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    題名: 基於三級交聯圖與表觀基因特徵分群對基因組切割
    Genome segmentation based on the embedding of chromosome contact and ChIP-seq networks
    作者: 張修誠
    Chang, Hsiu-Cheng
    貢獻者: 張家銘
    Chang, Jia-Ming
    張修誠
    Chang, Hsiu-Cheng
    關鍵詞: 高通量染色體捕獲技術
    染色質免疫沉澱-測序
    資訊融合
    節點嵌入
    分群
    日期: 2024
    上傳時間: 2024-03-01 13:42:29 (UTC+8)
    摘要: 高通量染色體捕獲技術（Hi-C）的全基因組染色體接觸矩陣可用於研究染色體三級結構組織，組織由大至小可分為隔間、子隔間以及拓撲結構域。本研究透過高通量染色體捕獲技術和染色質免疫沉澱-測序（ChIP-seq）兩項技術獲得了基因組的空間結構和基因間相互作用的重要信息，應用圖論的節點嵌入和資訊融合的技術並分群，以高解析度資料處理不同尺度的組織分區，提供更全面的基因組切割分析，透過降維視覺化和量化分析結果呈現有效找出基因體區分。
    參考文獻: 1. Lieberman-Aiden, Erez, et al. "Comprehensive mapping of long-range interactions reveals folding principles of the human genome." Science 326.5950 (2009): 289-293.
    2. Dekker, Job, et al. "Capturing chromosome conformation." Science 295.5558 (2002): 1306-1311.
    3. Van Berkum, Nynke L., et al. "Hi-C: a method to study the three-dimensional architecture of genomes." JoVE (Journal of Visualized Experiments) 39 (2010): e1869.
    4. Johnson, David S., et al. "Genome-wide mapping of in vivo protein-DNA interactions." Science 316.5830 (2007): 1497-1502.
    5. Illumina et al.Pub. No. 770-2007-007 Current as of 26 November 2007. Whole-Genome Chromatin IP Sequencing (ChIP-seq).
    6. Rao, Suhas SP, et al. "A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping." Cell 159.7 (2014): 1665-1680.
    7. Peifer, Martin, et al. "Telomerase activation by genomic rearrangements in high-risk neuroblastoma." Nature 526.7575 (2015): 700-704.
    8. Ashoor, Haitham, et al. "Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data." Nature communications 11.1 (2020): 1173.
    9. Tang, Jian, et al. "Line: Large-scale information network embedding." Proceedings of the 24th international conference on world wide web. 2015.
    10. Grover, Aditya, and Jure Leskovec. "node2vec: Scalable feature learning for networks." Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining. 2016.
    11. Hou, Chengbin, Shan He, and Ke Tang. "RoSANE: Robust and scalable attributed network embedding for sparse networks." Neurocomputing 409 (2020): 231-243.
    12. 吳映函.HiCSeg: an interactive genome segmentation cross samples and species (2021).
    13. Blondel, Vincent D., et al. "Fast unfolding of communities in large networks." Journal of statistical mechanics: theory and experiment 2008.10 (2008): P10008.
    14. Traag, Vincent A., Ludo Waltman, and Nees Jan Van Eck. "From Louvain to Leiden: guaranteeing well-connected communities." Scientific Reports 9.1 (2019): 5233.
    15. Knight, Philip A., and Daniel Ruiz. "A fast algorithm for matrix balancing." IMA Journal of Numerical Analysis 33.3 (2013): 1029-1047.
    16. Van der Maaten, Laurens, and Geoffrey Hinton. "Visualizing data using t-SNE." Journal of machine learning research 9.11 (2008).
    17. Vinh, Nguyen Xuan, Julien Epps, and James Bailey. "Information theoretic measures for clusterings comparison: is a correction for chance necessary?." Proceedings of the 26th annual international conference on machine learning. 2009.
    18. Rousseeuw, Peter J. "Silhouettes: a graphical aid to the interpretation and validation of cluster analysis." Journal of computational and applied mathematics 20 (1987): 53-65.
    19. Caliński, Tadeusz, and Jerzy Harabasz. "A dendrite method for cluster analysis." Communications in Statistics-theory and Methods 3.1 (1974): 1-27.
    20. Eigenvector,Juicer.(2017).https://github.com/aidenlab/juicer/wiki/Eigenvector
    21. Guo, Kun, et al. "Network Embedding Based on Biased Random Walk for Community Detection in Attributed Networks." IEEE Transactions on Computational Social Systems (2022).
    22. Robinson, James T., et al. "Juicebox. js provides a cloud-based visualization system for Hi-C data." Cell systems 6.2 (2018): 256-258.
    描述: 碩士
    國立政治大學
    資訊科學系
    110753165
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0110753165
    資料類型: thesis
    顯示於類別:[資訊科學系] 學位論文

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