Mars imperative.