This reprint highlights recent developments in computational biology, deep learning algorithms, and cancer biology that enable the decoding of the cancer genome and tumor microenvironment ecosystem. One of its major focuses is on the integration of multi-omics data such as WGS, WES, scRNAseq, spatial transcriptomics, and proteomics, along with radiomics and digital pathology, to better understand cancer initiation, evolution, drug-tolerant persister cancer states, and full therapy resistance. Unbiased, systematic analyses ...
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This reprint highlights recent developments in computational biology, deep learning algorithms, and cancer biology that enable the decoding of the cancer genome and tumor microenvironment ecosystem. One of its major focuses is on the integration of multi-omics data such as WGS, WES, scRNAseq, spatial transcriptomics, and proteomics, along with radiomics and digital pathology, to better understand cancer initiation, evolution, drug-tolerant persister cancer states, and full therapy resistance. Unbiased, systematic analyses using artificial intelligence, machine learning, and deep learning approaches could advance our knowledge and improve cancer treatment. In this reprint, leading experts in the field share their insights, research findings, and visions for the future of cancer informatics. Cutting-edge computational approaches and bioinformatics algorithms provide powerful toolkits to systematically identify clinically relevant biomarkers for early cancer diagnosis, prognosis, and precision cancer therapy stratification.
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Add this copy of Application of Multi-Omics Analysis in Cancer Diagnosis to cart. £49.29, like new condition, Sold by GreatBookPricesUK5 rated 4.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2024 by Mdpi AG.
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Fine. Sewn binding. Cloth over boards. 180 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Application of Multi-Omics Analysis in Cancer Diagnosis to cart. £49.78, new condition, Sold by GreatBookPricesUK5 rated 4.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2024 by Mdpi AG.
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New. Sewn binding. Cloth over boards. 180 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
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Add this copy of Application of Multi-Omics Analysis in Cancer Diagnosis to cart. £60.55, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2024 by Mdpi AG.
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Fine. Sewn binding. Cloth over boards. 180 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Application of Multi-Omics Analysis in Cancer Diagnosis to cart. £61.11, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2024 by Mdpi AG.
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Seller's Description:
New. Sewn binding. Cloth over boards. 180 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
