ggplot2: Elegant Graphics for Data Analysis

Microplastic contamination in Lake Winnipeg, Canada

Anderson, P. J., Warrack, S., Langen, V., Challis, J. K., Hanson, M. L., & Rennie, M. D. (2017) · Environmental Pollution · doi:10.1016/j.envpol.2017.02.072 · Cited by 488

Interactive dynamics for visual analysis

Heer, J., & Shneiderman, B. (2012) · Communications of the ACM · doi:10.1145/2133806.2133821 · Cited by 484

Deciphering the “m6A Code” via Antibody-Independent Quantitative Profiling

García-Campos, M. A., Edelheit, S., Toth, U., Safra, M., Shachar, R., Viukov, S. V., Winkler, R., Nir, R., Lasman, L., Brandis, A. S., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.013 · Cited by 479

Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues

Bartosovic, M., Kabbe, M., & Castelo-Branco, G. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00869-9 · Cited by 483

A recent bottleneck of Y chromosome diversity coincides with a global change in culturePreprint

Karmin, M., Saag, L., Vicente, M., Sayres, M. A. W., Järve, M., Talas, U. G., Rootsi, S., Ilumäe, A.-M., Mägi, R., Mitt, M., et al. (2015) · Genome Research · doi:10.1101/gr.186684.114 · Cited by 480

Cardiorespiratory fitness as a predictor of intestinal microbial diversity and distinct metagenomic functions

Estaki, M., Pither, J., Baumeister, P., Little, J. P., Gill, S. K., Ghosh, S., Ahmadi-Vand, Z., Marsden, K. R., & Gibson, D. L. (2016) · Microbiome · doi:10.1186/s40168-016-0189-7 · Cited by 476

Pirfenidone in patients with progressive fibrotic interstitial lung diseases other than idiopathic pulmonary fibrosis (RELIEF): a double-blind, randomised, placebo-controlled, phase 2b trial

Behr, J., Prasse, A., Kreuter, M., Johow, J., Rabe, K. F., Bonella, F., Bonnet, R., Grohe, C., Held, M., Wilkens, H., et al. (2021) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30554-3 · Cited by 522

A pH-driven transition of the cytoplasm from a fluid- to a solid-like state promotes entry into dormancy

Munder, M. C., Midtvedt, D., Franzmann, T. M., Nüske, E., Otto, O., Herbig, M., Ulbricht, E., Müller, P. F., Taubenberger, A. V., Maharana, S., et al. (2016) · eLife · doi:10.7554/elife.09347 · Cited by 476

The Effects of Changes in Utilization and Technological Advancements of Cross-Sectional Imaging on Radiologist Workload

McDonald, R. J., Schwartz, K. M., Eckel, L. J., Diehn, F. E., Hunt, C. H., Bartholmai, B. J., Erickson, B. J., & Kallmes, D. F. (2015) · Academic Radiology · doi:10.1016/j.acra.2015.05.007 · Cited by 460

DNA Repair Network Analysis Reveals Shieldin as a Key Regulator of NHEJ and PARP Inhibitor Sensitivity

Gupta, R., Somyajit, K., Narita, T., Maskey, E., Stanlie, A., Kremer, M., Typas, D., Lammers, M., Mailand, N., Nussenzweig, A., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.050 · Cited by 480

Sample size planning for classification models

Beleites, C., Neugebauer, U., Bocklitz, T. W., Krafft, C., & Popp, J. (2012) · Analytica Chimica Acta · doi:10.1016/j.aca.2012.11.007 · Cited by 465

Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing

Prodan, A., Tremaroli, V., Brolin, H., Zwinderman, A. H., Nieuwdorp, M., & Levin, E. (2020) · PLOS ONE · doi:10.1371/journal.pone.0227434 · Cited by 462

KLRG1+ Effector CD8+ T Cells Lose KLRG1, Differentiate into All Memory T Cell Lineages, and Convey Enhanced Protective Immunity

