Showing 2,301 - 2,320 results of 5,161 for search '"genomics"', query time: 0.05s Refine Results
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    Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

    Published 2024-12-01
    “…The emerging field of radiogenomics utilizes statistical methods to correlate radiographic tumor features with genomic characteristics from biopsy samples. Radiomic techniques automate the precise extraction of imaging features from tumor regions in radiographic scans, which are subjected to machine learning (ML) to predict genomic attributes. …”
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    Introduction to genetic analysis / by Griffiths, Anthony J. F., Doebley, John F., Peichel, Catherine L., 1969-, Wassarman, David A.

    Published 2020
    Table of Contents: “…The Genetic Control of Development -- 14. Genomes and Genomics -- Part III. Core Principles in Mutation, Variation, and Evolution -- 15. …”
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    Advances in chromosomal microarray analysis: Transforming neurology and neurosurgery by Wireko Andrew Awuah, Muhammad Hamza Shah, Vivek Sanker, Krishitha Meenu Mannan, Sruthi Ranganathan, Princess Afia Nkrumah-Boateng, Mabel Frimpong, Kwadwo Darko, Joecelyn Kirani Tan, Toufik Abdul-Rahman, Oday Atallah

    Published 2025-01-01
    “…Over the past two decades, genomics has transformed our understanding of various clinical conditions, with Chromosomal Microarray Analysis (CMA) standing out as a key technique. …”
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    High-throughput phenotyping techniques for forage: Status, bottleneck, and challenges by Tao Cheng, Dongyan Zhang, Gan Zhang, Tianyi Wang, Weibo Ren, Feng Yuan, Yaling Liu, Zhaoming Wang, Chunjiang Zhao

    Published 2025-03-01
    “…These include establishing uniform data collection standards, designing effective algorithms to handle complex genetic and environmental interactions, deepening the cross-exploration of phenomics-genomics, solving the problem of pathological inversion of forage phenotypic growth monitoring models, and developing low-cost forage phenotypic equipment. …”
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