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  1. 2017-03-14 Hong, S. et al. Dissociation of muscle insulin sensitivity from exercise endurance in mice by HDAC3 depletion. Nat Med 23, 223-234, doi:10.1038/nm.4245 (2017), PMID: 27991918

  2. 2018-09-19 Takagi, T. et al. Differences in gut microbiota associated with age, sex, and stool consistency in healthy Japanese subjects. J Gastroenterol. Jun 20, doi: 10.1007/s00535-018-1488-5 (2018) PMID: 29926167 

  3. 2018-10-02 Yang, Q. et al. MicroRNA and piRNA profiles in normal human testis detected by next generation sequencing. PLoS One, Jun 24;8(6):e66809 doi: 10.1371/journal.pone.0066809 (2013), PMID: 27991918 

  4. 2018-10-10 Valencia, PM. et al. The human microbiome: opportunity or hype? Nat Rev Drug Discov, Dec;16(12):823-824. doi: 10.1038/nrd.2017.154 (2017) PMID: 28912600

  5. 2018-10-10 Halkjær, SI. et al. Faecal microbiota transplantation alters gut microbiota in patients with irritable bowel syndrome: results from a randomised, double-blind placebo-controlled study. Gut. Jul 6. pii: gutjnl-2018-316434.
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  6. 2018-10-17 Wang, X. et al. Widespread genetic epistasis among cancer genes. Nat Commun. Nov 19;5:4828. doi: 10.1038/ncomms5828 (2014) PMID: 25407795

  7. 2018-10-29 Steven A. Roberts and Dmitry A. Gordenin. Hypermutation in human cancer genomes: footprints and mechanisms. Nat Rev Cancer. Dec; 14(12): 786–800. doi:  [10.1038/nrc3816] (2014) PMID: 25568919

  8. 2018-10-29 Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. Oct;562(7726):203-209. doi: 10.1038/s41586-018-0579-z. (2018) PMID: 30305743

  9. 2018-11-12 JY Ryu. et al. Deep learning improves prediction of drug–drug and drug–food interactions. PNAS May 1, 2018 115 (18) E4304-E4311; doi: https://doi.org/10.1073/pnas.1803294115 

  10. 2018-11-19 JP Tosar. et al. Non-coding RNA fragments account for the majority of annotated piRNAs expressed in somatic non-gonadal tissues. Communications Biology volume 1, Article number: 2 (2018); doi:10.1038/s42003-017-0001-7

  11. 2018-11-26 SK Mazmanian. et al. A microbial symbiosis factor prevents intestinal inflammatory disease. Nature Vol 453, 620–625, 29 May (2008) doi:10.1038/nature07008

  12. 2018-12-11 SP Rosshart. et al. Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance. Cell. Nov 16;171(5):1015-1028.e13. (2017) doi: 10.1016/j.cell.2017.09.016 PMID: 29056339

  13. 2019-01-22 L Sundaram. et al. Predicting the clinical impact of human mutation with deep neural networks. Nature Genetics volume 50, pages1161–1170 (2018) doi:10.1038/s41588-018-0167-z

  14. 2019-02-11 TB Rounge. et al. Circulating small non-coding RNAs associated with age, sex, smoking, body mass and physical activity. Scientific Reports volume 8, Article number: 17650 (2018) doi:10.1038/s41598-018-35974-4

  15. 2019-03-26 S Turajlic. et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol. Volume 18, Issue 8, August, Pages 1009-1021 (2017) doi: 10.1016/S1470-2045(17)30516-8  PMID: 28694034

  16. 2019-04-10 W Weng. et al. Novel evidence for a PIWI-interacting RNA (piRNA) as an oncogenic mediator of disease progression, and a potential prognostic biomarker in colorectal cancer. Mol Cancer. Jan 30;17(1):16. (2018) doi:10.1186/s12943-018-0767-3  PMID: 29382334

  17. 2019-04-23 AM Thomas. et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nature Medicine, volume 25, 667–678 April (2019) doi:10.1038/s41591-019-0405-7.

  18. 2019-05-14  J Zou. et al. A primer on deep learning in genomics. Nat Genet. Jan;51(1):12-18. (2019) doi:10.1038/s41588-018-0295-5. PMID: 30478442

  19. 2019-05-21 R Xing. et al. Whole-genome sequencing reveals novel tandem-duplication hotspots and a prognostic mutational signature in gastric cancer. Nature Communications, volume 10, Article number: 2037 May (2019) doi:10.1038/s41467-019-09644-6.