Herndler‐Brandstetter, D., Ishigame, H., Shinnakasu, R., Plajer, V., Stecher, C., Zhao, J., Lietzenmayer, M., Kroehling, L., Takumi, A., Kometani, K., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.03.015 · Cited by 457

Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization

Finn, E. H., Pegoraro, G., Brandão, H. B., Valton, A.-L., Oomen, M. E., Dekker, J., Mirny, L., & Misteli, T. (2019) · Cell · doi:10.1016/j.cell.2019.01.020 · Cited by 459

A global review of past land use, climate, and active vs. passive restoration effects on forest recovery

Meli, P., Holl, K. D., Beñayas, J. M. R., Jones, H. P., Jones, P. C., Montoya, D., & Moreno‐Mateos, D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171368 · Cited by 484

Dynamic CD8+ T cell responses to cancer immunotherapy in human regional lymph nodes are disrupted in metastatic lymph nodes

Rahim, M. K., Okholm, T. L. H., Jones, K. B., McCarthy, E. E., Liu, C. C., Yee, J. L., Tamaki, S. J., Marquez, D. M., Tenvooren, I., Wai, K., et al. (2023) · Cell · doi:10.1016/j.cell.2023.02.021 · Cited by 455

Seagrass ecosystems reduce exposure to bacterial pathogens of humans, fishes, and invertebrates

Lamb, J. B., van de Water, J. A. J. M., Bourne, D. G., Altier, C., Hein, M. Y., Fiorenza, E. A., Abu, N., Jompa, J., & Harvell, C. D. (2017) · Science · doi:10.1126/science.aal1956 · Cited by 473

Impact of delivery mode-associated gut microbiota dynamics on health in the first year of life

Reyman, M., van Houten, M. A., van Baarle, D., Bosch, A. A. T. M., Man, W. H., Chu, M. L. J. N., Arp, K., Watson, R. L., Sanders, E. A. M., Fuentes, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13014-7 · Cited by 477

Prevalence of Mental Illnesses in U.S. State Prisons: A Systematic Review

Prins, S. J. (2014) · Psychiatric Services · doi:10.1176/appi.ps.201300166 · Cited by 509

Developmental stages and sex differences of white matter and behavioral development through adolescence: A longitudinal diffusion tensor imaging (DTI) study

Simmonds, D. J., Hallquist, M. N., Asato, M. R., & Luna, B. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.044 · Cited by 473

Genome-centric view of carbon processing in thawing permafrost

Woodcroft, B. J., Singleton, C. M., Boyd, J. A., Evans, P. N., Emerson, J., Zayed, A. A., Hoelzle, R. D., Lamberton, T. O., Mccalley, C. K., Hodgkins, S. B., et al. (2018) · Nature · doi:10.1038/s41586-018-0338-1 · Cited by 457

Prevalence of refractive error in Europe: the European Eye Epidemiology (E3) Consortium

Williams, K. M., Verhoeven, V. J. M., Cumberland, P. M., Bertelsen, G., Wolfram, C., Buitendijk, G. H. S., Albert Hofman, D., van Duijn, C. M., Vingerling, J. R., Kuijpers, R. W. A. M., et al. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-0010-0 · Cited by 449

rfishbase: exploring, manipulating and visualizing FishBase data from R

Boettiger, C., Lang, D. T., & Wainwright, P. C. (2012) · Journal of Fish Biology · doi:10.1111/j.1095-8649.2012.03464.x · Cited by 444

Tissue Determinants of Human NK Cell Development, Function, and Residence

Dogra, P., Rancan, C., Ma, W., Tóth, M., Senda, T., Carpenter, D. J., Kubota, M., Matsumoto, R., Thapa, P., Szabo, P. A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.022 · Cited by 456

Reduction of motion-related artifacts in resting state fMRI using aCompCor

Muschelli, J., Nebel, M. B., Caffo, B. S., Barber, A. D., Pekar, J. J., & Mostofsky, S. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.028 · Cited by 431

