McGuire AL, Gabriel S, Tishkoff SA, Wonkam A, Chakravarti A, Furlong EEM, et al. The road ahead in genetics and genomics. Nat Rev Genet. 2020;21:581–96. https://doi.org/10.1038/s41576-020-0272-6
Article CAS PubMed PubMed Central Google Scholar
Brogi S, Ramalho TC, Kuca K, Medina-Franco JL, Valko M. Editorial: in silico methods for drug design and discovery. Front Chem. 2020;8:612. https://doi.org/10.3389/fchem.2020.00612
Article PubMed PubMed Central Google Scholar
Brunak S, Bjerre Collin C, Eva Ó Cathaoir K, Golebiewski M, Kirschner M, Kockum I, et al. Towards standardization guidelines for in silico approaches in personalized medicine. J Integr Bioinforma. 2020;17. https://doi.org/10.1515/JIB-2020-0006.
Zhang Y, Qazi S, Raza K. Differential expression analysis in ovarian cancer: a functional genomics and systems biology approach. Saudi J Biol Sci. 2021;28:4069–81. https://doi.org/10.1016/J.SJBS.2021.04.022
Article CAS PubMed PubMed Central Google Scholar
Lu W, Zhang R, Jiang H, Zhang H, Luo C. Computer-aided drug design in epigenetics. Front Chem. 2018;6:57. https://doi.org/10.3389/fchem.2018.00057
Article CAS PubMed PubMed Central Google Scholar
Qazi S, Raza K. In silico approach to understand epigenetics of POTEE in ovarian cancer. J Integr Bioinform. 2021;18:20210028
Article PubMed PubMed Central Google Scholar
Dawson MA. The cancer epigenome: concepts, challenges, and therapeutic opportunities. Science. 2017;355:1147–52. https://doi.org/10.1126/science.aam7304
Article CAS PubMed Google Scholar
Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. 2022;12:31–46. https://doi.org/10.1158/2159-8290.CD-21-1059
Article CAS PubMed Google Scholar
Maston GA, Evans SK, Green MR. Transcriptional regulatory elements in the human genome. Annu Rev Genomics Hum Genet. 2006;7:29–59. https://doi.org/10.1146/annurev.genom.7.080505.115623
Article CAS PubMed Google Scholar
Creyghton MP, Cheng AW, Welstead GG, Kooistra T, Carey BW, Steine EJ, et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci USA. 2010;107:21931–6. https://doi.org/10.1073/pnas.1016071107
Article PubMed PubMed Central Google Scholar
Okabe A, Kaneda A. Transcriptional dysregulation by aberrant enhancer activation and rewiring in cancer. Cancer Sci. 2021;112:2081. https://doi.org/10.1111/CAS.14884
Article CAS PubMed PubMed Central Google Scholar
Corona RI, Seo JH, Lin X, Hazelett DJ, Reddy J, Fonseca MAS, et al. Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer. Nat Commun. 2020;11:1–11. https://doi.org/10.1038/s41467-020-15951-0
Lawrenson K, Fonseca MAS, Liu AY, Freedman ML, Gayther SA, Noushmehr H. A study of high-grade serous ovarian cancer origins implicates the SOX18 transcription factor in tumor development. Cell Rep. 2019;29:3726–35.
Ravindran F, Choudhary B. Ovarian cancer: molecular classification and targeted therapy. Ovarian Cancer Updat Tumour Biol Ther. 2021. https://doi.org/10.5772/intechopen.95967.