  20. 2019-06-04 J Flannick. et al. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. Nature. Jun;570(7759):71-76. (2019) doi: 10.1038/s41586-019-1231-2 PMID: 31118516

  21. 2019-06-11 TH Wang. et al. More Is Less: Increased Processing of Unwanted Memories Facilitates Forgetting. Journal of Neuroscience 1 May 2019, 39 (18) 3551-3560; doi: 10.1523/JNEUROSCI.2033-18.2019

  22. 2019-07-02 A Eetemadi. et al. Genetic Neural Networks: An artificial neural network architecture for capturing gene expression relationships. Bioinformatics Nov 19 (2018). doi: 10.1093/bioinformatics/bty945 PMID: 30452523

  23. 2019-08-06 M Riester. et al. PureCN: copy number calling and SNV classification using targeted short read sequencing. Source Code for Biology and Medicine, volume 11, Article number: 13 (2016) doi: 10.1186/s13029-016-0060-z

  24. 2019-08-13 DM Ozata. et al. PIWI-interacting RNAs: small RNAs with big functions. Nature Reviews Genetics, volume 20, pages89–108 (2019) doi: 10.1038/s41576-018-0073-3

  25. 2019-09-10 S An. et al. TSEE: an elastic embedding method to visualize the dynamic gene expression patterns of time series single-cell RNA sequencing data. BMC Genomics, 20(Suppl 2):224 (2019) doi: 10.1186/s12864-019-5477-8

  26. 2019-09-17 JX Sun. et al. A computational approach to distinguish somatic vs. germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal. PLoS Comput Biol. Feb 7;14(2):e1005965 (2018) doi: 10.1371/journal.pcbi.1005965 PMID: 29415044

  27. 2019-10-01 DM Ozata. et al. PIWI-interacting RNAs: small RNAs with big functions. Nature Reviews Genetics, volume 20, pages89–108 (2019) doi: 10.1038/s41576-018-0073-3

  28. 2019-10-08 JG Reiter. et al. An analysis of genetic heterogeneity in untreated cancers. Nat Rev Cancer. Aug 27(2019). doi: 10.1038/s41568-019-0185-x PMID: 31455892

  29. 2019-10-15 T Lee. et al. Convolutional neural network model to predict causal risk factors that share complex regulatory features. Nucleic Acids Research. Oct 10 (2019). doi: 10.1093/nar/gkz868

  30. 2019-10-22  Abid K. et al. Image analysis: openCV-Python. URL : https://opencv-python-tutroals.readthedocs.io

  31. 2019-10-29 H Jung. et al. DNA methylation loss promotes immune evasion of tumours with high mutation and copy number load. Nat Commun. Sep 19;10(1):4278. (2019) doi: 10.1038/s41467-019-12159-9  PMID: 31537801

  32. 2019-11-05 Y Wang. et al. Comprehensive Molecular Characterization of the Hippo Signaling Pathway in Cancer. Cell Rep. 2018 Oct 30;25(5):1304-1317.e5. doi: 10.1016/j.celrep.2018.10.001 PMID: 30380420​

  33. 2019-11-12 X Peng. et al. Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers. Cell reports vol. 23,1 (2018): 255-269.e4. doi:10.1016/j.celrep.2018.03.077 PMID: 29617665​

  34. 2019-11-19 K Kim. et al. Chromatin structure–based prediction of recurrent noncoding mutations in cancer. Nature Genetics, 48(11), 1321–1326 (2016). doi:10.1038/ng.3682​

  35. 2019-12-17 Y Yuan. et al. Comprehensive Molecular Characterization of Mitochondrial Genomes in Human Cancers. BioRxiv (2017): 161356. doi:10.1101/161356

  36. 2020-01-07 H Chen, et al. A pan-cancer analysis of enhancer expression in nearly 9000 patient samples. Cell 173.2 (2018): 386-399. doi:10.1016/j.cell.2018.03.027

  37. 2020-01-13 B Seo, et al. Roseburia Spp. Abundance Associates with Alcohol Consumption in Humans and Its Administration Ameliorates Alcoholic Fatty Liver in Mice. Cell Host & Microbe (2019), doi:10.1016/j.chom.2019.11.001

  38. 2020-01-20 H Jung, et al. Immune signatures correlate with L1 retrotransposition in gastrointestinal cancers." Genome research 28.8 (2018): 1136-1146, doi:10.1101/gr.231837.117

  39. 2020-01-28 Y Xin, et al. RNA sequencing of single human islet cells reveals type 2 diabetes genes. Cell metabolism 24.4 (2016): 608-615, doi:10.1016/j.cmet.2016.08.018

  40. 2020-02-03 GF Gao, et al. Before and after: Comparison of legacy and harmonized TCGA genomic data commons’ data. Cell systems 9.1 (2019): 24-34, doi:10.1016/j.cels.2019.06.006

  41. 2020-02-10 JS Park, et al. Brain somatic mutations observed in Alzheimer’s disease associated with aging and dysregulation of tau phosphorylation. Nat Commun 10, 3090 (2019), doi:10.1038/s41467-019-11000-7 

