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This is a "connection" page, showing publications co-authored by OLGA GORLOVA and IVAN GORLOV.
OLGA GORLOVA
Connection Strength
7.053
IVAN GORLOV
  1. Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes. Oncotarget. 2022; 13:756-767.
    View in: PubMed
    Score: 0.876
  2. SNP characteristics and validation success in genome wide association studies. Hum Genet. 2022 Feb; 141(2):229-238.
    View in: PubMed
    Score: 0.853
  3. Downstream targets of GWAS-detected genes for breast, lung, and prostate and colon cancer converge to G1/S transition pathway. Hum Mol Genet. 2017 04 15; 26(8):1465-1471.
    View in: PubMed
    Score: 0.615
  4. Genes with a large intronic burden show greater evolutionary conservation on the protein level. BMC Evol Biol. 2014 Mar 16; 14(1):50.
    View in: PubMed
    Score: 0.497
  5. Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases. J Bioinform Comput Biol. 2012 Apr; 10(2):1241008.
    View in: PubMed
    Score: 0.434
  6. Beyond comparing means: the usefulness of analyzing interindividual variation in gene expression for identifying genes associated with cancer development. J Bioinform Comput Biol. 2012 Apr; 10(2):1241013.
    View in: PubMed
    Score: 0.434
  7. Methylation of nonessential genes in cutaneous melanoma - Rule Out hypothesis. Melanoma Res. 2023 06 01; 33(3):163-172.
    View in: PubMed
    Score: 0.231
  8. Tumor somatic mutations also existing as germline polymorphisms may help to identify functional SNPs from genome-wide association studies. Carcinogenesis. 2020 10 15; 41(10):1353-1362.
    View in: PubMed
    Score: 0.196
  9. Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma. Hum Mutat. 2020 10; 41(10):1751-1760.
    View in: PubMed
    Score: 0.193
  10. SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies. BMC Genet. 2019 11 12; 20(1):85.
    View in: PubMed
    Score: 0.184
  11. Untouchable genes in the human genome: Identifying ideal targets for cancer treatment. Cancer Genet. 2019 02; 231-232:67-79.
    View in: PubMed
    Score: 0.174
  12. Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples. BMC Bioinformatics. 2018 Nov 19; 19(1):430.
    View in: PubMed
    Score: 0.172
  13. Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations. PLoS One. 2018; 13(1):e0189498.
    View in: PubMed
    Score: 0.162
  14. Prediction of the gene expression in normal lung tissue by the gene expression in blood. BMC Med Genomics. 2015 Nov 17; 8:77.
    View in: PubMed
    Score: 0.139
  15. Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases. PLoS Genet. 2015 Jul; 11(7):e1005371.
    View in: PubMed
    Score: 0.136
  16. SNP characteristics predict replication success in association studies. Hum Genet. 2014 Dec; 133(12):1477-86.
    View in: PubMed
    Score: 0.129
  17. How to get the most from microarray data: advice from reverse genomics. BMC Genomics. 2014 Mar 21; 15:223.
    View in: PubMed
    Score: 0.124
  18. Building a statistical model for predicting cancer genes. PLoS One. 2012; 7(11):e49175.
    View in: PubMed
    Score: 0.113
  19. Initial medical attention on patients with early-stage non-small cell lung cancer. PLoS One. 2012; 7(3):e32644.
    View in: PubMed
    Score: 0.108
  20. Association of smoking with tumor size at diagnosis in non-small cell lung cancer. Lung Cancer. 2011 Dec; 74(3):378-83.
    View in: PubMed
    Score: 0.102
  21. Prioritizing genes associated with prostate cancer development. BMC Cancer. 2010 Nov 02; 10:599.
    View in: PubMed
    Score: 0.098
  22. GWAS meets microarray: are the results of genome-wide association studies and gene-expression profiling consistent? Prostate cancer as an example. PLoS One. 2009 Aug 04; 4(8):e6511.
    View in: PubMed
    Score: 0.090
  23. Candidate pathways and genes for prostate cancer: a meta-analysis of gene expression data. BMC Med Genomics. 2009 Aug 04; 2:48.
    View in: PubMed
    Score: 0.090
  24. Relative effects of mutability and selection on single nucleotide polymorphisms in transcribed regions of the human genome. BMC Genomics. 2008 Jun 17; 9:292.
    View in: PubMed
    Score: 0.083
  25. Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms. Am J Hum Genet. 2008 Jan; 82(1):100-12.
    View in: PubMed
    Score: 0.081
  26. Predicting the oncogenicity of missense mutations reported in the International Agency for Cancer Research (IARC) mutation database on p53. Hum Mutat. 2005 Nov; 26(5):446-54.
    View in: PubMed
    Score: 0.070
  27. Missense mutations in cancer suppressor gene TP53 are colocalized with exonic splicing enhancers (ESEs). Mutat Res. 2004 Oct 04; 554(1-2):175-83.
    View in: PubMed
    Score: 0.065
  28. Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls. Cancer. 2024 03 15; 130(6):913-926.
    View in: PubMed
    Score: 0.061
  29. Missense mutations in hMLH1 and hMSH2 are associated with exonic splicing enhancers. Am J Hum Genet. 2003 Nov; 73(5):1157-61.
    View in: PubMed
    Score: 0.060
  30. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population. Nat Commun. 2023 05 26; 14(1):3043.
    View in: PubMed
    Score: 0.059
  31. Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis. J Thorac Oncol. 2023 08; 18(8):1003-1016.
    View in: PubMed
    Score: 0.058
  32. Immune Infiltration in Tumor and Adjacent Non-Neoplastic Regions Codetermines Patient Clinical Outcomes in Early-Stage Lung Cancer. J Thorac Oncol. 2023 09; 18(9):1184-1198.
    View in: PubMed
    Score: 0.058
  33. Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer. Nat Genet. 2022 08; 54(8):1167-1177.
    View in: PubMed
    Score: 0.055
  34. Protein-altering germline mutations implicate novel genes related to lung cancer development. Nat Commun. 2020 05 11; 11(1):2220.
    View in: PubMed
    Score: 0.048
  35. Association Analysis of Driver Gene-Related Genetic Variants Identified Novel Lung Cancer Susceptibility Loci with 20,871 Lung Cancer Cases and 15,971 Controls. Cancer Epidemiol Biomarkers Prev. 2020 07; 29(7):1423-1429.
    View in: PubMed
    Score: 0.047
  36. Lung Cancer Risk in Never-Smokers of European Descent is Associated With Genetic Variation in the 5p15.33 TERT-CLPTM1Ll Region. J Thorac Oncol. 2019 08; 14(8):1360-1369.
    View in: PubMed
    Score: 0.044
  37. Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development. Oncotarget. 2019 Mar 05; 10(19):1760-1774.
    View in: PubMed
    Score: 0.044
  38. Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk. Nat Commun. 2018 08 13; 9(1):3221.
    View in: PubMed
    Score: 0.042
  39. Variants in inflammation genes are implicated in risk of lung cancer in never smokers exposed to second-hand smoke. Cancer Discov. 2011 Oct; 1(5):420-9.
    View in: PubMed
    Score: 0.026
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.