Eva Maria Novoa

@OdedRechavi @grnfluoresceblg Its nice but if used for the purpose of increasing the odds of getting your grant funded, i disagree. if everyone would use it, it will still be the same problem no? Just even harder to decide which grants get funded, but the percentage of success will be the same: very low….

Important announcement!!!🫵💥💫 Would you have a tooth pulled if it helped your chances to get an important grant funded? Absurd question (obviously), but the situation right now is so bad funding-wise, that I bet some of you actually considered it for a second… Well, don’t get desperate - we created a new tool that might help! (keep your teeth!) I’m excited to announce that as of today we are officially releasing “QED for Grants” for everyone. What started off as an extension of our existing paper review platform, grew in the last few months to an entirely new design. We’ve been working like crazy on this, and although we have more things we want to add in the (very near) future, we decided to release our AI for grants NOW, earlier than planned. It’s not perfect, no AI is, but for the first time, when I run my own grants through @qedscience, I feel it gets the research, finds real problems, and gives me very useful feedback that I can implement before submission. It’s like sending it to 20 scientists from my domain, knowing they’ll agree to dedicate their entire week to carefully read and comment on every line. It’s very important to write your own grants yourself, it makes you think hard and you learn a lot from doing it, and q.e.d’s system is designed to preserve these positive aspects and augment them - you get feedback on your own writing, we don’t write for you!! But at the same time, a typical PI spends many months every year writing proposals and sadly only a tiny fraction gets funded, even if the ideas are good. When you are forced to submit an unreasonable amount of grants the quality of the writing drops, and rejection rates increase. Not because the essence is bad. It’s simply too competitive right now (the cuts made it so much worse) and if your proposal is not super clear and tight, and if it’s not a perfect fit for the grant you’re submitting, you’re doomed. Our grant solution is not an authoring, text-generating tool. It gives you constructive feedback on your writing (it comments on the deep things, not grammar and typos). It’s meant to help you with the questions that torment you late at night (“is this a good fit?”, “Is this novel enough?”, “Did I miss something?”). Tens of thousands of you already use q.e.d to improve your manuscripts and critically read papers, we built the grant tool by the same principles (you’ll identify many of the features that you told us you like). We’ve processed thousands of proposals, learned where things fail, where reviewers get stuck, why good ideas come out weak. We interviewed hundreds of scientists, and also experts who work in funding agencies and university research authorities, and implemented their feedback (we’re constantly looking for more feedback). Our AI is always happy to give you constructive (and polite!) critique, and it will go through your grant line-by-line, forcing you to improve clarity, flag weak points, and push the whole thing to a higher standard. We study, in scale, what gets funded and what doesn’t, and what is the perfect fit for each type of grant. So please, use it, pressure-test it, tell us where it fails, and together we’ll improve it every day to put you in the best position for actually testing your ideas in the real world. As always with q.e.d, the system is completely secured and private, and we are NOT training on your data (see the FAQ on our website). Please like, retweet, and share with your favorite colleagues! (link to the platform below in the thread👇)

@LabBoke I’ve also requested in some occasions for a postdoc to go on my behalf. A couple of times was not accepted but recently they agreed to this in one conference. So things are also changing a bit :-) And it can be a great opportunity for visibility for the early career researchers!

I’ve been wondering about conference norms. When I can’t attend an invited talk, I offer to send my postdoc who led the relevant work; but this is basically never accepted by organisers. When I organize meetings, I’m more than happy for postdocs to step in.

Academic publishing is a racket on impressive scale Open Access involves inflated costs to authors to protect the revenue of publishers In an already underfunded system, academia can’t afford to keep paying tithes to Elsevier, Wiley and the rest news.cancerresearchuk.org/2026/04/01/why…

@rodalies Podeu si us plau incrementar la frequencia de la R2 nord mes enlla de granollers? Es baixa mes gent a cardedeu i llinars que a granollers. S’hauria de incrementar la frequencia en les seguents parades, aixo no seria una gran inversio i milloraria molt les condicions de molta gent

🚊R4: ✅ Recuperació del servei ferroviari entre Sant Sadurní i Martorell Central · Servei ferroviari entre Sant Vicenç de Calders – Terrassa Estació del Nord · Servei ferroviari i servei complementari per carretera entre Terrassa Estació del Nord – Manresa

📢 ATENCIÓ! ℹ️ Millora del servei de Rodalies de Catalunya a les línies R1, R2 i R4 🗓️ A partir d’avui, dimarts 7 d’abril nous horaris 🔗: gen.cat/41Qe2JM 🧵Obrim fil amb més informació:

New #preprint from our @NovoaLab! We develop tRIBO-seq, a nanopore method to sequence ribosome-associated #tRNAs and track how the active tRNA pool changes across #stress conditions. Wonderful collaborative effort with #immaginaBiotech and #SoaresLab! biorxiv.org/content/10.648…

Lifespan is 50% heritable, twice previous estimates! In our new paper out today in @ScienceMagazine , we used mathematical modeling to remove extrinsic mortality, and validated with new twin data.

