BMB Reports : eISSN 1976-670X

Cited by CrossRef (18)

  1. Antoine Daunay, Laura G. Baudrin, Jean-François Deleuze, Alexandre How-Kit. Evaluation of six blood-based age prediction models using DNA methylation analysis by pyrosequencing. Sci Rep 2019;9
    https://doi.org/10.1038/s41598-019-45197-w
  2. Ana Belén Márquez-Ruiz, Lucas González-Herrera, Juan de Dios Luna, Aurora Valenzuela. DNA methylation levels and telomere length in human teeth: usefulness for age estimation. Int J Legal Med 2020
    https://doi.org/10.1007/s00414-019-02242-7
  3. Huan Zhao, Huan Tian, Peng Bai, Zhilong Li, Duo Peng, Dan Chen, Tao Feng, Haoyan Jiang, Xinyao Li, Weibo Liang, Fuping Li. Effect of infertile semen samples on mRNA-based body fluid identification by KLK3 and PRM1. Forensic Science International: Genetics Supplement Series 2019;7:507
    https://doi.org/10.1016/j.fsigss.2019.10.069
  4. Renuka Prasad G, Eek-hoon Jho. A concise review of human brain methylome during aging and neurodegenerative diseases. BMB Rep. 2019;52:577
    https://doi.org/10.5483/BMBRep.2019.52.10.215
  5. A. D. Zolotarenko, E. V. Chekalin, S. A. Bruskin. Modern Molecular Genetic Methods for Age Estimation in Forensics. Russ J Genet 2019;55:1460
    https://doi.org/10.1134/S1022795419120147
  6. Claudio Franceschi, Paolo Garagnani, Cristina Morsiani, Maria Conte, Aurelia Santoro, Andrea Grignolio, Daniela Monti, Miriam Capri, Stefano Salvioli. The Continuum of Aging and Age-Related Diseases: Common Mechanisms but Different Rates. Front. Med. 2018;5
    https://doi.org/10.3389/fmed.2018.00061
  7. Sang-Eun Jung, Seung Min Lim, Sae Rom Hong, Eun Hee Lee, Kyoung-Jin Shin, Hwan Young Lee. DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes for age prediction from blood, saliva, and buccal swab samples. Forensic Science International: Genetics 2019;38:1
    https://doi.org/10.1016/j.fsigen.2018.09.010
  8. Gabriel R. Fries, Madeline J. Zamzow, Taylor Andrews, Omar Pink, Giselli Scaini, Joao Quevedo. Accelerated aging in bipolar disorder: A comprehensive review of molecular findings and their clinical implications. Neuroscience & Biobehavioral Reviews 2020;112:107
    https://doi.org/10.1016/j.neubiorev.2020.01.035
  9. Helena Correia Dias, Cristina Cordeiro, Francisco Corte Real, Eugénia Cunha, Licínio Manco. Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals . J Forensic Sci 2019
    https://doi.org/10.1111/1556-4029.14185
  10. Jana Naue, Hwan Young Lee. Considerations for the need of recommendations for the research and publication of DNA methylation results. Forensic Science International: Genetics 2018;37:e12
    https://doi.org/10.1016/j.fsigen.2018.08.003
  11. S. Ritz-Timme, P. M. Schneider, N. S. Mahlke, B. E. Koop, S. B. Eickhoff. Altersschätzung auf Basis der DNA-Methylierung. Rechtsmedizin 2018;28:202
    https://doi.org/10.1007/s00194-018-0249-3
  12. Luyao Li, Feng Song, Min Lang, Jiayi Hou, Zheng Wang, Mechthild Prinz, Yiping Hou. Methylation‐Based Age Prediction Using Pyrosequencing Platform from Seminal Stains in Han Chinese Males. J Forensic Sci 2019
    https://doi.org/10.1111/1556-4029.14186
  13. Maria Moreno-Villanueva, Alexander Bürkle. Epigenetic and redox biomarkers: Novel insights from the MARK-AGE study. Mechanisms of Ageing and Development 2019;177:128
    https://doi.org/10.1016/j.mad.2018.06.006
  14. Choi, Joe, Nam. Development of Tissue-Specific Age Predictors Using DNA Methylation Data. Genes 2019;10:888
    https://doi.org/10.3390/genes10110888
  15. Julia Becker, Nina Sophia Mahlke, A. Reckert, S. B. Eickhoff, S. Ritz-Timme. Age estimation based on different molecular clocks in several tissues and a multivariate approach: an explorative study. Int J Legal Med 2019
    https://doi.org/10.1007/s00414-019-02054-9
  16. Athina Vidaki, Manfred Kayser. Recent progress, methods and perspectives in forensic epigenetics. Forensic Science International: Genetics 2018;37:180
    https://doi.org/10.1016/j.fsigen.2018.08.008
  17. Sae Rom Hong, Kyoung-Jin Shin, Sang-Eun Jung, Eun Hee Lee, Hwan Young Lee. Platform-independent models for age prediction using DNA methylation data. Forensic Science International: Genetics 2019;38:39
    https://doi.org/10.1016/j.fsigen.2018.10.005
  18. Kumiko TAKEDA, Eiji KOBAYASHI, Kagetomo NISHINO, Akira IMAI, Hiromichi ADACHI, Yoichiro HOSHINO, Ken IWAO, Satoshi AKAGI, Masahiro KANEDA, Shinya WATANABE. Age-related changes in DNA methylation levels at CpG sites in bull spermatozoa and in vitro fertilization-derived blastocyst-stage embryos revealed by combined bisulfite restriction analysis. J. Reprod. Dev. 2019;65:305
    https://doi.org/10.1262/jrd.2018-146