David vilanova (@david_vilanova) header
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« From data to knowledge « Biologist - Bioinformatics , Genomics 🧬 🇦🇩Andorra

Andorra
Joined June 2008
Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)Photo by David vilanova (@david_vilanova)
David vilanova retweeted
How much do PhD students earn? The first comprehensive overview of PhD income shows vast imbalances across much of Europe Read the full story: nature.com/articles/d41586-0…
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David vilanova retweeted
In our new npj Aging paper, we show that a 30-second voice recording captures a signature of biological aging Using 7,000 participants from the Human Phenotype Project (humanphenotypeproject.org) we trained voice-based age models to predict chronological age. The resulting Voice Age was among the strongest single-modality aging clocks and added information beyond metabolomics, imaging, physiology and lifestyle A higher Voice Age gap was associated with adiposity, sleep-disordered breathing, poorer nocturnal oxygenation and liver-related traits, suggesting that voice may provide a simple, scalable biomarker of accelerated biological aging nature.com/articles/s41514-0…
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David vilanova retweeted
We are proud to release the world's first virtual cell -- a multi-modal, multi-scale, dynamic, and stateful world model of the cell, the first step toward an AI-driven Digital Organism (AIDO).
Today we're releasing a preview of AIDO Cell, a world model of the human cell. It simulates one cell across DNA, RNA, protein, through regulatory networks and whole-cell behavior. Not four models handing results to each other. One system.
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David vilanova retweeted
Predicting a person's health and disease arc many years in advance from their electronic health records and polygenic risk scores, along with the biological mechanism for the diseases just published @Nature Will be discussing the paper with the brilliant lead author @tigerstatdoc this Friday in Ground Truths 10:30 AM PST nature.com/articles/s41586-0…
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David vilanova retweeted
🧬 El fin de la ciencia inventada? Cero alucinaciones en PubMed con Claude Usa el nuevo protocolo MCP para conectar Claude directamente a la base de datos de PubMed. ¿El resultado? Analiza más de 50 papers médicos en segundos con 0% de alucinaciones. Lo que soluciona: Conexión Real: Consulta la API oficial de PubMed en tiempo real (mira las tablas y gráficos adjuntos). Cero Datos Falsos: Valida identificadores (PMID) y resultados clínicos reales de forma exacta. Metanálisis Express: Convierte horas de lectura médica en resúmenes estructurados al instante. El Siguiente Nivel (Idea de Producto): Review Pipelines: Agentes que redacten revisiones sistemáticas automáticas basadas en este protocolo. Clinical Alert Bot: Un bot que monitoree PubMed y publique hallazgos críticos en X o Discord de forma autónoma. Se acabaron las citas bibliográficas falsas. Repooooo 👇👇
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David vilanova retweeted
Genomics just hit its “foundation model” moment. AlphaGenome now predicts thousands of molecular effects from 1Mb DNA sequences at single-base resolution [1]. Pair that with UK Biobank’s 490,640 whole genomes and AI is no longer just speeding analysis it’s changing what questions researchers can ask 🧬 Industry noticed. Illumina and NVIDIA are combining sequencing, multiomics and accelerated AI to push drug discovery and clinical research forward [2]. The edge will go to teams that can connect wet labs, compute and interpretable models ⚙️ The challenge: don’t treat ML as magic. Treat genomic data quality, diversity and governance as core infrastructure or the benefits will concentrate in a few regions and companies. 🤔 Where do you think the real bottleneck is now: better models, better data, or better trust? [1] [nature.com/articles/s41586-0…](nature.com/articles/s41586-0…) [2] [illumina.com/company/news-ce…) [3] [genome.gov/about-genomics/fa…](genome.gov/about-genomics/fa…) #Genomics #MachineLearning #BioAI #PrecisionMedicine
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En 2021, les opposants à la vaccination craignaient "une hécatombe" dans les années à venir. Nous sommes 5 ans plus tard et une immense étude sur les données de 29 millions de Français (23 millions vaccinés, 6 millions non-vaccinés) prouve le contraire 👉 l.sciencesetavenir.fr/n43
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David vilanova retweeted
🚨 Over 1 billion rows of psychiatric genetics data. Now on Hugging Face. ADHD. Depression. Schizophrenia. Bipolar. PTSD. OCD. Autism. Anxiety. Tourette. Eating disorders. 12 disorder groups. 52 publications. Every GWAS summary statistic from the Psychiatric Genomics Consortium. Before: wget, gunzip, 20 minutes debugging separators, repeat 50 times. Now: one line of Python.
