| 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. |