The importance of stupidity in scientific research

Today in @Nature we report a new prime editing strategy that can rescue a common cause of many genetic diseases in a disease-agnostic manner. This approach converts a redundant endogenous tRNA into an optimized suppressor tRNA, enabling a single prime edit to rescue premature stop codons across different diseases. (1/15) drive.google.com/file/d/1bSvkJW…

Ribosomal RNA (rRNA) genes are found in hundreds of copies in the human genome. Do sequence variations in these paralogs change the ribosome function? Yes! I am excited to share our new preprint @mbarnalab @jkpritch in collaboration with Calico: medrxiv.org/content/10.110… 1/8

🗨️ Just published in @NatureBiotech: Our CellWhisperer AI enables chat-based analysis of single-cell sequencing data. You can talk to your cells & figure out the biology without writing any computer code. Paper link and annotated walkthrough in the thread below (1/11)

Fresh preprint from the @NovoaLab!😀📌 Do you want to barcode up to 96 #RNA samples in your #nanopore flowcells? How well do RNA #modification-aware models perform? What if there is #noBasecallingModel for your modification-of-interest? Find it out here!😊biorxiv.org/content/10.110…

I am so incredibly excited to share our latest work, on the exploration of #RNA secondary structure ensembles and discovery of RNA regulatory structural switches in bacteria and human cells, out today in @NatureBiotech: nature.com/articles/s4158…. A short tread! (1/n)

A list of 17 total universities around the USA announcing layoffs or cuts from this week alone…

New postdoc opening @UNSW in RNA biology and T cell immunity 🥼🧬🧫. Use molecular biology, nanopore sequencing, and in vivo models to uncover the regulatory drivers of adaptive immunity. Apply 👉 tinyurl.com/422n7hr6

