Statistical power and significance testing in large-scale genetic studies

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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PLINK: a tool set for whole-genome association and population-based linkage analyses.

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A method and server for predicting damaging missense mutations.

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Statistical Methods for Research Workers

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Principal components analysis corrects for stratification in genome-wide association studies

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Bootstrap Methods and their Application

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A haplotype map of the human genome

The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858

Bootstrap Methods and Their Application

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Genome-wide association studies for common diseases and complex traits

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Rectangular Confidence Regions for the Means of Multivariate Normal Distributions

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The Human Leukocyte Antigen Locus and Rheumatic Heart Disease Susceptibility in South Asians and Europeans

Auckland, K., Mittal, B., Cairns, B. J., Garg, N. K., Kumar, S., Mentzer, A. J., Kado, J. H., Perman, M. L., Steer, A. C., Hill, A. V. S., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-65855-8 · Cited by 24

Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature

Jonson, C., Levine, K. S., Lake, J., Hertslet, L., Jones, L., Patel, D., Kim, J., Bandrés‐Ciga, S., Terry, N. L., Mata, I. F., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13873 · Cited by 24

A novel approach to genome-wide association analysis identifies genetic associations with primary biliary cholangitis and primary sclerosing cholangitis in Polish patients

Paziewska, A., Habior, A., Rogowska, A., Zych, W., Goryca, K., Karczmarski, J., Dąbrowska, M., Ambrożkiewicz, F., Walewska‐Zielecka, B., Krawczyk, M., et al. (2017) · BMC Medical Genomics · doi:10.1186/s12920-016-0239-9 · Cited by 24

Dynamic incorporation of prior knowledge from multiple domains in biomarker discovery

Guan, X., Runger, G. C., & Liu, L. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-3344-x · Cited by 24

Gene‐based mapping of trehalose biosynthetic pathway genes reveals association with source‐ and sink‐related yield traits in a spring wheat panel

Lyra, D. H., Griffiths, C. A., Watson, A., Joynson, R., Molero, G., Igna, A., Hassani‐Pak, K., Reynolds, M. P., Hall, A. J. W., & Paul, M. J. (2021) · Food and Energy Security · doi:10.1002/fes3.292 · Cited by 24

Genome-Wide Association Study of Post-Traumatic Stress Disorder in Two High-Risk Populations

Melroy-Greif, W. E., Wilhelmsen, K. C., Yehuda, R., & Ehlers, C. L. (2017) · Twin Research and Human Genetics · doi:10.1017/thg.2017.12 · Cited by 23

An Estimation of Online Video User Engagement From Features of Time- and Value-Continuous, Dimensional Emotions

Stappen, L., Baird, A., Lienhart, M., Bätz, A., & Schuller, B. W. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.773154 · Cited by 22

Artificial Neural Network Study on the Pyrolysis of Polypropylene with a Sensitivity Analysis

Dubdub, I. (2023) · Polymers · doi:10.3390/polym15030494 · Cited by 22

Rigor and reproducibility in genetic research on eating disorders

Hübel, C., Leppä, V., Breen, G. D., & Bulik, C. M. (2018) · International Journal of Eating Disorders · doi:10.1002/eat.22896 · Cited by 24

A Genome-Wide Association Study of Bisphosphonate-Associated Atypical Femoral Fracture

Kharazmi, M., Michaëlsson, K., Schilcher, J., Eriksson, N., Melhus, H., Wadelius, M., & Hallberg, P. (2019) · Calcified Tissue International · doi:10.1007/s00223-019-00546-9 · Cited by 22

In silico profiling of systemic effects of drugs to predict unexpected interactions

Yoo, S., Noh, K., Shin, M., Park, J., Lee, K.-H., Nam, H., & Lee, D. (2018) · Scientific Reports · doi:10.1038/s41598-018-19614-5 · Cited by 22

Whole-exome sequencing and gene-based rare variant association tests suggest that PLA2G4E might be a risk gene for panic disorder

