George Tulevski

🌟 BREAKTHROUGH DISCOVERY IN CANCER GENETICS 🌟 UCLA researchers have published a groundbreaking study in Nature Communications that revolutionizes our understanding of how noncoding DNA influences cancer progression. Their discovery of mutations in these "silent" regions significantly impacting mRNA levels, leading to abnormal protein production which can accelerate or hinder cell proliferation, challenges previous assumptions about noncoding DNA's role. The study also introduces a new prognostic tool, the untranslated tumor mutation burden (uTMB), which could predict patient survival in certain cancers. This pioneering research paves the way for developing targeted treatments and personalized medicine strategies, offering new hope in the fight against cancer. #CancerResearch #Genetics #InnovativeScience

16

🚀 Professor Hani Zaher (and Lab) have uncovered a groundbreaking mechanism in cellular stress response linked to ribosome speed! 🧬 Their recent paper reveals how cells activate stress responses by altering ribosome speed through the interplay of eIF4E and eIF4A factors. This discovery not only deepens our understanding of cellular biology but also opens new avenues for cancer research, potentially influencing therapeutic strategies. 🔬 #CellBiology #ResearchBreakthrough #CancerResearch #RibosomeSpeed #ScienceInnovation Read more: https://lnkd.in/e-KJnHYV

5

Prof. Vedika Khemani's research focuses on non-equilibrium many-body physics, a field born from advances in controlling quantum systems like atoms and superconducting qubits. Her work addresses foundational questions about the behavior of quantum systems outside equilibrium, including the emergence of novel phases, mechanisms of thermalization, and transitions between ergodic and localized behaviors. Notably, she introduced the concept of Hilbert Space Fragmentation, revealing new mechanisms for non-ergodicity beyond traditional conservation laws. A key achievement is her discovery and experimental realization of time crystals, non-equilibrium phases that break time-translation symmetry and oscillate indefinitely without heating. In collaboration with Google’s Quantum AI team, Prof. Khemani demonstrated this phenomenon in a system of spins flipping perpetually between two localized states. This work, published in PRL and Nature, highlights her role as a leading theorist in the study of quantum dynamics and non-equilibrium phases. Know all about the winner of the Infosys Prize 2024 in Physical Sciences from the scope and impact of her work to her career timeline! - https://lnkd.in/gvc-kTve  

20

🚨 Breakthrough in Cancer Treatment: Unveiling the Structure of LAG-3 🚨 Exciting news from Stanford and NYU researchers! They've unveiled a detailed structure of the LAG-3 protein, a key to understanding how some cancers evade the immune system. This discovery could revolutionize immunotherapy treatments by revealing new ways to deactivate the immune "brakes" that tumors use for protection. With one LAG-3 targeting therapy already FDA approved and more in development, this research is a game-changer in the fight against cancer. Dive into the groundbreaking study that's setting the stage for next-generation cancer therapies! #CancerResearch #Immunotherapy #MedicalInnovation

1

I School Ph.D. alums Nitin K. and Emily Aiken, as well as Prof. Joshua Blumenstock published their research in Nature Magazine Scientific Reports. In this paper, the team develops and tests an approach for releasing private mobility data and utilizes mobile data from Afghanistan and Rwanda to show how this algorithm can enable the use of private mobility data in two high-stakes policy decisions: pandemic response and the distribution of humanitarian aid. To read the paper: https://lnkd.in/gWkNrwFw

14

🔬 Breaking Ground in Genetic Disease Treatment at UChicago! 🧬Researchers at the University of Chicago are pioneering a novel treatment for genetic disorders using engineered transfer RNA (tRNA) to correct missense mutations. This cutting-edge approach leverages tRNA, a key molecule in translating genetic codes into proteins, to accurately target and fix the erroneous genetic "letters" responsible for producing defective proteins. Lead researcher Yichen Hou and the team have developed "missense-correcting tRNAs" (mc-tRNAs), which carry the correct protein building blocks despite the genetic miscode, offering a potential new platform for treating a broad spectrum of genetic diseases without the drawbacks associated with current gene editing technologies like CRISPR. This innovative strategy could dramatically change how we approach genetic therapy, providing a safer, more precise alternative. #GeneticTherapy #Innovation #UChicago #HealthcareTech

6

🔬✨ Assistant Professor Alberto Perez and his team have made a groundbreaking discovery in disease treatment! They have revolutionized our understanding of molecular interactions in disease development with their innovative AF-CBA Pipeline, an AI-driven tool that harnesses the power of computational biology. Their research, detailed in Angewandte Chemie, could lead to targeted therapies for conditions like cancer and immune dysregulation. 🧬🖥️ By leveraging AI, the AF-CBA Pipeline performs complex simulations, pinpointing the best molecules for protein binding, similar to picking the ripest fruit from a vast selection! The team, spanning talents from Rutgers, RPI, and UF, aims to craft novel peptide libraries that outperform current treatments, tackling tough viruses and potentially saving lives. 💡🌐 Let's unlock the future of medicine together! Join the conversation on #AIBioTech #HealthInnovation #MolecularBiology and learn more about this exciting development in disease treatment.

