R: A Language and Environment for Statistical Computing

Climate Change, Elevational Range Shifts, and Bird Extinctions

SEKERCIOGLU, C. H., SCHNEIDER, S. H., FAY, J. P., & LOARIE, S. R. (2008) · Conservation Biology · doi:10.1111/j.1523-1739.2007.00852.x · Cited by 683

Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts

Gallone, B., Steensels, J., Prahl, T., Soriaga, L., Saels, V., Herrera-Malaver, B., Merlevede, A., Roncoroni, M., Voordeckers, K., Miraglia, L., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.020 · Cited by 679

Large mammal population declines in Africa’s protected areas

Craigie, I. D., Baillie, J. E. M., Balmford, A., Carbone, C., Collen, B., Green, R. E., & Hutton, J. M. (2010) · Biological Conservation · doi:10.1016/j.biocon.2010.06.007 · Cited by 685

Human orbitofrontal cortex represents a cognitive map of state space

Schuck, N. W., Cai, M. B., Wilson, R. C., & Niv, Y. (2016) · Neuron · doi:10.1016/j.neuron.2016.08.019 · Cited by 602

Estimation of the size of drug-like chemical space based on GDB-17 data

Polishchuk, P. G., Madzhidov, T. I., & Varnek, A. (2013) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-013-9672-4 · Cited by 619

Mining big data: current status, and forecast to the future

Fan, W., & Bifet, A. (2013) · ACM SIGKDD Explorations Newsletter · doi:10.1145/2481244.2481246 · Cited by 677

Gender differences in the prevalence of nonsuicidal self-injury: A meta-analysis

Bresin, K., & Schoenleber, M. (2015) · Clinical Psychology Review · doi:10.1016/j.cpr.2015.02.009 · Cited by 678

Global estimates of the prevalence of hyperglycaemia in pregnancy

Guariguata, L., Linnenkamp, U., Beagley, J., Whiting, D. R., & Cho, N. H. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.11.003 · Cited by 664

Optimal temperature for malaria transmission is dramatically lower than previously predicted

Mordecai, E. A., Paaijmans, K. P., Johnson, L. R., Balzer, C., Ben‐Horin, T., de Moor, E., McNally, A., Pawar, S., Ryan, S. J., Smith, T. C., et al. (2013) · Ecology Letters · doi:10.1111/ele.12015 · Cited by 680

Coping flexibility and psychological adjustment to stressful life changes: A meta-analytic review.

Cheng, C., Lau, H.-P. B., & Chan, M.-P. S. (2014) · Psychological Bulletin · doi:10.1037/a0037913 · Cited by 664

Endogenous Testosterone and Mortality in Men: A Systematic Review and Meta-Analysis

Araujo, A. B., Dixon, J. M., Suarez, E. A., Murad, M. H., Guey, L. T., & Wittert, G. A. (2011) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2011-1137 · Cited by 671

What is known and unknown about the effects of plastic pollution: A meta-analysis and systematic review

Bucci, K., Tulio, M., & Rochman, C. M. (2020) · Ecological Applications · doi:10.1002/eap.2044 · Cited by 658

Widespread intron retention in mammals functionally tunes transcriptomes

Braunschweig, U., Barbosa-Morais, N. L., Pan, Q., Nachman, E. N., Alipanahi, B., Gonatopoulos-Pournatzis, T., Frey, B., Irimia, M., & Blencowe, B. J. (2014) · Genome Research · doi:10.1101/gr.177790.114 · Cited by 664

Validation of the revised Mystical Experience Questionnaire in experimental sessions with psilocybin

Barrett, F. S., Johnson, M. W., & Griffiths, R. R. (2015) · Journal of Psychopharmacology · doi:10.1177/0269881115609019 · Cited by 637

Calibrating Probability with Undersampling for Unbalanced Classification

Pozzolo, A. D., Caelen, O., Johnson, R. A., & Bontempi, G. (2015) · 2015 IEEE Symposium Series on Computational Intelligence · doi:10.1109/ssci.2015.33 · Cited by 667

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe

Martin, E. A., Dainese, M., Clough, Y., Báldi, A., Bommarco, R., Gagic, V., Garratt, M. P. D., Holzschuh, A., Kleijn, D., Kovács‐Hostyánszki, A., et al. (2019) · Ecology Letters · doi:10.1111/ele.13265 · Cited by 648