Morimoto, Y., Shimada‐Sugimoto, M., Otowa, T., Yoshida, S., Kinoshita, A., Mishima, H., Yamaguchi, N., Mori, T., Imamura, A., Ozawa, H., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-017-0088-0 · Cited by 21

Fine-tuned adaptation of embryo–endometrium pairs at implantation revealed by transcriptome analyses in Bos taurus

Biase, F. H., Hue, I., Moorey, S. E., Jaffrézic, F., Laloë, D., Lewin, H. A., & Sandra, O. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000046 · Cited by 21

Genetic determinants of apixaban plasma levels and their relationship to bleeding and thromboembolic events

Attelind, S., Hallberg, P., Wadelius, M., Hamberg, A., Siegbahn, A. G., Granger, C. B., Lópes, R. D., Alexander, J. H., Wallentin, L. C., & Eriksson, N. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.982955 · Cited by 20

Guidelines to Statistical Analysis of Microbial Composition Data Inferred from Metagenomic Sequencing

Odintsova, V. Y., Tyakht, A., & Alexeev, D. G. (2017) · Current Issues in Molecular Biology · doi:10.21775/cimb.024.017 · Cited by 20

The role of human host genetics in tuberculosis resistance

Kinnear, C. J., Hoal, E. G., Schurz, H., van Helden, P. D., & Möller, M. (2017) · Expert Review of Respiratory Medicine · doi:10.1080/17476348.2017.1354700 · Cited by 20

Genome-wide association study (GWAS) of human host factors influencing viral severity of herpes simplex virus type 2 (HSV-2)

Kleinstein, S. E., Shea, P. R., Allen, A. S., Koelle, D. M., Wald, A., & Goldstein, D. B. (2018) · Genes and Immunity · doi:10.1038/s41435-018-0013-4 · Cited by 20

Molecular epidemiology; New but impressive

Honardoost, M., Rajabpour, A., & Vakil, L. (2018) · Medical Journal of the Islamic Republic of Iran · doi:10.14196/mjiri.32.53 · Cited by 20

Reduced meiotic recombination in rhesus macaques and the origin of the human recombination landscape

Xue, C., Rustagi, N., Liu, X., Raveendran, M., Harris, R. A., Venkata, M. G., Rogers, J., & Yu, F. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236285 · Cited by 19

15q12 Variants, Sputum Gene Promoter Hypermethylation, and Lung Cancer Risk: A GWAS in Smokers

Leng, S., Liu, Y., Weissfeld, J. L., Thomas, C. L., Han, Y., Picchi, M. A., Edlund, C. K., Willink, R. P., Davis, A. L. G., Kieu, C., et al. (2015) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djv035 · Cited by 19

Low-, high-coverage, and two-stage DNA sequencing in the design of the genetic association study

Xu, C., Wu, K., Zhang, J., Shen, H., & Deng, H. (2016) · Genetic Epidemiology · doi:10.1002/gepi.22015 · Cited by 21

The Clinical Application of RNA Sequencing in Genetic Diagnosis of Mendelian Disorders

Stenton, S. L., & Prokisch, H. (2020) · Clinics in Laboratory Medicine · doi:10.1016/j.cll.2020.02.004 · Cited by 19

Empirical facts from search for replicable associations between cortical thickness and psychometric variables in healthy adults

Masouleh, S. K., Eickhoff, S. B., Balajoo, S. M., Nicolaisen‐Sobesky, E., Thirion, B., & Genon, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-17556-7 · Cited by 19

Ophthalmic statistics note 7: multiple hypothesis testing—to adjust or not to adjust

Cipriani, V., Quartilho, A., Bunce, C., Freemantle, N., & Doré, C. J. (2015) · British Journal of Ophthalmology · doi:10.1136/bjophthalmol-2015-306784 · Cited by 19

Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI ScansPreprint

Jahanshad, N., Ganjgahi, H., Bralten, J., den Braber, A., Faskowitz, J., Knodt, A. R., Lemaître, H., Nir, T. M., Patel, B., Richie, S., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/107987 · Cited by 21

Genome-wide Association Study for AKI

Bhatraju, P. K., Stanaway, I. B., Palmer, M. R., Menon, R., Schaub, J. A., Menez, S. P., Srivastava, A., Wilson, F. P., Kiryluk, K., Palevsky, P. M., et al. (2023) · Kidney360 · doi:10.34067/kid.0000000000000175 · Cited by 18

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Li, Z., Guo, B., Yang, J., Herczeg, G., Gonda, A., Balázs, G., Shikano, T., Calboli, F. C. F., & Merilä, J. (2017) · Molecular Ecology · doi:10.1111/mec.14005 · Cited by 18

Analysis of association of gene variants with obesity traits in New Zealand European children at 6 years of age

Krishnan, M., Thompson, J., Mitchell, E. A., Murphy, R., McCowan, L. M. E., Shelling, A. N., & g on behalf of the Children of SCOPE study group (2017) · Molecular BioSystems · doi:10.1039/c7mb00104e · Cited by 19

Logical and Methodological Issues Affecting Genetic Studies of Humans Reported in Top Neuroscience Journals

Grabitz, C. R., Button, K. S., Munafo, M. R., Newbury, D. F., Pernet, C. R., Thompson, P. A., & Bishop, D. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01192 · Cited by 18

A genome-wide association study of corneal astigmatism: The CREAM Consortium.

Shah, R. L., Li, Q., Zhao, W., Tedja, M. S., Tideman, J. W. L., Khawaja, A. P., Fan, Q., Yazar, S., Williams, K. M., Verhoeven, V. J. M., et al. (2018) · PubMed Central · doi:10.7892/boris.114871 · Cited by 18

Understanding avian assemblage change within anthropogenic environments using citizen science data

Joyce, M., Barnes, M. D., Possingham, H. P., & van Rensburg, B. J. (2018) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2018.07.006 · Cited by 18

Genome-Wide Association Study Confirms Previous Findings of Major Loci Affecting Resistance to Piscine myocarditis virus in Atlantic Salmon (Salmo salar L.)

Hillestad, B., Kristjánsson, Ó. H., Makvandi‐Nejad, S., & Moghadam, H. K. (2020) · Genes · doi:10.3390/genes11060608 · Cited by 18

Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis

Quick, C., Wen, X., Abecasis, G. R., Boehnke, M., & Kang, H. M. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009060 · Cited by 18

SNP characteristics and validation success in genome wide association studies

Gorlova, O. Y., Xiao, X., Tsavachidis, S., Amos, C. I., & Gorlov, I. P. (2022) · Human Genetics · doi:10.1007/s00439-021-02407-8 · Cited by 18

Genetic variants associated with syncope implicate neural and autonomic processes

Aegisdottir, H. M., Þórólfsdóttir, R. B., Sveinbjörnsson, G., Stefánsson, Ó. A., Gunnarsson, B., Tragante, V., Þorleifsson, G., Stefánsdóttir, L., Thorgeirsson, T. E., Ferkingstad, E., et al. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad016 · Cited by 18

Population-based analysis of ocular Chlamydia trachomatis in trachoma-endemic West African communities identifies genomic markers of disease severity

Last, A. R., Pickering, H. C., Roberts, C. H., Coll, F., Phelan, J. E., Burr, S. E., Cassama, E. T. D. S., Nabicassa, M., Seth-Smith, H. M. B., Hadfield, J., et al. (2018) · Genome Medicine · doi:10.1186/s13073-018-0521-x · Cited by 18

Implication of Genes for the N-Methyl-d-Aspartate (NMDA) Receptor in Substance Addictions

Chen, J., Ma, Y., Fan, R., Yang, Z., & Li, M. D. (2018) · Molecular Neurobiology · doi:10.1007/s12035-018-0877-3 · Cited by 18

