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Lastest news items (10)
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Scientists have created a new way to measure how quickly a person's body is aging by analyzing two kinds of blood data with artificial intelligence. The method, called gtAge, uses information from the sugars attached to antibodies and from gene activity in blood cells. By combining these data with deep reinforcement learning, the researchers built a model that predicts biological age more accurately than traditional approaches. They say it could one day help track how lifestyle or medical treatments slow aging and reduce disease risk. ARTICLE
Xia, Yao, Syed Mohammed Shamsul Islam, Xingang Li, Abdul Baten, Xuerui Tan, and Wei Wang. 2025. "Deep Reinforcement Learning--Driven Multi-Omics Integration for Constructing gtAge: A Novel Aging Clock from IgG N-glycome and Blood Transcriptome." Engineering. https://doi.org/10.1016/j.eng.2025.08.016.
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Researchers have developed a powerful new system called MetaGraph that allows scientists to search through enormous DNA and RNA databases containing more than a quadrillion genetic letters. The tool can rapidly find genetic sequences across global repositories such as the Sequence Read Archive, making it possible to uncover links between genes, microbes, and diseases that were previously hidden within petabytes of raw data. ARTICLE
Karasikov, Mikhail, Harun Mustafa, Daniel Danciu, Oleksandr Kulkov, Marc Zimmermann, Christopher Barber, Gunnar Rätsch, and André Kahles. "Efficient and Accurate Search in Petabase-Scale Sequence Repositories." Nature (October 8, 2025). https://doi.org/10.1038/s41586-025-09603-w.
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Frontiers, an open-science publisher, has launched FAIR² Data Management, an AI-powered service designed to address the fact that approximately 90% of scientific data never gets reused to drive new discoveries. The platform automates data curation, compliance checking, and formatting – tasks that previously took months – to make research datasets properly preserved, citable, and reusable by both humans and AI systems. Out of every 100 datasets created, about 80 remain in labs and only one typically leads to new findings, a bottleneck that delays advances in fields like cancer treatment and climate research. The service has completed pilot projects spanning COVID variants, brain injury research, climate indicators, and biodiversity, with researchers noting that it could accelerate scientific progress while ensuring data creators receive proper credit for their work.
Source: https://www.frontiersin.org/news/2025/10/13/90-of-science-is-lost-frontiers-revolutionary-ai-powered-service-transforms
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A new method called SDR-seq – short for single-cell DNA-RNA sequencing – enables researchers to measure DNA mutations and gene activity within the same cell, offering a direct view of how genetic variation shapes cell function. The approach improves on previous multi-omic techniques, which often suffered from data loss and could not reliably connect genotype to transcriptomic effects at single-cell resolution. By reducing allelic dropout and scaling to hundreds of genomic targets, SDR-seq provides more accurate and comprehensive insights, demonstrating its effectiveness in both laboratory models and primary tumour samples. ARTICLE
Lindenhofer, Dominik, Christian E. Saliba, René Schmutz, et al. "Functional Phenotyping of Genomic Variants Using Joint Multiomic Single-Cell DNA--RNA Sequencing." Nature Methods (2025). https://doi.org/10.1038/s41592-025-02805-0.
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A large-scale genomic study of more than 218,000 participants in Geisinger's MyCode Community Health Initiative has revealed that rare genetic disorders (RGDs) may be more common and less clinically recognised than previously thought. Researchers found that 2.5% of participants carried high-confidence pathogenic variants linked to RGDs, yet only about one in five of those who were positive had corresponding clinical diagnoses. The findings suggest that genomic-first approaches could identify many undiagnosed cases, refine estimates of disease penetrance, and improve early diagnosis and management of RGDs. ARTICLE
Torene, Rebecca I., et al. "A Scalable Approach for Genomic-First Rare Disorder Detection in a Healthcare-Based Population." The American Journal of Human Genetics, published online October 6, 2025. https://doi.org/10.1016/j.ajhg.2025.09.010. [not open-access]
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Researchers analyzed ancient microbial DNA from 483 mammoth specimens, including 440 newly sequenced samples dating back up to 1.1 million years, and identified six microbial clades likely associated with living mammoths – spanning Actinobacillus, Pasteurella, Streptococcus, and Erysipelothrix. They reconstructed partial genomes of Erysipelothrix from the oldest specimen – representing the oldest authenticated host-associated microbial DNA known to date – and also found putative virulence factors in some lineages, including a Pasteurella relative linked to disease in modern elephants. ARTICLE
Benjamin Guinet, et al. 2025. "Ancient Host-Associated Microbes Obtained from Mammoth Remains." Cell, October 3, 2025. https://doi.org/10.1016/j.cell.2025.08.003
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Early findings from a clinical trial suggest that a new gene therapy, administered directly into the brain, may slow the progression of Huntington's disease. The therapy targets the faulty gene responsible for the condition, aiming to reduce the production of the toxic protein that damages brain cells. While the trial involved only a small number of participants, the results represent an important step toward developing the first treatment to alter the course of the disease, which currently has no cure and is typically managed only through supportive care.
Source: https://www.bbc.com/news/articles/cevz13xkxpro
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A new study in Nature Genetics identifies over 400 genes associated with accelerated aging, revealing distinct genetic factors behind frailty subtypes like cognitive decline and mobility issues.
Source: https://www.colorado.edu/today/2025/08/18/why-do-some-people-age-faster-others-study-ids-genes-play
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Futurism reports that researchers at Stanford and the Arc Institute used an AI model called Evo – trained on millions of bacteriophage genomes – to design 302 variants of the E. coli-infecting phage phiX174, chemically synthesized ("printed") them, and found 16 that successfully infected and lysed bacteria, in some cases outperforming the wild type and even being distinct enough to count as new species. The study is a bioRxiv preprint (not yet peer-reviewed) and is framed as the first demonstration of AI writing coherent, genome-scale sequences that function in the lab; experts quoted warn about ethical and biosafety risks, with Craig Venter urging caution about any viral-enhancement work and noting potential misuse for bioweapons, while the authors stress that designing a full organism remains far off.
Source: https://futurism.com/health-medicine/ai-designed-virus-printed
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Grant Belgard of The Bioinformatics CRO (https://www.bioinformaticscro.com) interviewed me about the past, present and future of Bioinformatics.org in his podcast.
The podcast is now online. Here are the links to the episode on Apple, Spotify, and the Bioinformatics CRO website:
Apple: https://podcasts.apple.com/us/podcast/the-bioinformatics-cro-podcast/id1535886933?i=1000724490820
Spotify: https://open.spotify.com/episode/1GTFyxUKBqTNt7E9g8X4WH?si=5IzdGrn-Tqys4aZq4kSlVA
Website: https://www.bioinformaticscro.com/podcast/jeff-bizzaro/
About The Bioinformatics CRO: It is a fully distributed contract research company that serves the computational biology needs of academics, science and research institutes, pharmaceutical companies, and biotechs, with a focus on genomics.
Cheers,
Jeff
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