A Generalized K Statistic for Estimating Phylogenetic Signal from Shape and Other High-Dimensional Multivariate Data

Adams, D. C. (2014) · Systematic Biology · doi:10.1093/sysbio/syu030 · Cited by 653

Suicide Rates After Discharge From Psychiatric Facilities: A Systematic Review and Meta-analysis

Chung, D. T., Ryan, C. J., Hadzi-Pavlovic, D., Singh, S. P., Stanton, C., & Large, M. M. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.1044 · Cited by 651

Longitudinal Changes in Adolescent Risk-Taking: A Comprehensive Study of Neural Responses to Rewards, Pubertal Development, and Risk-Taking Behavior

Braams, B. R., van Duijvenvoorde, A. C. K., Peper, J. S., & Crone, E. A. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4764-14.2015 · Cited by 617

Exploring the potential of using an AI language model for automated essay scoring

Mizumoto, A., & Eguchi, M. (2023) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2023.100050 · Cited by 647

The oral microbiota in colorectal cancer is distinctive and predictive

Flemer, B., Warren, R. D., Barrett, M. P., Cisek, K., Das, A., Jeffery, I. B., Hurley, E., O‘Riordain, M., Shanahan, F., & O‘Toole, P. W. (2018) · Gut · doi:10.1136/gutjnl-2017-314814 · Cited by 646

Global patterns of bacterial beta-diversity in seafloor and seawater ecosystems

Zinger, L., Amaral-Zettler, L. A., Fuhrman, J. A., Horner-Devine, M. C., Huse, S. M., Welch, D. B. M., Martiny, J. B. H., Sogin, M., Boetius, A., & Ramette, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024570 · Cited by 643

Simplifying Microplastic via Continuous Probability Distributions for Size, Shape, and Density

Kooi, M., & Koelmans, A. A. (2019) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.9b00379 · Cited by 639

Childhood maltreatment is associated with reduced volume in the hippocampal subfields CA3, dentate gyrus, and subiculum

Teicher, M. H., Anderson, C. M., & Polcari, A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115396109 · Cited by 639

Association between psychological distress and mortality: individual participant pooled analysis of 10 prospective cohort studies

Russ, T. C., Stamatakis, E., Hamer, M., Starr, J. M., Kivimaki, M., & Batty, G. D. (2012) · BMJ · doi:10.1136/bmj.e4933 · Cited by 637

Meta-analysis of dropout in treatments for posttraumatic stress disorder

Imel, Z. E., Laska, K., Jakupcak, M., & Simpson, T. L. (2013) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0031474 · Cited by 633

Rodent reservoirs of future zoonotic diseases

Han, B. A., Schmidt, J. P., Bowden, S. E., & Drake, J. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1501598112 · Cited by 629

Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation

O’Gorman, N., Wright, D., Syngelaki, A., Akolekar, R., Wright, A., Poon, L. C., & Nicolaides, K. H. (2016) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2015.08.034 · Cited by 629

Fecal pollution can explain antibiotic resistance gene abundances in anthropogenically impacted environments

Karkman, A., Pärnänen, K., & Larsson, D. G. J. (2019) · Nature Communications · doi:10.1038/s41467-018-07992-3 · Cited by 628

Parameter estimation for differential equations: a generalized smoothing approach

Ramsay, J. O., Hooker, G., Campbell, D., & Cao, J. (2007) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2007.00610.x · Cited by 613

The AIC model selection method applied to path analytic models compared using a d‐separation test

Shipley, B. (2013) · Ecology · doi:10.1890/12-0976.1 · Cited by 606

Estimated life expectancy in a Scottish cohort with type 1 diabetes, 2008-2010

Livingstone, S. J., Levin, D., Looker, H. C., Lindsay, R. S., Wild, S. H., Joss, N., Leese, G., Leslie, P., McCrimmon, R. J., Metcalfe, W., et al. (2015) · JAMA · doi:10.1001/jama.2014.16425 · Cited by 621

Operating parameters for bio-oil production in biomass pyrolysis: A review

Guedes, R. E., Luna, A. S., & Torres, A. R. (2018) · Journal of Analytical and Applied Pyrolysis · doi:10.1016/j.jaap.2017.11.019 · Cited by 619

Biodiversity, Ecosystem Functioning, and Human Wellbeing: An Ecological and Economic Perspective