Review of Genetic Variation as a Predictive Biomarker for Chronic Graft-Versus-Host-Disease After Allogeneic Stem Cell Transplantation

Partanen, J., Hyvärinen, K., Bickeböller, H., Bogunia‐Kubik, K., Crossland, R. E., Ivanova, M., Perutelli, F., & Dressel, R. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.575492 · Cited by 18

Mapping Selection within Drosophila melanogaster Embryo’s Anatomy

Salvador‐Martínez, I., Coronado‐Zamora, M., Castellano, D., Barbadilla, A., & Salazar‐Ciudad, I. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx266 · Cited by 17

Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries

Smith, S. P., Shahamatdar, S., Cheng, W., Zhang, S., Paik, J., Graff, M., Haiman, C. A., Matise, T. C., North, K. E., Peters, U., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.03.005 · Cited by 17

Epigenetics and the Burden of Noncommunicable Disease: A Paucity of Research in Africa

Hobbs, A., & Ramsay, M. (2015) · Epigenomics · doi:10.2217/epi.15.17 · Cited by 17

Locus‐specific ancestry to detect recent response to selection in admixed Swiss Fleckvieh cattle

Khayatzadeh, N., Mészáros, G., Utsunomiya, Y. T., Garcia, J. F., Schnyder, U., Gredler, B., Čurik, I., & Sölkner, J. (2016) · Animal Genetics · doi:10.1111/age.12470 · Cited by 17

New insights into the genetic component of non-infectious uveitis through an Immunochip strategy

Márquez, A., Cordero‐Coma, M., Martín‐Villa, J. M., Gorroño-Echebarría, M. B., Blanco, R., Díaz‐Valle, D., del Rio, M. J., Blanco, A., Olea, J. L., Cordero, Y., et al. (2016) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2016-104144 · Cited by 17

The genomic potential of the Aspirin in Reducing Events in the Elderly and Statins in Reducing Events in the Elderly studies

Lacaze, P. A., Woods, R. L., Zoungas, S., McNeil, J. J., on behalf of the ASPREE Investigator Group, Biobank, A. H. A., & and the STAREE Investigator Group (2017) · Internal Medicine Journal · doi:10.1111/imj.13384 · Cited by 17

Spatial Structure of Synchronized Inhibition in the Olfactory Bulb

Arnson, H. A., & Strowbridge, B. W. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1004-17.2017 · Cited by 17

Hommel's procedure in linear time

Meijer, R. J., Krebs, T. J. P., & Goeman, J. J. (2018) · Biometrical Journal · doi:10.1002/bimj.201700316 · Cited by 17

SLC11A1 polymorphisms and host susceptibility to cutaneous leishmaniasis in Pakistan

Sophie, M., Hameed, A., Muneer, A., Samdani, A. J., Saleem, S., & Azhar, A. (2017) · Parasites & Vectors · doi:10.1186/s13071-016-1934-2 · Cited by 17

Association mapping of morphological traits in wild and captive zebra finches: reliable within, but not between populations

Knief, U., Schielzeth, H., Backström, N., Hemmrich‐Stanisak, G., Wittig, M., Franke, A., Griffith, S. C., Ellegren, H., Kempenaers, B., & Forstmeier, W. (2017) · Molecular Ecology · doi:10.1111/mec.14009 · Cited by 17

Systematic Review and Meta‐analysis of SNPs from Genome‐Wide Association Studies of Head and Neck Cancer

Vuković, V., Stojanovic, J., Vecchioni, A., Pastorino, R., & Boccia, S. (2018) · Otolaryngology · doi:10.1177/0194599818792262 · Cited by 17

Non-additive (dominance) effects of genetic variants associated with refractive error and myopia

Pozarickij, A., Williams, C., & Guggenheim, J. A. (2020) · Molecular Genetics and Genomics · doi:10.1007/s00438-020-01666-w · Cited by 16