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David vilanova retweeted
🚨 The largest anxiety GWAS to date JUST dropped Over 850,000 genomes It found 58 risk loci and strongly points to GABAergic signaling as a core driver... ...the same neurons targeted by benzodiazepines. We finally have a robust genetic map for anxiety 🧵
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David vilanova retweeted
Accelerating minimap2 for whole-genome alignment academic.oup.com/bioinformat… 🧬💻🧪 github.com/at-cg/mm2-plus
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David vilanova retweeted
Resveratrol Quercetin ECGC Curcumin
Dietary polyphenols and sarcopenia: epigenetic mechanisms and geroscience perspectives for muscle health in aging frontiersin.org/journals/agi…
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David vilanova retweeted
Today in @NatureMedicine we report that AI can predict 130 diseases from 1 night of sleep🛌 We trained a foundation model (#SleepFM) on 585K hours of sleep recordings from 65K people—brain, heart, muscle & breathing signals combined. AI learns the language of sleep🧵
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Biobank Japan now offers GWAS data for NMR metabolomics (N=37,969), as well as a multi-ancestry meta-analysis with UK Biobank & Estonian Biobank (total N=657,341). The data cover 248 metabolites and expand our metabolomics resources for following-up GWAS signals.
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Genetic correlations of a proteomic aging clock with epigenetic aging clocks, cardiometabolic risk factors, telomere length, pubertal timing traits, and longevity.
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Epigenetic Reprogramming in humans is coming early next year (2026)... This is one of the first steps towards longevity escape velocity. We've known that you can reset the age of DNA taken from an "old cell" and putting it into a "young egg". Epigenetic reprogramming is real, and its coming. Get ready for a longer, healthier life... just in time to Surf the Singularity!
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David vilanova retweeted
PathogenSurveillance: an automated pipeline for population genomic analyses and pathogen identification biorxiv.org/content/10.1101/… Code: github.com/nf-core/pathogens… Nextflow nf-core pipeline: nf-co.re/pathogensurveillanc…
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🧬 In-Vivo CAR-T: Pharma’s New Holy Grail Ex-vivo cell therapy was biotech’s moonshot. But it’s running into gravity, manufacturing drag, cost friction, and clinical complexity. The next frontier is in-vivo CAR-T, programming immune cells directly inside the body. Pharma’s deal flow makes the shift obvious. > $ABBV bought Capstan for its targeted LNPs. > $GILD took Interius for integrating in-vivo delivery. >$AZN scooped EsoBiotec for immune-tropic vectors > $BMY grabbed Orbital for circular RNA payloads. These aren’t bets on “CAR-T 2.0.” They’re bets on skipping the cell therapy factory. ⚙️ What Pharma is Buying 1️⃣ Delivery that actually hits T cells. Platforms with immune-tropic vectors or LNPs that deliver RNA/DNA directly to lymphocytes are the crown jewels. The focus is on delivery/tropism and human data proving transduction at drug-like doses. 2️⃣ Autoimmune first, oncology second. Autoimmune diseases are the new on-ramp. Rebooting B-cells with in-vivo CD19 or CD20 CARs offers a faster regulatory path and cleaner biomarkers than solid tumors. 3️⃣ Control layers. Investors miss this: buyers aren’t paying for “permanent cures.” They’re paying for reversible control. RNA or epigenetic switches that let you turn therapy off, re-dose, and manage risk are where the value pools sit. 4️⃣ CMC scalability. If a CAR-T can be shipped like Humira, not manufactured like a transplant, it’s a platform. Simple fill-finish beats elegant biology every time. 💡 What Differentiation Looks Like >Immune reset, not immune destruction. Design for measurable immune recalibration (e.g., B-cell depletion, autoantibody drop, reconstitution window) with built-in rescue drugs. It’s a narrative payers understand. >Targeted LNP + circRNA stack. CircRNA extends expression without permanent edits, and LNP tropism turns dosing into a controllable dial. It’s the combination investors should hunt for. >Non-genotoxic engineering. Replace DNA cuts with transient RNA knockdowns (Cas13) or epigenetic silencing. Same function, lower risk, and better suited for systemic delivery. > Programmability over potency. Logic-gated CARs that activate only in certain cytokine or antigen contexts will dominate next-gen designs. Think conditional biology, not brute force. 🧭 What Comes Next >The endgame is obvious: off-the-shelf in-vivo immunomodulation that looks like a biologic and behaves like gene therapy. >First applications will be autoimmune reset, then solid tumor infiltration, then regenerative immune programming. >Pharma’s M&A tells you where translation is headed, away from autologous complexity and toward drug-like cell engineering. cell.com/trends/cancer/fullt…
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