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    題名: 總體基因組 Hi-C 接觸圖網絡分析及其重組總體基因組品質預測
    Metagenomic Hi-C Contact Map Network Analysis and Prediction of Recovered Metagenome Assembled Genome Quality
    作者: 王神鐸
    Serrato, Armando
    貢獻者: 張家銘
    Chang, Jia-Ming
    王神鐸
    Armando Serrato
    關鍵詞: Hi-C 接觸圖
    總體基因體學
    總體基因體組裝基因體
    網路相關指標
    機器學習
    生物資料科學
    Hi-C Contact Maps
    Metagenomics
    Metagenome-Assembled genomes
    Network Theory
    Machine Learning
    Bioinformatics
    日期: 2024
    上傳時間: 2024-10-04 10:47:11 (UTC+8)
    摘要: 近年來，總體基因體學利用 Hi-C 定序數據從複雜的微生物群落中收復總體基因體組裝基因體 (MAGs)。本研究進一步驗證了先前提出的假設，即可以通過網路相關的指標來預測 MAG 質量。我們深入分析了總體基因體Hi-C 接觸圖，提取了額外的網路屬性，並整合了來自群聚基因組的生物信息，以提升預測表現。這種網路與生物屬性相結合的特徵在機器學習模型中的應用，不僅增強了 MAG 質量預測，還提供了對微生物群落動態的見解。
    Recent advancements in Metagenomics leverage Hi-C sequencing data to recover Metagenome Assembled Genomes (MAGs) from complex microbial communities. This research advances MAG quality prediction by building upon previous hypotheses that network-based metrics could be used to predict MAG quality. Deeper analysis of metagenomic HI-C contact maps extracts additional network properties and integrates biological information from the clustered genomes, enhancing predictive performance. This combination of network and biological properties used as features in Machine Learning Models, enhances MAG quality prediction and offers insights into microbial community dynamics.
    參考文獻: Sait M, Hugenholtz P, Janssen PH. Cultivation of globally distributed soil bacteria from phylogenetic lineages previously only detected in cultivation-independent surveys. Environ Microbiol. 2002; 4(11):654–66.
    Hugenholtz et al. (2008) Metagenomics. Nature, 455, 481–483.
    Burton et al. (2014) Species-Level Deconvolution of Metagenome Assemblies with Hi-C–Based Contact Probability Maps. G3: GENES, GENOMES, GENETICS, 4, 7.
    Lieberman-Aiden et al. (2009) Comprehensive mapping of long range interactions reveals folding principles of the human genome. Science, 326(5950), 289–293.
    DeMaere et al. (2019) bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes. Genome Biology, 20, 46.
    Cheng et al. (2020) Bin3C_SLM: Deconvoluting metagenomic assemblies via Hi-C connect networks.
    Stalder, T., Press, M.O., Sullivan, S. et al. Linking the resistome and plasmidome to the microbiome. ISME J 13, 2437–2446 (2019). https://doi.org/10.1038/s41396-019-0446-4
    Du, Y., Sun, F. HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps. Genome Biol 23, 63 (2022). https://doi.org/10.1186/s13059-022-02626-w
    Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2014. CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Research, 25: 1043-1055.
    Yuting Hsu (2022) The Network Analysis of the metagenomic Hi-C contact map and its downstream metagenome assembly
    Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature. 1998;393:440–2
    Waltman L, Eck NJ van. A smart local moving algorithm for large-scale modularity-based community detection. European Phys J B. 2013;86:471.
    Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. J Statistical Mech Theory Exp. 2008;2008:P10008.
    Rosvall M, Bergstrom CT. Maps of random walks on complex networks reveal community structure. Proc National Acad Sci. 2008;105:1118–23.
    Ke Zhang, Chenxi Wang, Liping Sun, Jie Zheng, Prediction of gene co-expression from chromatin contacts with graph attention network, Bioinformatics, Volume 38, Issue 19, October 2022, Pages 4457–4465, https://doi.org/10.1093/bioinformatics/btac535
    Ernest YB, Daniel AA. A Review of the Logistic Regression Model with Emphasis on Medical Research. J Data Analysis Information Process. 2019;07:190–207.
    Hyatt, D., Chen, GL., LoCascio, P.F. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010). https://doi.org/10.1186/1471-2105-11-119
    Gao, W., Lin, W., Li, Q. et al. Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder. Nat Protoc 19, 2803–2830 (2024). https://doi.org/10.1038/s41596-024-00999-9
    Scott M. Lundberg and Su-In Lee. 2017. A unified approach to interpreting model predictions. In Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS'17). Curran Associates Inc., Red Hook, NY, USA, 4768–4777.
    Manchanda, N., Portwood, J.L., Woodhouse, M.R. et al. GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations. BMC Genomics 21, 193 (2020). https://doi.org/10.1186/s12864-020-6568-2
    Hunt, M., Kikuchi, T., Sanders, M. et al. REAPR: a universal tool for genome assembly evaluation. Genome Biol 14, R47 (2013). https://doi.org/10.1186/gb-2013-14-5-r47
    描述: 碩士
    國立政治大學
    資訊科學系
    107753048
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0107753048
    資料類型: thesis
    顯示於類別:[資訊科學系] 學位論文

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