Learning the optimal scale for GWAS through hierarchical SNP aggregation

Guinot, F., Szafranski, M., Ambroise, C., & Samson, F. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2475-9 · Cited by 16

Cross-ancestry analyses identify new genetic loci associated with 25-hydroxyvitamin D

Wang, X., Hivert, V., Groot, S., Wang, Y., Yengo, L., McGrath, J. J., Kemper, K. E., Visscher, P. M., Wray, N. R., & Revez, J. A. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1011033 · Cited by 15

Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes

Clark, M. M., Chazara, O., Sobel, E. M., Gjessing, H. K., Magnus, P. M., Moffett, A., & Sinsheimer, J. S. (2016) · Human Heredity · doi:10.1159/000456033 · Cited by 15

Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls

Gjerdevik, M., Jugessur, A., Haaland, Ø. A., Romanowska, J., Lie, R. T., Cordell, H. J., & Gjessing, H. K. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2727-3 · Cited by 16

Association Mapping of Lathyrus sativus Disease Response to Uromyces pisi Reveals Novel Loci Underlying Partial Resistance

Martins, D. C., Rubiales, D., & Patto, M. C. V. (2022) · Frontiers in Plant Science · doi:10.3389/fpls.2022.842545 · Cited by 15

Genome‐wide time‐to‐event analysis on smoking progression stages in a family‐based study

He, L., Pitkäniemi, J. M., Heikkila, K. V., Chou, Y., Madden, P. A. F., Korhonen, T., Sarin, A., Ripatti, S., Kaprio, J. A., & Loukola, A. (2016) · Brain and Behavior · doi:10.1002/brb3.462 · Cited by 15

Association of the CYP4V2 polymorphism rs13146272 with venous thromboembolism in a Chinese population

Yue, Y., Sun, Q., Man, G. C. W., & Fu, Y. (2018) · Clinical and Experimental Medicine · doi:10.1007/s10238-018-0529-y · Cited by 15

Exome array analysis of rare and low frequency variants in amyotrophic lateral sclerosis

Dekker, A. M., Diekstra, F. P., Pulit, S. L., Tazelaar, G. H. P., van der Spek, R. A. A., van Rheenen, W., van Eijk, K. R., Calvo, A., Brunetti, M., Damme, P. V., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-42091-3 · Cited by 16

Age-related late-onset disease heritability patterns and implications for genome-wide association studies

Oliynyk, R. T. (2019) · PeerJ · doi:10.7717/peerj.7168 · Cited by 15

Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia

Björn, N., Sigurgeirsson, B., Svedberg, A., Pradhananga, S., Brandén, E., Koyi, H., Lewensohn, R., Petris, L. D., Apellániz-Ruiz, M., Rodríguez‐Antona, C., et al. (2019) · The Pharmacogenomics Journal · doi:10.1038/s41397-019-0099-8 · Cited by 15

Dissecting the heritable risk of breast cancer: From statistical methods to susceptibility genes

Fanfani, V., Zátopková, M., Harris, A. L., Pezzella, F., & Stracquadanio, G. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.06.001 · Cited by 15

Differential patterns of age‐related cortical and subcortical functional connectivity in 6‐to‐10 year old children: A connectome‐wide association study

Langen, C. D., Muetzel, R. L., Blanken, L. M. E., van der Lugt, A., Tiemeier, H. W., Verhulst, F. C., Niessen, W. J., & White, T. J. H. (2018) · Brain and Behavior · doi:10.1002/brb3.1031 · Cited by 18

Multi-population GWAS detects robust marker associations in a newly established six-rowed winter barley breeding program

Skovbjerg, C. K., Sarup, P. M., Wahlström, E. M., Jensen, J. D., Orabi, J., Olesen, L., Jensen, J., Jahoor, A., & Ramstein, G. P. (2024) · Heredity · doi:10.1038/s41437-024-00733-x · Cited by 14