9

#RENCI researchers Anirban Mandal + Cong W. are listed as authors on a paper being presented at 2 PM ET in Room B311 at #SC24. https://lnkd.in/guG7Np4E #LLM #anomalydetection #computationalworkflows #computationalefficiency

11

Accelerating Drug Discovery with Geometric and Generative AI - Insights from a Pioneering Researcher! 🧬🤖 I am excited to announce that Dr. Wengong Jin, Assistant Professor at Northeastern University and Affiliated Researcher at the Broad Institute, will be a featured speaker at the upcoming Boston AI Forum on September 28, 2024! 💡 Why this talk matters: 1️⃣ AI-Driven Drug Discovery: Learn how AI is revolutionizing the pharmaceutical industry, dramatically speeding up the drug discovery process. 2️⃣ Geometric Deep Learning: Discover how this cutting-edge AI technique is being applied to molecular structures for breakthrough insights. 3️⃣ Generative AI in Biology: Explore how AI is generating novel molecular structures, potentially leading to new drug candidates. 4️⃣ Interdisciplinary Innovation: See how the fusion of AI, chemistry, and biology is creating unprecedented opportunities in biotechnology. 🏆 About Dr. Wengong Jin,: • Assistant Professor at Northeastern University, leading research in AI applications for drug discovery and computational biology • Affiliated Researcher at the Broad Institute, collaborating on cutting-edge projects at the intersection of AI and life sciences • Ph.D. from MIT, where he developed pioneering work in machine learning for chemistry and materials science As a researcher pushing the boundaries of AI in life sciences, Wengong's insights into geometric and generative AI applications in drug discovery are set to inspire anyone interested in the future of healthcare and biotechnology. Don't miss this opportunity to hear from a true innovator at the forefront of AI-driven pharmaceutical research! The AI Revolution in Drug Discovery AI is transforming the pharmaceutical landscape, enabling researchers to accelerate drug discovery at an unprecedented pace. Geometric deep learning is providing new ways to analyze complex molecular structures, while generative AI is creating novel drug candidates. These technologies are not only speeding up the discovery process but also uncovering potential treatments that traditional methods might miss. However, challenges remain in data quality, model interpretability, and bridging the gap between in silico predictions and real-world efficacy. Don't miss Dr. Wengong Jin's talk for deeper insights into these groundbreaking advancements! (Note: The image you see is a creative AI-generated cartoon representation inspired by Dr. Wengong Jin. ) #AIDrugDiscovery #GeometricAI #GenerativeAI #BiotechInnovation #BostonAIForum #WengongJin

6

1 Comment

Our #quantumcomputing effort goes beyond purely #quantum algorithms running on quantum devices, and reaching production-level quality in the next few years as quantum hardware continues to mature. We are also actively exploring quantum-inspired algorithms, running on classical devices today: see below for more details as well our job application link!

33

2 Comments

AI will put scientific discovery on an exponential trajectory. DORA integrates multiple AI agents that leverage LLMs, designed to streamline the process of drafting academic papers and other scientific documents including grant and patent applications, internal research summaries, IND applications, etc. It assists researchers in drafting these types of documents with proper referencing through engineered prompts, proprietary databases, and pre-designed content generation workflows

7

New in the AFP: The Category of Sets An axiomatization of category SET on top of HOL, following the presentation given by Halvorson, including Cantor's diagonalization theorem and mathematical induction. https://lnkd.in/g6WTQ-MX

13

Machine learning leads to novel metamaterials in a collaboration by PhD students Xiangbei Liu, Huan Zhao, Ya Tang, and Professor Yan Li, along with researchers from University of Maine and Sandia National Laboratories. The team used their novel approach to "identify a non-periodic metamaterial that does not experience lateral deformation when stretched or compressed—constructed by strategically arranging 64 common unit cells, each having either positive or negative Poisson’s ratios. This unique property is highly desirable for applications such as space actuators, tissue scaffolds, and gaskets," said Li. Their study, entitled "Few-shot learning-based generative design of metamaterials with zero Poisson’s ratio," was published in Materials & Design: https://bit.ly/4digrRK

