[1] Ehrlich, Melanie. "DNA hypomethylation in cancer cells." Epigenomics 1.2 (2009): 239-259.
[2] Ehrlich, Melanie, and Michelle Lacey. "DNA hypomethylation and hemimethylation in cancer." Epigenetic Alterations in Oncogenesis. Springer, New York, NY, 2013. 31-56.
[3] Moore, Lisa D., Thuc Le, and Guoping Fan. "DNA methylation and its basic function." Neuropsychopharmacology 38.1 (2013): 23.
[4] Beck, Samuel, et al. "Implications of CpG islands on chromosomal architectures and modes of global gene regulation." Nucleic acids research46.9 (2018): 4382-4391.
[5] Singh, Sidhartha, Deepika Rai, and Ayush Praveen. "DNA Methylation in Cancer.".
[6] Frigola, Jordi, et al. "Differential DNA hypermethylation and hypomethylation signatures in colorectal cancer." Human molecular genetics 14.2 (2004): 319-326.
[7] Rapley, Ralph, and Stuart Harbron, eds. Molecular analysis and genome discovery. J. Wiley, 2004.
[8] Pfeifer, Gerd. "Defining driver DNA methylation changes in human cancer." International journal of molecular sciences 19.4 (2018): 1166.
[9] Wu, Hao, et al. "Redefining CpG islands using hidden Markov models." Biostatistics 11.3 (2010): 499-514.
[10] Zheng, Hao, Shi-Wen Jiang, and Hongwei Wu. "A Review on the Techniques for Characterizing and Predicting Human Genomic DNA Methylation." Current Bioinformatics 8.2 (2013): 140-147.
[11] Claverie, Jean-Michel, and Cedric Notredame. Bioinformatics for dummies. John Wiley & Sons, 2006.
[12] Bi Raut, Shital A., S. R. Sathe, and Adarsh Raut. "Bioinformatics: Trends in gene expression analysis." 2010 International Conference on Bioinformatics and Biomedical Technology. IEEE, 2010.R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press.
[13] https://byjus.com/biology/dna-replication-machinery-enzymes/
[14] https://epigenetics-genetics.weebly.com/.
[15] Rakyan, Vardhman K., et al. "DNA methylation profiling of the human major histocompatibility complex: a pilot study for the human epigenome project." PLoS biology 2.12 (2004): e405.
[16] Noushmehr, Houtan, et al. "Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma." Cancer cell 17.5 (2010): 510-522.
[17] Wang, Yiheng, et al. "Predicting DNA methylation state of CpG dinucleotide using genome topological features and deep networks." Scientific reports 6 (2016): 19598.
[18] Pfeifer, Gerd. "Defining driver DNA methylation changes in human cancer." International journal of molecular sciences 19.4 (2018): 1166.
[19] Bock, Christoph, et al. "CpG Island mapping by epigenome prediction." PLoS computational biology 3.6 (2007): e110.
[20] Han, Leng, et al. "CpG island density and its correlations with genomic features in mammalian genomes." Genome biology9.5 (2008): R79.
[21] Gardiner-Garden, M., and M. Frommer. "CpG islands in vertebrate genomes." Journal of molecular biology 196.2 (1987): 261-282.
[22] Takai, Daiya, and Peter A. Jones. "Comprehensive analysis of CpG islands in human chromosomes 21 and 22." Proceedings of the national academy of sciences 99.6 (2002): 3740-3745.
[23] Hackenberg, Michael, et al. "CpGcluster: a distance-based algorithm for CpG-island detection." BMC bioinformatics 7.1 (2006): 446.
[24] Wu, Hao, et al. "Redefining CpG islands using hidden Markov models." Biostatistics 11.3 (2010): 499-514.
[25] Yu, Ning, et al. "GaussianCpG: a Gaussian model for detection of CpG island in human genome sequences." BMC genomics 18.4 (2017): 392.
[26] Yang, Cheng-Hong, et al. "A hybrid approach for CpG island detection in the human genome." PloS one 11.1 (2016): e0144748.