(2009) · doi:10.1093/acprof:oso/9780199547951.001.0001 · Cited by 608

Recruitment and retention of participants in randomised controlled trials: a review of trials funded and published by the United Kingdom Health Technology Assessment Programme

Walters, S. J., Bonacho dos Anjos Henriques-Cadby, I., Bortolami, O., Flight, L., Hind, D., Jacques, R. M., Knox, C., Nadin, B., Rothwell, J., Surtees, M., et al. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-015276 · Cited by 560

Heritability of schizophrenia and schizophrenia spectrum based on the nationwide danish twin register

Hilker, R., Helenius, D., Fagerlund, B., Skytthe, A., Christensen, K., Werge, T. M., Nordentoft, M., & Glenthøj, B. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.08.017 · Cited by 615

Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence

Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0536-12.2012 · Cited by 613

A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes

Cheung, M. W.-L. (2019) · Neuropsychology Review · doi:10.1007/s11065-019-09415-6 · Cited by 610

HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling

Roemer, E., Schuberth, F., & Henseler, J. (2021) · Industrial Management & Data Systems · doi:10.1108/imds-02-2021-0082 · Cited by 630

The Gut Microbiota of Rural Papua New Guineans: Composition, Diversity Patterns, and Ecological Processes

Martínez, I., Stegen, J. C., Maldonado-Gómez, M. X., Eren, A. M., Siba, P. M., Greenhill, A. R., & Walter, J. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.03.049 · Cited by 576

Contact with blue-green spaces during the COVID-19 pandemic lockdown beneficial for mental health.

Pouso, S., Borja, Á., Fleming, L. E., Gómez-Baggethun, E., White, M. P., & Uyarra, M. C. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.143984 · Cited by 604

Pervasive Sharing of Genetic Effects in Autoimmune Disease

Cotsapas, C., Voight, B. F., Rossin, E., Lage, K., Neale, B. M., Wallace, C., Abecasis, G. R., Barrett, J. C., Behrens, T., Cho, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002254 · Cited by 606

Association of Gestational Diabetes With Maternal Disorders of Glucose Metabolism and Childhood Adiposity

Lowe, W. L., Scholtens, D. M., Lowe, L. P., Kuang, A., Nodzenski, M., Talbot, O., Catalano, P. M., Linder, B., Brickman, W. J., Clayton, P., et al. (2018) · JAMA · doi:10.1001/jama.2018.11628 · Cited by 591

Risk Factors for School Absenteeism and Dropout: A Meta-Analytic Review

Gubbels, J., van der Put, C. E., & Assink, M. (2019) · Journal of Youth and Adolescence · doi:10.1007/s10964-019-01072-5 · Cited by 596

Vegetarian dietary patterns and mortality in Adventist Health Study 2

Orlich, M. J., Singh, P. N., Sabaté, J., Jaceldo-Siegl, K., Fan, J., Knutsen, S., Beeson, W. L., & Fraser, G. E. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.6473 · Cited by 607

A review of spline function procedures in R

Perperoglou, A., Sauerbrei, W., Abrahamowicz, M., & Schmid, M. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-019-0666-3 · Cited by 585

Biofouling on buoyant marine plastics: an experimental study into the effect of size on surface longevity

Fazey, F. M. C., & Ryan, P. G. (2016) · Environmental Pollution · doi:10.1016/j.envpol.2016.01.026 · Cited by 588

Microbes on a bottle: substrate, season and geography influence community composition of microbes colonizing marine plastic debris

Oberbeckmann, S., Osborn, A. M., & Duhaime, M. B. (2016) · PLOS ONE · doi:10.1371/journal.pone.0159289 · Cited by 572

Correcting for Bias in Psychology: A Comparison of Meta-Analytic Methods

Carter, E. C., Schönbrodt, F. D., Gervais, W. M., & Hilgard, J. (2019) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245919847196 · Cited by 588

Overview of Friedman’s test and post-hoc analysis

Pereira, D. G., Afonso, A., & Medeiros, F. M. (2015) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2014.931971 · Cited by 585

Circadian patterns of gene expression in the human brain and disruption in major depressive disorder

Li, J. Z., Bunney, B. G., Meng, F., Hagenauer, M. H., Walsh, D. M., Vawter, M. P., Evans, S. J., Choudary, P. V., Cartagena, P., Barchas, J. D., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1305814110 · Cited by 589

Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics

Fritz, S. A., Bininda‐Emonds, O. R. P., & Purvis, A. (2009) · Ecology Letters · doi:10.1111/j.1461-0248.2009.01307.x · Cited by 585

Model Choice in Time Series Studies of Air Pollution and Mortality

Peng, R. D., Dominici, F., & Louis, T. A. (2006) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2006.00410.x · Cited by 583

Season, sex, age, and education as modifiers of the effects of outdoor air pollution on daily mortality in Shanghai, China: the Public Health and Air Pollution in Asia (PAPA) Study

Kan, H., London, S. J., Chen, G., Zhang, Y., Song, G., Zhao, N., Jiang, L., & Chen, B. (2008) · Environmental Health Perspectives · doi:10.1289/ehp.10851 · Cited by 582

CNV-seq, a new method to detect copy number variation using high-throughput sequencing

Xie, C., & Tammi, M. T. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-80 · Cited by 582

Evaluation of inconsistency in networks of interventions

Veroniki, A. A., Vasiliadis, H. S., Higgins, J. P., & Salanti, G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dys222 · Cited by 576

The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder

Heintz‐Buschart, A., Pandey, U., Wicke, T., Sixel‐Döring, F., Janzen, A., Sittig‐Wiegand, E., Trenkwalder, C., Oertel, W. H., Mollenhauer, B., & Wilmes, P. (2018) · Movement Disorders · doi:10.1002/mds.27105 · Cited by 554

Increasing crop heterogeneity enhances multitrophic diversity across agricultural regions

Sirami, C., Gross, N., Baillod, A. B., Bertrand, C., Carrié, R., Hass, A., Henckel, L., Miguet, P., Vuillot, C., Alignier, A., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1906419116 · Cited by 562

Microbiota of Human Breast Tissue

Urbaniak, C., Cummins, J., Brackstone, M., Macklaim, J. M., Gloor, G. B., Baban, C. K., Scott, L., O'Hanlon, D. M., Burton, J. P., Francis, K. P., et al. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.00242-14 · Cited by 552

Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): maternal gestational diabetes mellitus and childhood glucose metabolism

Lowe, W. L., Scholtens, D. M., Kuang, A., Linder, B., Lawrence, J. M., Lebenthal, Y., McCance, D., Hamilton, J., Nodzenski, M., Talbot, O., et al. (2019) · Diabetes Care · doi:10.2337/dc18-1646 · Cited by 574

Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease

Lunnon, K., Smith, R., Hannon, E., De Jager, P. L., Srivastava, G., Volta, M., Troakes, C., Al-Sarraj, S., Burrage, J., Macdonald, R., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3782 · Cited by 574

flexsurv : A Platform for Parametric Survival Modeling in R

Jackson, C. (2016) · Journal of Statistical Software · doi:10.18637/jss.v070.i08 · Cited by 558

Identity, Critical Agency, and Engineering: An Affective Model for Predicting Engineering as a Career Choice

Godwin, A., Potvin, G., Hazari, Z., & Lock, R. (2016) · Journal of Engineering Education · doi:10.1002/jee.20118 · Cited by 574

Depression and anxiety in patients with Inflammatory Bowel Disease: a systematic review

Neuendorf, R., Harding, A., Stello, N., Hanes, D., & Wahbeh, H. (2016) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2016.06.001 · Cited by 561

In vivo evidence for a lactate gradient from astrocytes to neurons

Mächler, P., Wyss, M. T., Elsayed, M., Stobart, J., Gutierrez, R., von Faber-Castell, A., Kaelin, V., Zuend, M., San Martín, A., Romero-Gómez, I., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.10.010 · Cited by 571

Dietary fibre and whole grains in diabetes management: Systematic review and meta-analyses

Reynolds, A. N., Akerman, A. P., & Mann, J. (2020) · PLOS Medicine · doi:10.1371/journal.pmed.1003053 · Cited by 567

Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions

Pan, C., Kumar, C., Bohl, S., Klingmueller, U., & Mann, M. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800258-mcp200 · Cited by 561

Spatial Variation in the Healthy Human Lung Microbiome and the Adapted Island Model of Lung Biogeography

Dickson, R. P., Erb-Downward, J. R., Freeman, C. M., McCloskey, L., Beck, J. M., Huffnagle, G. B., & Curtis, J. L. (2015) · Annals of the American Thoracic Society · doi:10.1513/annalsats.201501-029oc · Cited by 567