Genome-Wide Association Studies of Chemotherapeutic Toxicities: Genomics of Inequality

Mapes, B. L., Charif, O. E., Al-Sawwaf, S., & Dolan, M. E. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-0429 · Cited by 14

Epistasis: Searching for Interacting Genetic Variants Using Crosses

Ehrenreich, I. M. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.117.042770 · Cited by 14

Genomics of Alzheimer's disease: Value of high-throughput genomic technologies to dissect its etiology

Tosto, G., & Reitz, C. (2016) · Molecular and Cellular Probes · doi:10.1016/j.mcp.2016.09.001 · Cited by 14

Genetic variants underlying vitamin D metabolism and VDR–TGFβ-1–SMAD3 interaction may impact on HCV progression: a study based on dbGaP data from the HALT-C study

de Azevedo, L. A., Matte, Ú. D. S., da Silveira, T. R., & Álvares‐da‐Silva, M. R. (2017) · Journal of Human Genetics · doi:10.1038/jhg.2017.75 · Cited by 14

An exome sequencing based approach for genome-wide association studies in the dog

Broeckx, B. J. G., Derrien, T., Mottier, S., Wucher, V., Cadieu, É., Hédan, B., Béguec, C. L., Botherel, N., Lindblad‐Toh, K., Saunders, J. H., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-15947-9 · Cited by 14

Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines

Bush, W. S., Bailey, J. N. C., Beno, M. F., & Crawford, D. C. (2019) · Public Health Genomics · doi:10.1159/000501974 · Cited by 14

Genetic variation in the alpha1B-adrenergic receptor and vascular response

Adefurin, A., Ghimire, L. V., Kohli, U., Muszkat, M., Sofowora, G. G., Li, C., Levinson, R. T., Paranjape, S. Y., Stein, C. M., & Kurnik, D. (2016) · The Pharmacogenomics Journal · doi:10.1038/tpj.2016.29 · Cited by 14

SWEDEGENE—a Swedish nation-wide DNA sample collection for pharmacogenomic studies of serious adverse drug reactions

Hallberg, P., Yue, Q., Eliasson, E., Melhus, H., Ås, J., & Wadelius, M. (2020) · The Pharmacogenomics Journal · doi:10.1038/s41397-020-0148-3 · Cited by 14

Next-Generation Omics Technologies for Exploring Complex Metabolic Regulation During Plant-Microbe Interaction

Sarim, K. M., Srivastava, R., & Ramteke, P. W. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819978-7.00009-9 · Cited by 13

Genetic variation in ALDH4A1 is associated with muscle health over the lifespan and across species

Villa, O., Stuhr, N. L., Yen, C.-A., Crimmins, E. M., Arpawong, T. E., & Curran, S. P. (2022) · eLife · doi:10.7554/elife.74308 · Cited by 13

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival

Kim, S., Welsh, D. A., Myers, L., Cherry, K. E., Wyckoff, J., & Jazwinski, S. M. (2015) · Oncotarget · doi:10.18632/oncotarget.2877 · Cited by 13

Association between UCP1, UCP2, and UCP3 gene polymorphisms with markers of adiposity in European adolescents: The HELENA study

Pascual-Gamarra, J. M., Salazar‐Tortosa, D. F., Martínez‐Téllez, B., Labayen, I., Rupérez, A. I., Censi, L., Μanios, Y., Nova, E., Gesteiro, E., Moreno, L. A., et al. (2019) · Pediatric Obesity · doi:10.1111/ijpo.12504 · Cited by 14

Genes for fibrogenesis in the determination of susceptibility to myocardial infarction

Goncharova, I. A., Makeeva, O. A., Golubenko, M. V., Markov, A., Тарасенко, Н. В., Sleptcov, A. A., & Puzyrev, V. P. (2016) · Molecular Biology · doi:10.1134/s0026893315060096 · Cited by 13

Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattlePreprint

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