  42. 2020-04-22 Y Qi, et al. Kinome Profiling Reveals Abnormal Activity of Kinases in Skeletal Muscle From Adults With Obesity and Insulin Resistance. J Clin Endocrinol Metab 105: 1– 16 (2019), doi:10.1210/clinem/dgz115 

  43. 2020-05-06 Matthew G. Vander Heiden, and Ralph J. DeBerardinis. Understanding the intersections between metabolism and cancer biology. Cell 168.4 (2017): 657-669., doi:10.1016/j.cell.2016.12.039

  44. 2020-05-20 Fiona M. Behan, et al. Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens. Nature 568.7753 (2019): 511. doi:10.1038/s41586-019-1103-9

  45. 2020-05-27 Cheng, Liang, et al. gutMDisorder: a comprehensive database for dysbiosis of the gut microbiota in disorders and interventions. Nucleic acids research 48.D1 (2020): D554-D560. doi:10.1093/nar/gkz843

  46. 2020-06-03 Fiona M. Behan, et al. Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens. Nature 568.7753 (2019): 511. doi:10.1038/s41586-019-1103-9

  47. 2020-06-10 Bryois, Julien, et al. Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease. Nature Genetics 52.5 (2020): 482-493. doi:10.1038/s41588-020-0610-9.

  48. 2020-06-17 Skene, Nathan G., et al. Genetic identification of brain cell types underlying schizophrenia. Nature genetics 50.6 (2018): 825-833.  doi:10.1038/s41588-018-0129-5

  49. 2020-07-27 Oh, Tae Gyu, et al. A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis. Cell Metabolism (2020).  doi:10.1016/j.cmet.2020.06.005

  50. 2020-08-19 Kwon, O., Lee, H., Kong, H. et al. Connectivity map-based drug repositioning of bortezomib to reverse the metastatic effect of GALNT14 in lung cancer. Oncogene 39, 4567–4580 (2020). doi:10.1038/s41388-020-1316-2

  51. 2020-09-03 Tsherniak A, Vazquez F, Montgomery PG, et al. Defining a Cancer Dependency Map. Cell. 2017;170(3):564-576.e16. doi:10.1016/j.cell.2017.06.010

  52. 2020-09-23 Lawrence Donehower, et al. (2019). Integrated Analysis of TP53 Gene and Pathway Alterations in The Cancer Genome Atlas. Cell Reports. 28. 3010. doi:10.1016/j.celrep.2019.08.061

  53. 2020-10-14 Balaguru Ravikumar, et al. (2019). Chemogenomic Analysis of the Druggable Kinome and Its Application to Repositioning and Lead Identification Studies. SSRN Electronic Journal. doi:10.2139/ssrn.3356840 

  54. 2020-10-28 Morteza H. Ghaffari, et al. (2019). Machine learning approach reveals a metabolic signature of over-conditioned cows. Diabetes 2020 Oct; db200586. doi:10.2337/db20-0586

  55. 2020-11-11 Chen, H., Li, J., Wang, Y. et al. Comprehensive assessment of computational algorithms in predicting cancer driver mutations. Genome Biol 21, 43 (2020). doi:10.1186/s13059-020-01954-z

  56. 2020-11-18 2020-Fernández-Torras, A., Duran-Frigola, M. & Aloy, P. Encircling the regions of the pharmacogenomic landscape that determine drug response. Genome Med 11, 17 (2019). doi:10.1186/s13073-019-0626-x  

  57. 2020-12-02 Lee, G., You, H.J., Bajaj, J.S. et al. Distinct signatures of gut microbiome and metabolites associated with significant fibrosis in non-obese NAFLD. Nat Commun 11, 4982 (2020). doi:10.1038/s41467-020-18754-5

  58. 2020-12-09 Schaub, Franz X.Caesar-Johnson, Samantha J. et al. Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas. Cell Syst. 2018 Mar 28;6(3):282-300.e2. doi: 10.1016/j.cels.2018.03.003.

  59. 2020-12-16 Kong, J., Lee, H., Kim, D. et al. Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients. Nat Commun 11, 5485 (2020). doi:10.1038/s41467-020-19313-8

  60. 2021-01-06 Mina, M., Iyer, A., Tavernari, D. et al. Discovering functional evolutionary dependencies in human cancers. Nat Genet 52, 1198–1207 (2020). doi:10.1038/s41588-020-0703-5

  61. 2021-02-03 Newell, F., Wilmott, J.S., Johansson, P.A. et al. Whole-genome sequencing of acral melanoma reveals genomic complexity and diversity. Nat Commun 11, 5259 (2020). doi:10.1038/s41467-020-18988-3

