Djamel Harbi

Today NIH Director Dr. Jay Bhattacharya presented his vision for embedding replication and reproducibility (R&R) at the core of gold-standard science. Building upon long-standing NIH policies and programs, he outlined a bold, coordinated strategy to advance robust R&R practices across the biomedical enterprise. Read more ➡️ https://lnkd.in/g53Bd3JQ

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NIH has released new guidance about the use of AI in grant writing. Our team of PhD trained editors and writers can help you get your grants submitted without violating NIH guidelines.

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🔍 New in ELSI in Review from ELSIhub | CERA ! This month’s featured review explores the ethical implications of using genetic predictions of aggressive behavior in the criminal justice system—a timely and complex issue at the intersection of genomics, ethics, and public policy. Other reviews in our July edition include communicating genetic test results, use artificial intelligence, and genetic data. 📚 Explore more reviews: https://lnkd.in/e5DbcK3j 📬 Have an ELSI-relevant review to share? Contact us! ELSI in Review is curated by the Center for ELSI Resources and Analysis (CERA) to spotlight recent literature reviews on key ELSI topics. #ELSI #Bioethics #Genetics #CriminalJustice #LiteratureReview

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UMGCCC and the Institute for Genome Sciences are proud to host the Human Tumor Atlas Network (HTAN) meeting at the University of Maryland, Baltimore. The goal of HTAN is to generate molecularly defined, multi-dimensional spatial atlases of tumors as they progress from precancer to cancer, transition from locally invasive to metastatic disease, and respond or become resistant to therapy. #CancerResearch

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AI is reshaping clinical care across genomics and genetic counseling. The latest issue of AI/ML in Genomics and Genetic Counseling explores what that shift means in practice, from clinical reasoning and patient communication to policy, safety and misinformation risks. Explore new perspectives and practical resources from the NSGC AI/ML Subcommittee at the link in the comments.

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🚨The 7th annual data release from the Adolescent Brain Cognitive Development (ABCD) Study is now live along with the Data Exploration & Analysis Portal, a graphical user interface for creating, visualizing, and analyzing NIH Brain Development Cohorts datasets in place. The ABCD 7.0 Data Release includes data from the largest long-term study of brain development and child health in the U.S. Interested parties may visit the NIH Brain Development Cohorts Data Hub to gain secure, controlled access: https://bit.ly/4uDLe4l

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To use or not to use AI? How much we can trust AI? Watch this very interesting conversation with bioinformatician and hear their thoughts and insights about using AI in bioinformatics organized by Robert Aboukhalil founder of OMGenomics Labs. #bioinformatics, #leadning #AI #programing #Claude #LLM

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Learn about implementing machine learning models for time series forecasting at the AMIA (American Medical Informatics Association) 2025 Annual Symposium on November 19. The Center for Applied Artificial Intelligence's Aaron Mullen presents his original talk on "Implementation and Assessment of Machine Learning Models for Forecasting Suspected Opioid Overdoses in Emergency Medical Services Data." This talk presents efforts to accurately predict counts of future suspected opioid overdoses in the state of Kentucky. By attending this presentation, learners will be able to guide ML models to forecast opioid overdoses, evaluate the performance of these models, and address data problems such as sparsity and missing data. #AMIA #ML #TimeSeriesForecasting #DataScience #Informatics #AMIA2025 #ClinicalInformatics #HealthResearch #HealthInformatics #MachineLearning

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NIH Highlights AI and Advanced Computing in New Data Science Strategic Plan - Datanami: Biomedical research generates large volumes of data, and NIH aims to ensure that researchers have access to advanced tools to analyze these resources ... #bigdata #cdo #cto

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UNC School of Medicine/SDSS faculty member Melissa Haendel will deliver two talks this week on health informatics and rare disease diagnostics. These talks highlight the intersection of data science and health care. Find out more information and consider attending one seminar or both! 💡Interoperability at all Scales: From Data Bits and Bytes to National Public Health Surveillance 📅 Wednesday, Sept. 17 | 4–5 p.m. | 321 MacNider Hall Hosted by Carolina Health Informatics Program 🔗 https://lnkd.in/ex-6QYjn 🧬From Data to Diagnosis: Quantifying Patient Role in Rare Disease Diagnostics 📅 Thursday, Sept. 18 | 3:30-4:30 p.m. | Michael Hooker Research Center 0001 Hosted by Department of Biostatistics at UNC-Chapel Hill, UNC Gillings School of Global Public Health 🔗 https://lnkd.in/eeV4HY4m #DataScience #HealthInformatics #RareDisease #UNCResearch

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NIH recently announced big changes: new rules around AI use in proposals and stricter limits on PI submissions. These updates take effect Sept. 25, 2025. We break down what this means and how to plan ahead ➡️https://hubs.ly/Q03D-Sn10 #NIH #FederalFunding #AI

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🚀 New Publication Alert! We’re excited to share a new Journal of Clinical and Translational Science paper from the ENACT Network: “Development and Validation of Natural Language Processing Algorithms in the National ENACT Network.” This work demonstrates how federated NLP (Natural Language Processing) can be developed and validated across a large, multi-institutional network, and unlock insights from clinical text while preserving local control of data. 🔹 Multisite ENACT NLP Working Group across 13 institutions 🔹 Validated NLP algorithms spanning rare disease phenotyping, SDOH, opioid use disorder, sleep, and delirium 🔹 Extension of the ENACT data model to support standardized NLP outputs 🔹 Proof that federated NLP at scale is both feasible and impactful 📄 Read the paper: https://lnkd.in/gcZdhYAe