42

The Carnegie Mellon University team, led by Prof.Tom Mitchell, were able to predict actual brain activity using BERT #LargeLanguageModel (#LLM): https://lnkd.in/eFiMCk3j #machinelearning #deeplearning #AI

6

1 Comment

Calling all aspiring #AI researchers and #NLP scientists! 🗣 🤖 Don't miss this new book 📖 , Natural Language Processing in Biomedicine, co-edited by Hua Xu, PhD, Yale Biomedical Informatics & Data Science vice chair and Yale School of Medicine assistant dean for biomedical informatics. The book includes topics ranging from biomedical #ML to #LLM #genai and more. In our summer newsletter feature, read more about this new essential reading for students and experts alike: https://lnkd.in/eJX3yXHc

134

5 Comments

🌟 Duke University researchers have uncovered a novel signaling mechanism in the body’s touch sensors, Piezo1 and Piezo2. Their study reveals that Piezo1 can signal neighboring proteins without the need for electrical currents, introducing a new dimension to how mechanical forces are understood and potentially revolutionizing treatments for pain and itching. Discover more about how these findings could pave the way for innovative therapies. #Neurobiology #PainManagement #InnovationInScience #DukeUniversity Read more: https://lnkd.in/eurC2He9

2

🧠 "Unlocking New Frontiers: The Promise of Brain-Computer Interfaces and now a new Head Transplant Machine - Entering the reality of Sci-fi?" When I was chatting with Tissue engineering PhD students at Columbia Engineering Alumni day working on develop biological substitutes that restore, maintain, or improve the function of human tissues, I was amazed. But the new machine below takes us to a different level Excited about the transformative potential of Brain-Computer Interfaces (BCIs) and innovations like Nueralink These technologies promise to revolutionize the way we interact with machines, opening up new possibilities for healthcare, communication, and beyond. Imagine a world where human cognition seamlessly integrates with AI, enhancing our capabilities and unlocking unprecedented opportunities.  Let's check the world’s first head transplant system, a groundbreaking device that will represent a landmark achievement in the fields of neuroscience, human engineering, and artificial intelligence. Brain can live several hundred years. It will help terminally ill patients with spinal cord damage. Thanks Alex Zhavoronkov for sharing it initially and I had to spend some time to understand all about it.  #BrainComputerInterface #BCI #Neuralink #AI #Innovation #FutureTech #Healthcare #Communication #HumanAugmentation #TechRevolution #DrugDiscovery #SpinalCordReconstruction #BrainBridge Mayo Clinic Mass General Brigham Stanford Biodesign Digital Health Jayanta (Jay) T Mukherjee, MD, MSc, FACC, FASE, FSCMR Neal Parikh Suneel Kandru, CAGS,MSD,Cert.Ed. Pierantonio Russo MD, FCPP, FAAP, STS Short Clip https://lnkd.in/eEY9ZFbh

4

Today marks the first time that a Nobel Prize was awarded for contributions related to the development of AI. Specifically, the Physics prize was awarded to both Drs. John Hopfield and Geoffrey Hinton for foundational discoveries and inventions that enable machine learning with artificial neural networks. The following write-up from the Nobel committee clarifies why this is a prize in Physics and not Physiology & Medicine, which I would have assumed given AI’s origins in neuroscience. Personally, I'm excited that AI is being represented outside of just the Turing and Fields prizes! I was first introduced to early neural network research in my training as a neuroscientist while an undergraduate at MIT. I was particularly captivated by how work done by McCulloch & Pitts in electronically modeling brain cells could be extended to include Hebbian learning mechanisms for memory. This interest is not only limited to neuroscience, as highlighted in today’s Nobel announcement. Computer hardware improved at a breakneck pace as I progressed through my PhD training, which accelerated my AI research in unprecedented ways. Now, I lead the AI Research team at 1910 Genetics, where we are making daily use of ANNs in application to therapeutic design to realize the promise of AI in drug discovery! https://lnkd.in/eZt3rS4V

32

2 Comments

Check out our recent paper solving PDEs on neuromorphic architectures using physics-informed neural networks (PINNs)! In this paper we discuss how a trained PINN is first converted to a spiking neural network (SNN). To complete the migration to neuromorphic hardware, we quantize floating point values in the network. The results section explores the accuracy, throughput, and power consumption tradeoffs using Intel's Loihi 2 platform. While in an early stage, the results show the promise of how these novel hardware systems can be utilized to solve problems in scientific machine learning. Stay tuned! This was a great multi-institution SEA-CROGS collaboration with Brad Theilman (Sandia), Qian Zhang (Brown), Adar Kahana, Brad Aimone, Nat Trask, and George Karniadakis. Thanks all!

170

3 Comments