As a co-founder of 23andMe, with all the recent news I felt it was time to express my views on the company, after witnessing the downfall of an idea and brand that could have become the world’s leading digital health platform. The idea for 23andMe came to me after years working in life science research across the US (San Francisco, Boston, San Diego, and DC), at companies like Applied Biosystems, Molecular Dynamics, Perlegen, and Affymetrix. In traditional research studies, it’s a very familiar pattern: data are collected toward a specific goal, analyses are performed, and papers may get published. But there was almost no way to re-engage the people who provided their samples and no provision for them to access their data. One story stuck in my mind. Augie Nieto was diagnosed with ALS or Lou Gehrig’s disease. He had the personal resources to fund a genetic study of ALS, but when he asked the researchers for his data (that he’d funded), he was informed that the research protocol didn’t permit them to share any data back with him. I had also attended the Personalized Medicine conference at Harvard for several years in the early 2000s. Everyone waxed on about this rosy future where people would only be prescribed medications that worked for them. It sounded great, but when you do a back-of-the-envelope calculation of the data required to implement that scenario, and consider how ploddingly research progress is made, it was a pipe dream. How would the data even be collected? 23andMe represented a new model: maintaining an online connection with the users and providing them with a direct view into their DNA. Having a communication link to the people who funded their own data access, we had a unique opportunity to continue the dialog, which could help parse the connection between our DNA and health outcomes in ways no government-funded effort was doing. This concept came out of work I did at Perlegen Sciences (2003-2005), a company with a mission to find variants in the human genome and determine their role in disease. We created gene ‘chips’ that enabled the analysis of variants in DNA across the whole genome. With these newly designed chips, the strategy was to take samples from patient cohorts, isolate and analyze the DNA, and correlate markers in patients compared to healthy controls. My job was to track down samples from patients who’d been diagnosed with various diseases and find funding to pay for the research. I met with countless disease foundations and patient advocacy groups. This is when I came across the Michael J. Fox foundation, which funded Perlegen’s first-of-its-kind study of Parkinson’s disease (and was how I met Sergey Brin, the co-founder of Google, who was a major donor to the organization). I was already feeling the inadequacy of these studies. So many diseases we were targeting were highly complex and needed more than just a simple diagnosis. The more I dug into ‘autism’, ‘bipolar disorder’, and ‘chronic fatigue syndrome’, to name a few, it was clear we needed more insights into what drove these patient diagnoses. The bible of medical diagnosis, the Diagnostic and Statistical Manual of Mental Disorders, or DSM-4 as it was called at that time, defined the conditions according to symptoms, but many likely have subtypes with differing causal routes. It was a ‘garbage in, garbage out’ problem. If you’re not starting with a succinct patient diagnosis, the genetic signature will be garbled. And it wasn’t easy collecting DNA from patients. In traditional research protocols, it meant getting blood samples, or worse, skin punches. Part of the answer to this problem came from attending a trade show where I came across the booth of a startup, DNA Genotek, claiming that they could get high-quality DNA from a spit sample. Out of curiosity I grabbed a kit and took it back to Perlegen. The scientists were a bit dubious, but were willing to do a test run. And I was recruited to be the ‘spitter’. Soon after, I found out it had worked beautifully. I was even more intrigued when they said they’d run my DNA across one of our GWAS chips. My data were sitting on a server in the company, and I was immediately hooked. Could I get a copy? This question raised far more concerns than I would have anticipated. Our HR department made me sign a release that I wouldn’t hold the company responsible for what I might learn. A lightbulb went on–if I was interested in accessing my own data, wouldn’t others feel the same way? Getting deeply personalized information about what makes us ‘us’ seemed undeniable. It didn’t take long for the concept to unfold. I’d then moved to Affymetrix where I floated the idea of a consumer-focused genetics startup to the management. To this day, I’m grateful to Steve Fodor, Sue Siegel, Gregg Fergus, Thane Krieiner, and others who supported my mission to run with it. Building a website for consumers to learn about their DNA was no small challenge. It took us over a year to build a secure database, research the scientific implications behind the genetic markers, design the user interface, and create understandable explanations for the general public. We asked for feedback from a wide range of scientists–including a day of grilling at the Broad Institute–and we informed the head of the FDA of our plans. Our scientific advisory board was made up of experts from across the US. Soon after launch, we branched into ‘23andWe’ (our research mission), with the goal of collecting additional data through surveys. I didn’t want to stop there. I knew we needed to keep engaging with our customers. What if we added in symptom tracking, blood test results, drug response, environmental exposure, etc? There was a wealth of information our customers could share. When we launched our initial surveys, we were pleased and surprised at the high response rate. But surveys can only collect limited data. There were so many other ways to dig deeper. And from a business model perspective, the one-and-done DNA collection step wouldn’t cut it. On another note, I was also very vocal about the opposition to gene patents, well before the Supreme Court ruled against them in 2013. Finding genetic correlations to any human traits very clearly isn’t an invention deserving of patent protection, nor did it seem ethical. (I later found out 23andMe discoveries were being filed for patents without my knowledge.) My time at the company was cut short in 2009, when my co-founder Anne convinced the board that she should run the company. And I must be honest, I was frustrated with the direction the company took after that point. After my departure, she architected a majority vote for herself that eliminated board governance, even as it expanded over the following funding rounds. For better or worse, the buck stopped with her. It came as no surprise when the board resigned last year. 23andMe was in a unique position when it started, well before the digital health revolution got underway. It is painful to think what could have been - the category-defining Google of digital health. The company has amassed one of the largest genetic data collections in the world, and to Anne’s credit, created a terrific consumer brand. We can only imagine the importance of the dataset that could have been built, combining blood work, deeper gene sequencing, wearable data, and providing actionable insights. Now, the market is fragmented with data siloed in many different companies. Without continued consumer-focused product development, and without governance, 23andMe lost its way, and society missed a key opportunity in furthering the idea of personalized health. The 14+ million people who bought into the concept deserve to see their data moved to a secure platform with new leadership and vision. Consumers, however, should be careful sharing their data if they don’t trust its secure and ethical use. There are many cautionary tales buried in the 23andMe story. Striking a balance between the desire for founder control and board oversight is essential; otherwise, why have a board at all? It’s a familiar trope in Silicon Valley that wealth translates into unquestionable business savvy. But no matter how great an idea, the importance of the dynamics of the founding team and their ability to listen to feedback is key. As a venture investor, I take these learnings into the tech bio space with a realistic view of the possibilities we’re seeing. The AI-guided future of health is here, and while there will never be a moment like the post-genome era with a blue ocean digital health market, it’s possible that new companies will rise and build the dream dataset of human health. I think there are great innovations that can make this happen, and I’m excited to be a part of that future.

Truly honored to receive this prize. This would have not been possible without the support from my wonderful family, all past and present @NovoaLab members, and our larger @CRGenomica family. Thanks for your continuous support! ❤️

I’m excited to share my work over the last few years with @JD_Buenrostro! Chronic inflammation creates an epigenetic memory in colonic stem cells, priming them for tumor growth: tinyurl.com/ColitisNagaraj…. Here’s a walkthrough of what we found (🧵)

How has native RNA sequencing contributed to epitranscriptomic research? This is one of the main questions we addressed in our recent review by @EvaMariaNovoa and I now live in @MolecularCell authors.elsevier.com/a/1kS2f3vVUPRn…

@ArcadiNavarro @IRBBarcelona @recercauniscat @ANavarroFPM @fpmaragall Bell missatge que celebra el passat i mira cap al futur, tot dient el que s’ha de dir, tot seguint els esforços de molta gent com el Joan Guinovart. Gracies Arcadi

Per si de cas:

La millor manera de celebrar la vida del gran Joan Guinovart: insistir en la seva lluita. Per part meva, "confirmo i confesso". ara.cat/129_500a9e Joan Guinovart, a la seva memòria: universitats i recerca: renovar el compromís

Where RNA Science Meets AI, May 4–8, 2025, Ascona. Invited speakers: @OliverStegle @fabian_theis @fiddle @EvaMariaNovoa @BTreutlein @satijalab @RivasElenaRivas @RouskinLab @YosephBarash @gagneurlab, Rhiju Das, Karla Neugebauer, Jernej Ule Registration open, rna-ai.org @quaidmorris @hagentilgner