What causes psychosis? An umbrella review of risk and protective factors

Radua, J., Ramella‐Cravaro, V., Ioannidis, J. P. A., Reichenberg, A., Phiphopthatsanee, N., Amir, T., Yenn Thoo, H., Oliver, D., Davies, C., Morgan, C., et al. (2018) · World Psychiatry · doi:10.1002/wps.20490 · Cited by 553

Classroom management self-efficacy and burnout: A multivariate meta-analysis

Aloe, A. M., Amo, L. C., & Shanahan, M. E. (2014) · Educational Psychology Review · doi:10.1007/s10648-013-9244-0 · Cited by 560

Meta-analysis using individual participant data: One-stage and two-stage approaches, and why they may differ

Burke, D. L., Ensor, J., & Riley, R. D. (2017) · Statistics in Medicine · doi:10.1002/sim.7141 · Cited by 538

The Ordinal Effects of Ostracism: A Meta-Analysis of 120 Cyberball Studies

Hartgerink, C. H. J., van Beest, I., Wicherts, J. M., & Williams, K. D. (2015) · PLOS ONE · doi:10.1371/journal.pone.0127002 · Cited by 558

The prevalence of statistical reporting errors in psychology (1985–2013)

Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2016) · Behavior Research Methods · doi:10.3758/s13428-015-0664-2 · Cited by 510

Developmental cognitive neuroscience using latent change score models: A tutorial and applications

Kievit, R. A., Brandmaier, A. M., Ziegler, G., van Harmelen, A.-L., de Mooij, S. M. M., Moutoussis, M., Goodyer, I. M., Bullmore, E., Jones, P. B., Fonagy, P., et al. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.11.007 · Cited by 516

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry

Tabb, D. L., Vega-Montoto, L., Rudnick, P. A., Variyath, A. M., Ham, A.-J. L., Bunk, D. M., Kilpatrick, L. E., Billheimer, D. D., Blackman, R. K., Cardasis, H. L., et al. (2010) · Journal of Proteome Research · doi:10.1021/pr9006365 · Cited by 551

Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)

Gruber, C. N., Patel, R. S., Trachtman, R., Lepow, L., Amanat, F., Krammer, F., Wilson, K. M., Onel, K., Geanon, D., Tuballes, K., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.034 · Cited by 551

Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis

Barro, C., Benkert, P., Disanto, G., Tsagkas, C., Amann, M., Naegelin, Y., Leppert, D., Gobbi, C., Granziera, C., Yaldizli, Ö., et al. (2018) · Brain · doi:10.1093/brain/awy154 · Cited by 517

A genetically encoded fluorescent sensor for rapid and specific in vivo detection of norepinephrine

Feng, J., Zhang, C., Lischinsky, J. E., Jing, M., Zhou, J., Wang, H., Zhang, Y., Dong, A., Wu, Z., Wu, H., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.02.037 · Cited by 545

Bacterial topography of the healthy human lower respiratory tract

Dickson, R. P., Erb-Downward, J. R., Freeman, C. M., McCloskey, L., Falkowski, N. R., Huffnagle, G. B., & Curtis, J. L. (2017) · mBio · doi:10.1128/mbio.02287-16 · Cited by 548

Widespread and Functional RNA Circularization in Localized Prostate Cancer

Chen, S., Huang, V., Xu, X., Livingstone, J., Soares, F., Jeon, J., Zeng, Y., Hua, J. T., Petricca, J., Guo, H., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.025 · Cited by 544

Deciphering the distribution of the savanna biome

Lehmann, C. E. R., Archibald, S. A., Hoffmann, W. A., & Bond, W. J. (2011) · New Phytologist · doi:10.1111/j.1469-8137.2011.03689.x · Cited by 523

Simpson's paradox in psychological science: a practical guide

Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00513 · Cited by 542

Happy to help? A systematic review and meta-analysis of the effects of performing acts of kindness on the well-being of the actor

Curry, O. S., Rowland, L. A., Van Lissa, C. J., Zlotowitz, S., McAlaney, J., & Whitehouse, H. (2018) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2018.02.014 · Cited by 528

Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota

Lauder, A. P., Roche, A. M., Sherrill-Mix, S., Bailey, A., Laughlin, A. L., Bittinger, K., Leite, R., Elovitz, M. A., Parry, S., & Bushman, F. D. (2016) · Microbiome · doi:10.1186/s40168-016-0172-3 · Cited by 539

Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis

Groenwold, R. H. H., White, I. R., Donders, A. R. T., Carpenter, J. R., Altman, D. G., & Moons, K. G. M. (2012) · Canadian Medical Association Journal · doi:10.1503/cmaj.110977 · Cited by 538

Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology: Concepts and Practice

(2014) · doi:10.1007/978-3-662-43550-2 · Cited by 538

A prospective phase II trial exploring the association between tumor microenvironment biomarkers and clinical activity of ipilimumab in advanced melanoma

Hamid, O., Schmidt, H., Nissan, A., Ridolfi, L., Aamdal, S., Hansson, J., Guida, M., Hyams, D. M., Gómez, H., Bastholt, L., et al. (2011) · Journal of Translational Medicine · doi:10.1186/1479-5876-9-204 · Cited by 534

Thalidomide promotes degradation of SALL4, a transcription factor implicated in Duane Radial Ray syndrome

Donovan, K. A., An, J., Nowak, R. P., Yuan, J. C., Fink, E. C., Berry, B. C., Ebert, B. L., & Fischer, E. S. (2018) · eLife · doi:10.7554/elife.38430 · Cited by 509

Examples of mixed-effects modeling with crossed random effects and with binomial data

Quené, H., & van den Bergh, H. (2008) · Journal of Memory and Language · doi:10.1016/j.jml.2008.02.002 · Cited by 534

Kombucha tea fermentation: Microbial and biochemical dynamics

Chakravorty, S., Bhattacharya, S., Chatzinotas, A., Chakraborty, W., Bhattacharya, D., & Gachhui, R. (2016) · International Journal of Food Microbiology · doi:10.1016/j.ijfoodmicro.2015.12.015 · Cited by 533

Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: A multicentre survey

Sit, C., Srinivasan, R., Amlani, A., Muthuswamy, K., Azam, A., Monzon, L., & Poon, D. S. (2020) · Insights into Imaging · doi:10.1186/s13244-019-0830-7 · Cited by 507

Diversity of the human skin microbiome early in life

Capone, K. A., Dowd, S. E., Stamatas, G. N., & Nikolovski, J. (2011) · Journal of Investigative Dermatology · doi:10.1038/jid.2011.168 · Cited by 532

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient

Yang, T., Zhang, F., Yardımcı, G. G., Song, F., Hardison, R. C., Noble, W. S., Yue, F., & Li, Q. (2017) · Genome Research · doi:10.1101/gr.220640.117 · Cited by 533

rehh : an R package to detect footprints of selection in genome-wide SNP data from haplotype structure

Gautier, M., & Vitalis, R. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts115 · Cited by 528

Gut vascular barrier impairment leads to intestinal bacteria dissemination and colorectal cancer metastasis to liver

Bertocchi, A., Carloni, S., Ravenda, P. S., Bertalot, G., Spadoni, I., Lo Cascio, A., Gandini, S., Lizier, M., Braga, D., Asnicar, F., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.03.004 · Cited by 515

Immunoresponsive Gene 1 and Itaconate Inhibit Succinate Dehydrogenase to Modulate Intracellular Succinate Levels

Cordes, T., Wallace, M., Michelucci, A., Divakaruni, A. S., Sapcariu, S. C., Sousa, C., Koseki, H., Cabrales, P., Murphy, A. N., Hiller, K., et al. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m115.685792 · Cited by 526

Epigenetic and immune function profiles associated with posttraumatic stress disorder

Uddin, M., Aiello, A. E., Wildman, D. E., Koenen, K. C., Pawelec, G., de los Santos, R., Goldmann, E., & Galea, S. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910794107 · Cited by 518

Deep MRI brain extraction: A 3D convolutional neural network for skull stripping

Kleesiek, J., Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., & Biller, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.024 · Cited by 505

A Spectrum of PCSK9 Alleles Contributes to Plasma Levels of Low-Density Lipoprotein Cholesterol

Kotowski, I. K., Pertsemlidis, A., Luke, A., Cooper, R. S., Vega, G. L., Cohen, J. C., & Hobbs, H. H. (2006) · The American Journal of Human Genetics · doi:10.1086/500615 · Cited by 517

Phylogenetic diversity promotes ecosystem stability

Cadotte, M. W., Dinnage, R., & Tilman, D. (2012) · Ecology · doi:10.1890/11-0426.1 · Cited by 515