  62. 2021-02-16 Govaere O, Cockell S, Tiniakos D, et al. Transcriptomic profiling across the nonalcoholic fatty liver disease spectrum reveals gene signatures for steatohepatitis and fibrosis. Sci Transl Med. 2020;12(572):eaba4448. doi:10.1126/scitranslmed.aba444

  63. 2021-02-24 Arechederra, M., Daian, F., Yim, A. et al. Hypermethylation of gene body CpG islands predicts high dosage of functional oncogenes in liver cancer. Nat Commun 9, 3164 (2018). doi:10.1038/s41467-018-05550-5

  64. 2021-03-10 Okazaki, K., Anzawa, H., Liu, Z. et al. Enhancer remodeling promotes tumor-initiating activity in NRF2-activated non-small cell lung cancers. Nat Commun 11, 5911 (2020). doi:org/10.1038/s41467-020-19593-0

  65. 2021-03-24 Zhang, C., Zhang, L., Xu, T. et al. Mapping the spreading routes of lymphatic metastases in human colorectal cancer. Nat Commun 11, 1993 (2020). doi:10.1038/s41467-020-15886-6

  66. 2021-04-14 Ballhausen, A., Przybilla, M.J., Jendrusch, M. et al. The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution. Nat Commun 11, 4740 (2020). doi:10.1038/s41467-020-18514-5

  67. 2021-04-28 Chong, J., Liu, P., Zhou, G. et al. Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc 15, 799–821 (2020). doi:10.1038/s41596-019-0264-1

  68. 2021-05-04 Lee YH. Overview of Mendelian Randomization Analysis. J Rheum Dis 2020;27:241-246. doi:10.4078/jrd.2020.27.4.241

  69. 2021-05-04 Yang, S.J., Kwak, SY., Jo, G. et al. Serum metabolite profile associated with incident type 2 diabetes in Koreans: findings from the Korean Genome and Epidemiology Study. Sci Rep 8, 8207 (2018). doi:10.1038/s41598-018-26320-9

  70. 2021-05-04 Moon, JS, Goeminne, LJE, Kim, S.-H., et al. Growth differentiation factor 15 protects against the aging-mediated systemic inflammatory response in humans and mice. Aging Cell. 2020; 19:e13195. doi:10.1111/acel.13195

  71. 2021-05-11 Wang, Longcai et al. Circulating Vitamin D Levels and Alzheimer’s Disease: A Mendelian Randomization Study in the IGAP and UK Biobank’ 1 Jan. 2020 : 609 – 618. doi: 10.3233/JAD-190713

  72. 2021-05-18 Walker VM, et al. Using the MR-Base platform to investigate risk factors and drug targets for thousands of phenotypes. Wellcome Open Res. 2019 Nov 7;4:113. doi: 10.12688/wellcomeopenres.15334.2. PMID: 31448343; PMCID: PMC6694718.

  73. 2021-06-23 Pierce BL, Ahsan H, Vanderweele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol. 2011;40(3):740-752. doi:10.1093/ije/dyq151

  74. 2021-08-04 Fu, Y., Jung, A.W., Torne, R.V. et al. Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis. Nat Cancer 1, 800–810 (2020). doi:10.1038/s43018-020-0085-8

  75. 2021-08-11 Arvanitis M, Qi G, Bhatt DL, Post WS, Chatterjee N, Battle A, McEvoy JW. Linear and Nonlinear Mendelian Randomization Analyses of the Association Between Diastolic Blood Pressure and Cardiovascular Events: The J-Curve Revisited. Circulation. 2021 Mar 2;143(9):895-906. doi: 10.1161/CIRCULATIONAHA.120.049819. Epub 2020 Nov 30. PMID: 33249881; PMCID: PMC7920937.

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  77. 2021-09-01 Faust, K., Bala, S., van Ommeren, R. et al. Intelligent feature engineering and ontological mapping of brain tumour histomorphologies by deep learning. Nat Mach Intell 1, 316–321 (2019). doi:10.1038/s42256-019-0068-6

  78. 2021-09-15  Sanchez-Vega F, Mina M, Armenia J, et al. Oncogenic Signaling Pathways in The Cancer Genome Atlas. Cell. 2018;173(2):321-337.e10. doi:10.1016/j.cell.2018.03.035

  79. 2021-09-29 Ye, Y., Hu, Q., Chen, H. et al. Characterization of hypoxia-associated molecular features to aid hypoxia-targeted therapy. Nat Metab 1, 431–444 (2019). doi:10.1038/s42255-019-0045-8

  80. 2021-10-06 Lynn MA, Eden G, Ryan FJ, et al. The composition of the gut microbiota following early-life antibiotic exposure affects host health and longevity in later life. Cell Rep. 2021;36(8):109564. doi:10.1016/j.celrep.2021.109564

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