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8. Contributors

10. A strategy for studying epigenetic diversity in natural populations: proof of concept in poplar and oak.

11. An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer.

12. Molecular Mechanisms of Trophoblast Dysfunction Mediated by Imbalance between STOX1 Isoforms

13. DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis

16. DNA hypomethylation of the host tree impairs interaction with mutualistic ectomycorrhizal fungus

17. A General Framework for Interrogation of mRNA Stability Programs Identifies RNA-Binding Proteins that Govern Cancer Transcriptomes

20. Specific association of extracellular vesicles-derived miRNA-17 and -106a clusters with pathomechanims of obesity-associated low type-2 asthma

21. Placental DNA methylation signatures of prenatal air pollution exposure and potential effects on birth outcomes: an analysis of three prospective cohorts

25. Identification of extracellular vesicle microRNA signatures specifically linked to inflammatory and metabolic mechanisms in obesity‐associated low type‐2 asthma

26. Epigenome-Wide Associations of Placental DNA Methylation and Behavioral and Emotional Difficulties in Children at 3 Years of Age

27. Tunable DNMT1 degradation reveals cooperation of DNMT1 and DNMT3B in regulating DNA methylation dynamics and genome organization

31. Epigenome-Wide Associations of Placental DNA Methylation and Behavioral and Emotional Difficulties in Children at 3 Years of Age

32. Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

33. Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

34. Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

35. Supplementary Table S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

36. Data from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

37. Supplementary Figure 2 from DNA Methylation Status of Key Cell-Cycle Regulators Such as CDKNA2/p16 and CCNA1 Correlates with Treatment Response to Doxorubicin and 5-Fluorouracil in Locally Advanced Breast Tumors

38. Supplementary Table 1-6 from DNA Methylation Status of Key Cell-Cycle Regulators Such as CDKNA2/p16 and CCNA1 Correlates with Treatment Response to Doxorubicin and 5-Fluorouracil in Locally Advanced Breast Tumors

39. Supplementary Figure 1 from DNA Methylation Status of Key Cell-Cycle Regulators Such as CDKNA2/p16 and CCNA1 Correlates with Treatment Response to Doxorubicin and 5-Fluorouracil in Locally Advanced Breast Tumors

40. Supplementary Figure legends from DNA Methylation Status of Key Cell-Cycle Regulators Such as CDKNA2/p16 and CCNA1 Correlates with Treatment Response to Doxorubicin and 5-Fluorouracil in Locally Advanced Breast Tumors

41. Supplementary Table 1 from GSTP1 Promoter Haplotypes Affect DNA Methylation Levels and Promoter Activity in Breast Carcinomas

42. Supplementary Figure 3 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

43. Data from GSTP1 Promoter Haplotypes Affect DNA Methylation Levels and Promoter Activity in Breast Carcinomas

44. Supplementary Table 3 from GSTP1 Promoter Haplotypes Affect DNA Methylation Levels and Promoter Activity in Breast Carcinomas

45. Supplementary Figure 1 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

46. Supplementary Figure 1 from GSTP1 Promoter Haplotypes Affect DNA Methylation Levels and Promoter Activity in Breast Carcinomas

47. Supplementary Table 2 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

48. Supplementary Table 1 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

49. Supplementary Figure 2 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

50. Supplementary Figure 4 from Quantitative Analysis of DNA Methylation Profiles in Lung Cancer Identifies Aberrant DNA Methylation of Specific Genes and Its Association with Gender and Cancer Risk Factors

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