[27] Boukelia, Abdelbasset, et al. "A Novel Algorithm for CpG Island Detection in Human Genome Based on Clustering and Chaotic Particle Swarm Optimization." International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics. Springer, Cham, 2016.
[28] https://www.ncbi.nlm.nih.gov/genome/gdv/.
[29] http://genome.ucsc.edu/cgi-bin/hgGateway.
[30] https://www.ensembl.org/Homo_sapiens/Info/Index
[31] Weitschek, Emanuel, et al. "Genomic data integration: A case study on next generation sequencing of cancer." 2016 27th International Workshop on Database and Expert Systems Applications (DEXA). IEEE, 2016.
[32] He, Ximiao, et al. "MethyCancer: the database of human DNA methylation and cancer." Nucleic acids research 36.suppl_1 (2007): D836-D841.
[33] Heisler, Lawrence E., et al. "CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome." Nucleic acids research 33.9 (2005): 2952-2961.
[34] Amoreira, Celine, Winfried Hindermann, and Christoph Grunau. "An improved version of the DNA Methylation database (MethDB)." Nucleic acids research 31.1 (2003): 75-77.
[35] Bradbury, Jane. "Human epigenome project—up and running." PLoS biology 1.3 (2003): e82.
[36] Rollins, Robert A., et al. "Large-scale structure of genomic methylation patterns." Genome research 16.2 (2006): 157-163.
[37] Gu, Fei, et al. "CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers." PloS one 8.4 (2013): e60980.
[38] http://genome.ucsc.edu.
[39] Huang, Wei-Yun, et al. "MethHC: a database of DNA methylation and gene expression in human cancer." Nucleic acids research 43.D1 (2014): D856-D861.
[40] Mao, Zijing, et al. "BIMMER: a novel algorithm for detecting differential DNA methylation regions from MBDCap-seq data." BMC bioinformatics 15.12 (2014): S6.
[41] Barazandeh, A., et al. "Genome-wide analysis of CpG islands in some livestock genomes and their relationship with genomic features." Czech Journal of Animal Science 61.11 (2016): 487-495.
[42] Pavlovic, Milos, et al. "DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes." Bioinformatics 33.19 (2017): 2986-2994.
[43] Kundaje, Anshul, et al. "Integrative analysis of 111 reference human epigenomes." Nature 518.7539 (2015): 317.
[44] Wu, Chengchao, et al. "Genome-wide prediction of DNA methylation using DNA composition and sequence complexity in human." International journal of molecular sciences 18.2 (2017): 420.
[45] http://www. ncbi.nlm.nih.gov.
[46] Pan, Gaofeng, et al. "A novel computational method for detecting DNA methylation sites with DNA sequence information and physicochemical properties." International journal of molecular sciences 19.2 (2018): 511.
[47] Smallwood, Sébastien A., et al. "Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity." Nature methods 11.8 (2014): 817.
[48] Angermueller, Christof, et al. "DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning." Genome biology 18.1 (2017): 67.
[49] Hou, Yu, et al. "Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas." Cell research 26.3 (2016): 304.
[50] Khwaja, Mohammed, Melpomeni Kalofonou, and Chris Toumazou. "A deep belief network system for prediction of DNA methylation." 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2017.
[51] C. Wrzodek, Clemens, et al. "Linking the epigenome to the genome: correlation of different features to DNA methylation of CpG islands." PloS one 7.4 (2012): e35327.
[52] ENCODE Project Consortium. "An integrated encyclopedia of DNA elements in the human genome." Nature 489.7414 (2012): 57.
[53] Celli, Fabrizio, Fabio Cumbo, and Emanuel Weitschek. "Classification of large DNA methylation datasets for identifying cancer drivers." Big data research 13 (2018): 21-28.
[54] Meng, Xiangrui, et al. "Mllib: Machine learning in apache spark." The Journal of Machine Learning Research 17.1 (2016): 1235-1241.
[55] Cestarelli, Valerio, et al. "CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules." Bioinformatics 32.5 (2015): 697-704.
[56] https://gdc.nci.nih.gov/.