Chandra A, Pius C, Nabeel M, Nair M, Vishwanatha JK, Ahmad S, et al. Ovarian cancer: current status and strategies for improving therapeutic outcomes. Cancer Med. 2019;8:7018–31. https://doi.org/10.1002/cam4.2560
Article PubMed PubMed Central Google Scholar
Marchetti C, De Felice F, Romito A, Iacobelli V, Sassu CM, Corrado G, et al. Chemotherapy resistance in epithelial ovarian cancer: mechanisms and emerging treatments. Semin Cancer Biol. 2021;77:144–66. https://doi.org/10.1016/j.semcancer.2021.08.011
Article CAS PubMed Google Scholar
Horikawa N, Abiko K, Matsumura N, Baba T, Hamanishi J, Yamaguchi K, et al. Anti-VEGF therapy resistance in ovarian cancer is caused by GM-CSF-induced myeloid-derived suppressor cell recruitment. Br J Cancer. 2020;122:778–88. https://doi.org/10.1038/s41416-019-0725-x
Article CAS PubMed PubMed Central Google Scholar
Dias MP, Moser SC, Ganesan S, Jonkers J. Understanding and overcoming resistance to PARP inhibitors in cancer therapy. Nat Rev Clin Oncol. 2021;18:773–91. https://doi.org/10.1038/s41571-021-00532-x
Roopra A. MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data. PLoS Comput Biol. 2020;16:e1007800. https://doi.org/10.1371/journal.pcbi.1007800
Article CAS PubMed PubMed Central Google Scholar
Szklarczyk D, Santos A, Von Mering C, Jensen LJ, Bork P, Kuhn M. STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data. Nucleic Acids Res. 2016;44:D380–4. https://doi.org/10.1093/nar/gkv1277
Article CAS PubMed Google Scholar
Coetzee SG, Shen HC, Hazelett DJ, Lawrenson K, Kuchenbaecker K, Tyrer J, et al. Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci. Hum Mol Genet. 2015;24:3595–607. https://doi.org/10.1093/HMG/DDV101
Article CAS PubMed PubMed Central Google Scholar
Lin X, Spindler TJ, de Souza Fonseca MA, Corona RI, Seo JH, Dezem FS, et al. Super-enhancer-associated LncRNA UCA1 interacts directly with AMOT to activate YAP target genes in epithelial ovarian cancer. IScience. 2019;17:242–55. https://doi.org/10.1016/j.isci.2019.06.025
Article CAS PubMed PubMed Central Google Scholar
Jones MR, Peng PC, Coetzee SG, Tyrer J, Reyes ALP, Corona RI, et al. Ovarian cancer risk variants are enriched in histotype-specific enhancers and disrupt transcription factor binding sites. Am J Hum Genet. 2020;107:622–35. https://doi.org/10.1016/j.ajhg.2020.08.021
Article CAS PubMed PubMed Central Google Scholar
Andrews S. FastQC: a quality control tool for high throughput sequence data. 2010. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9. https://doi.org/10.1038/nmeth.1923
Article CAS PubMed PubMed Central Google Scholar
Dobin A, Gingeras TR, Spring C, Flores R, Sampson J, Knight R, et al. Mapping RNA-seq with STAR. Curr Protoc Bioinforma. 2016;51:586–97. https://doi.org/10.1002/0471250953.bi1114s51.Mapping
Kharchenko PV, Tolstorukov MY, Park PJ. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol. 2008;26:1351–9. https://doi.org/10.1038/nbt.1508
Article CAS PubMed PubMed Central Google Scholar
Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, et al. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. 2012:1813–31. https://doi.org/10.1101/gr.136184.111.
Carroll TS, Liang Z, Salama R, Stark R, de Santiago I. Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data. Front Genet. 2014;5:1–11. https://doi.org/10.3389/fgene.2014.00075
Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9:1–9. https://doi.org/10.1186/GB-2008-9-9-R137
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. https://doi.org/10.1186/s13059-014-0550-8
Article CAS PubMed PubMed Central Google Scholar
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, et al. rchestrating high-throughput genomic analysis with ioconductor. Nat Methods. 2015;12:115–21.
Article CAS PubMed PubMed Central Google Scholar
Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database. 2017;2017. https://doi.org/10.1093/database/bax028.
Kolde R. pheatmap: Pretty Heatmaps. R package version 1.0.12 (2019). https://CRAN.R-project.org/package=pheatmap
Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature. 2012;481:389–93. https://doi.org/10.1038/nature10730
Article CAS PubMed PubMed Central Google Scholar
Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer-Verlag New York; 2016.
Hahne F, Ivanek R. Visualizing genomic data using Gviz and bioconductor. Methods Mol Biol. 2016;1418:335–51. https://doi.org/10.1007/978-1-4939-3578-9_16
Gehlenborg N. UpSetR: a more scalable alternative to Venn and Euler diagrams for visualizing intersecting sets. R package version 1.4.0 (2019). https://CRAN.R-project.org/package=UpSetR
Inkscape Project. Inkscape [Internet]. 2020. Available from https://inkscape.org.
Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res. 2019;47:W199–205. https://doi.org/10.1093/nar/gkz401
Article CAS PubMed PubMed Central Google Scholar
Joshi NA, Fass JN. Sickle: a sliding-window, adaptive, quality-based trimming tool for FastQ files (Version 1.33) [Software]. Available at https://github.com/najoshi/sickle
Beauparlant CJ, Lemacon A, Fournier E, Droit A. ENCODExplorer: a compilation of ENCODE metadata. R package version 2.12.1 (2019). https://rdrr.io/bioc/ENCODExplorer/
Grant CE, Bailey TL, Noble WS. FIMO: Scanning for occurrences of a given motif. Bioinformatics. 2011;27:1017–8. https://doi.org/10.1093/bioinformatics/btr064
Article CAS PubMed PubMed Central Google Scholar
Nettling M, Treutler H, Grau J, Keilwagen J, Posch S, Grosse I. DiffLogo: a comparative visualization of sequence motifs. BMC Bioinforma. 2015;16:1–9. https://doi.org/10.1186/S12859-015-0767-X
Bateman A, Martin MJ, Orchard S, Magrane M, Agivetova R, Ahmad S, et al. UniProt: the universal protein knowled
留言 (0)