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The NIH announced that their Bridge2AI program is advancing to its second stage. Here's what that means for you: The next Bridge2AI stage focuses on two initiatives: innovation funnels and network for AI health science. Innovation funnels focus on utilizing AI-ready datasets to create tools and insights that utilize AI to contribute to health science. The network for AI health science aims to create a network of experts to develop safety measures regarding AI in health research both now and in the future. As the NIH advances with this program, you can expect: - Clearer guidelines surrounding AI in health and health research - A growing number of AI products to use when investigating health challenges - Training programs to build an AI-proficient workforce - A growing community of researchers excited and transparent about using AI Learn more at https://lnkd.in/ezGG89HA

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Bioinformatics Toolbox provides algorithms and apps for building bioinformatics pipelines, next-generation sequencing (NGS), microarray analysis, mass spectrometry, and gene ontology Learn more about Bioinformatics Toolbox: https://spr.ly/6041Cg4V7

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𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗧𝗼𝗼𝗹𝘀 𝗔𝗿𝗲 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗚𝗲𝗻𝗼𝗺𝗶𝗰𝘀 𝗮𝗻𝗱 𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀  Modern research labs require precision, efficiency, and reliable workflows to analyze complex biological samples. 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗵𝗼𝘄 𝗻𝗲𝘅𝘁-𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗿𝘆 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗮𝗿𝗲 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻𝗶𝗻𝗴 𝗴𝗲𝗻𝗼𝗺𝗶𝗰 𝗮𝗻𝗱 𝗽𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝘄𝗶𝘁𝗵  𝗚𝗲𝗻𝗼𝗺𝗶𝗰𝘀 𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗘𝗾𝘂𝗶𝗽𝗺𝗲𝗻𝘁: https://lnkd.in/e-UVdp5P 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗹𝗲𝗮𝗱𝗶𝗻𝗴 𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗿𝗶𝗲𝘀 𝗮𝗿𝗲 𝗮𝗰𝗵𝗶𝗲𝘃𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗲𝗾𝘂𝗶𝗽𝗺𝗲𝗻𝘁:   • Accurate nucleic acid & protein analysis for sequencing and detection  • Reliable sample prep & extraction for consistent, high-purity results  • Integrated lab informatics & automation for smoother workflows  • Faster throughput with optimized, user-friendly platforms  • Greater reproducibility through advanced analytical precision As scientific demands grow, modern tools are helping laboratories achieve stronger accuracy and improve productivity across every research stage. If your facility is upgrading its genomic or proteomic capabilities, now is the right time to adopt advanced lab systems. 𝗧𝗼𝗽 𝗖𝗮𝘁𝗲𝗴𝗼𝗿𝗶𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗠𝗼𝗿𝗲 𝗔𝗯𝗼𝘂𝘁:  𝗡𝘂𝗰𝗹𝗲𝗶𝗰 𝗔𝗰𝗶𝗱 & 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: https://lnkd.in/ekb9SCvg 𝗦𝗮𝗺𝗽𝗹𝗲 𝗣𝗿𝗲𝗽 & 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻: https://lnkd.in/eyjmJCHH 𝗟𝗮𝗯 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀 & 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: https://lnkd.in/eta8hdJA #Genomics #Proteomics #LabTechnology #MolecularBiology #SamplePrep #LaboratoryAutomation #ResearchTools #ScientificEquipment #B2BTech 

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NIH’s staff within DCTD coauthored a report on the virtual workshop titled “Digital Pathology Imaging (DPI) in Cancer Clinical Trials and Research” held on March 6-7, 2024. Nearly 400 attendees from academia, industry, government, and non-government organizations discussed the expanding role of DPI in translational cancer research, biomarker studies, clinical trials, and pharmaceutical development. The authors reflected on current challenges, practical solutions, and future directions in pathology with practical recommendations for integration that include: - Invest in DPI infrastructure alongside standardized protocols and IT staff - Optimize workflows before digitization and after scanning slides for remote access - Apply Digital Imaging and Communication in Medicine (DICOM) whole-slide imaging in NCI clinical trials for interoperability - Develop structured annotation frameworks and scalable tools to create AI-ready datasets across institutions - Adapt biobanking workflows for biospecimen–image linkage and specimen tracking More information here: https://lnkd.in/euwTtMEJ

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This major partner to NIH and leading bioscience and information technology company, that offers advancements in translational research, health informatics, and data science applications to research centers and healthcare organizations around the globe, secured a 3-year task from the National Institutes of Health (NIH) National Institute of Allergy and Infectious Diseases (NIAID) to provide professional, scientific, and technical support services for the Vaccine Research Center (VRC) and Vaccine Production Program (VPP). ==>> https://lnkd.in/eD4RdC-x Axle | Vidya Chari | Jason Callahan

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For clinical AI to be trusted in healthcare, it first must develop an understanding of clinical evidence and disease prevalence, plus the ability to explain its reasoning and confidence in its prediction. Yanjun Gao, PhD, biomedical researcher at the University of Colorado Anschutz conducts research to ensure that implementations of Large Language Models (LLMs) in healthcare are safe, trustworthy and aligned with human needs.

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