📥 Inbound Notifications 669

Time â–¾ Id From To Type Content
2026-04-05 06:43:49 urn:uuid:beb88aa2-b064-43da-87d3-40ec2d6fa95a https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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            "All CT images were viewed with lung window parameters (width, 1500 HU; level, -550 HU) using the SPYD software developed by Owkin.",
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            "Spearman's correlation between fork speed and RT was computed using the stat_cor() function of the ggpubr R package. Statistical analysis. The R environment v4.0.5 was used for all the analyses."
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2026-04-05 06:43:08 urn:uuid:2cd598f7-099c-46a4-9fd5-e37176d1d654 https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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2026-04-05 06:43:08 urn:uuid:1c72ee83-0b94-48ec-8cdf-d04d6bc0c53e https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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            "RepNano 13 and other published BrdU basecallers, DNAscent 15 and DNAscent v2 16 , were also assessed for comparison.",
            "RepNano v2 architecture.",
            "RepNano v2 training.",
            "RepNano v2 was trained using nanopore reads of the 11 genomic DNA samples with various BrdU substitution rates described above (BrdU contents measured by mass spectrometry of 0, 9.4, 16.6, 27.9, 35.1, 46.1, 54.8, 59, 72.6, 78.8 and 80.3%).",
            "using RepNano v2 outputs, then trained our model a second time using the outputs of the first training and adding specific false positive BrdU signals to the training dataset in order to reduce background and false-positive signals.",
            "The final network (RepNano v2 architecture) was trained on this cleaner dataset of 400 reads per sample.",
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            "megalodon) and estimated BrdU incorporation probability at each thymidine site rather than over 96 bp windows as in RepNano 13 (see the 'Methods' section).",
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            "First, we modified the architecture of RepNano convolutional neural network 13 in order to obtain a nucleotide resolution for BrdU detection, creating RepNano v2.",
            "For each of the 11 genomic DNA samples with different BrdU substitution rates described above, a set of 8000 nanopore reads were basecalled either with Megalodon or with DNAscent v1 15 , DNAscent v2 16 , RepNano 13 transition matrices (RepNano_TM) and RepNano convolutional neural network (RepNano_CNN).",
            "For each of the 11 genomic DNA samples with different BrdU substitution rates described above, a set of 8000 nanopore reads were basecalled either with Megalodon or with DNAscent v1 15 , DNAscent v2 16 , RepNano 13 transition matrices (RepNano_TM) and RepNano convolutional neural network (RepNano_CNN)."
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2026-04-05 06:43:07 urn:uuid:e9bf4b17-b6e1-4714-ac89-5f823dd56932 https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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2026-04-05 06:43:07 urn:uuid:ab9be0fb-1d3d-4d52-8e0d-c7272ae1229e https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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2026-04-05 06:43:07 urn:uuid:3d335adb-b62f-4c9d-8f76-c956b13264fe https://datalake.inria.fr https://inria.hal.science ["Offer","coar-notify:ReviewAction"]
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