The native microbiome of the nematode Caenorhabditis elegans: gateway to a new host-microbiome model

Dirksen, P., Marsh, S., Braker, I., Heitland, N., Wagner, S., Nakad, R., Mäder, S., Petersen, C., Kowallik, V., Rosenstiel, P. C., et al. (2016) · BMC Biology · doi:10.1186/s12915-016-0258-1 · Cited by 434

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

Praveen, B., Talukdar, S., Shahfahad, Mahato, S., Mondal, J., Sharma, P., Islam, A. R. M. T., & Rahman, A. (2020) · Scientific Reports · doi:10.1038/s41598-020-67228-7 · Cited by 439

Summer warming explains widespread but not uniform greening in the Arctic tundra biome

Berner, L. T., Massey, R., Jantz, P. A., Forbes, B. C., Macias‐Fauria, M., Myers‐Smith, I. H., Kumpula, T., Gauthier, G., Andreu‐Hayles, L., Gaglioti, B. V., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18479-5 · Cited by 483

From genome-wide arrays to tailor-made biomarker readout – Progress towards routine analysis of skin sensitizing chemicals with GARD

Forreryd, A., Zeller, K. S., Lindberg, T., Johansson, H., & Lindstedt, M. (2016) · Toxicology in Vitro · doi:10.1016/j.tiv.2016.09.013 · Cited by 442

COVID-19 surveillance in Southeastern Virginia using wastewater-based epidemiology

González, R., Curtis, K., Bivins, A. W., Bibby, K. J., Weir, M. H., Yetka, K., Thompson, H. M., Keeling, D., Mitchell, J., & González, D. (2020) · Water Research · doi:10.1016/j.watres.2020.116296 · Cited by 443

Osteoclasts recycle via osteomorphs during RANKL-stimulated bone resorption

McDonald, M. M., Khoo, W. H., Ng, P. Y., Xiao, Y., Zamerli, J., Thatcher, P., Kyaw, W., Pathmanandavel, K., Grootveld, A. K., Moran, I., et al. (2021) · Cell · doi:10.1016/j.cell.2021.02.002 · Cited by 433

Land-use intensity alters networks between biodiversity, ecosystem functions, and services

Felipe‐Lucia, M. R., Soliveres, S., Penone, C., Fischer, M., Ammer, C., Boch, S., Boeddinghaus, R. S., Bonkowski, M., Buscot, F., Fiore‐Donno, A. M., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2016210117 · Cited by 453

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

Seethepalli, A., Dhakal, K., Griffiths, M., Guo, H., Freschet, G. T., & York, L. M. (2021) · AoB Plants · doi:10.1093/aobpla/plab056 · Cited by 436

BioTIME: A database of biodiversity time series for the Anthropocene

Dornelas, M., Antão, L. H., Moyes, F., Bates, A. E., Magurran, A. E., Adam, D., Ахметжанова, А. А., Appeltans, W., Arcos, J. M., Arnold, H., et al. (2018) · Global Ecology and Biogeography · doi:10.1111/geb.12729 · Cited by 418

Resting energy expenditure, calorie and protein consumption in critically ill patients: a retrospective cohort study

Zusman, O., Theilla, M., Cohen, J., Kagan, I., Bendavid, I., & Singer, P. (2016) · Critical Care · doi:10.1186/s13054-016-1538-4 · Cited by 421

A multidimensional systems biology analysis of cellular senescence in aging and disease

Avelar, R. A., Ortega, J. G., Tacutu, R., Tyler, E. J., Bennett, D., Binetti, P., Budovsky, A., Chatsirisupachai, K., Johnson, E., Murray, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-01990-9 · Cited by 399

Similar neural responses predict friendship

Parkinson, C., Kleinbaum, A. M., & Wheatley, T. (2018) · Nature Communications · doi:10.1038/s41467-017-02722-7 · Cited by 388

OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units

Westcott, S. L., & Schloss, P. D. (2017) · mSphere · doi:10.1128/mspheredirect.00073-17 · Cited by 428

Effects of manure fertilizer on crop yield and soil properties in China: A meta-analysis

Du, Y., Cui, B., Zhang, Q., Wang, Z., Sun, J., & Niu, W. (2020) · CATENA · doi:10.1016/j.catena.2020.104617 · Cited by 440

MGIDI: toward an effective multivariate selection in biological experiments

Olivoto, T., & Nardino, M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa981 · Cited by 420

Plastic recycling in a circular economy; determining environmental performance through an LCA matrix model approach

Schwarz, A., Ligthart, T. N., Bizarro, D. E. G., de Wild, P. J., Vreugdenhil, B. J., & van Harmelen, T. (2021) · Waste Management · doi:10.1016/j.wasman.2020.12.020 · Cited by 448

PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R

Grau, J., Große, I., & Keilwagen, J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv153 · Cited by 401

Long-term forest soil warming alters microbial communities in temperate forest soils

DeAngelis, K. M., Pold, G., TopçuoÄŸlu, B. D., van Diepen, L. T. A., Varney, R., Blanchard, J. L., Melillo, J. M., & Frey, S. D. (2015) · Frontiers in Microbiology · doi:10.3389/fmicb.2015.00104 · Cited by 425

The Role of m6A/m-RNA Methylation in Stress Response Regulation

Engel, M., Eggert, C., Kaplick, P. M., Eder, M., Röh, S., Tietze, L., Namendorf, C., Arloth, J., Weber, P., Rex-Haffner, M., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.07.009 · Cited by 411

The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing

Barry, G., Briggs, J. A., Vanichkina, D. P., Poth, E. M., Beveridge, N. J., Ratnu, V. S., Nayler, S. P., Nones, K., Hu, J., Bredy, T. W., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.45 · Cited by 394

Driving forces of soil bacterial community structure, diversity, and function in temperate grasslands and forests

Kaiser, K., Wemheuer, B., Korolkow, V., Wemheuer, F., Nacke, H., Schöning, I., Schrumpf, M., & Daniel, R. (2016) · Scientific Reports · doi:10.1038/srep33696 · Cited by 416

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

McFarland, J. M., Ho, Z. V., Kugener, G., Dempster, J. M., Montgomery, P. G., Bryan, J. G., Krill-Burger, J., Green, T. M., Vazquez, F., Boehm, J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06916-5 · Cited by 348

Microplastics in marine biota: A review

Ugwu, K., Herrera, A., & Gómez, M. (2021) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2021.112540 · Cited by 416

A room with a green view: the importance of nearby nature for mental health during the COVID-19 pandemic

Soga, M., Evans, M. J., Tsuchiya, K., & Fukano, Y. (2021) · Ecological Applications · doi:10.1002/eap.2248 · Cited by 389

What’s normal? Oligosaccharide concentrations and profiles in milk produced by healthy women vary geographically ,

McGuire, M. K., Meehan, C. L., McGuire, M. A., Williams, J. E., Foster, J., Sellen, D., Kamau‐Mbuthia, E. W., Kamundia, E. W., Mbugua, S., Moore, S. E., et al. (2017) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.139980 · Cited by 405

Bacterial biogeography of the human digestive tract

Stearns, J. C., Lynch, M. D. J., Senadheera, D. B., Tenenbaum, H. C., Goldberg, M. B., Cvitkovitch, D. G., Croitoru, K., Moreno‐Hagelsieb, G., & Neufeld, J. D. (2011) · Scientific Reports · doi:10.1038/srep00170 · Cited by 411

Regional variability of imaging biomarkers in autosomal dominant Alzheimer's disease

Benzinger, T. L. S., Blazey, T., Jack, C. R., Koeppe, R. A., Su, Y., Xiong, C., Raichle, M. E., Snyder, A. Z., Ances, B. M., Bateman, R. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317918110 · Cited by 391

Defining Stem Cell Dynamics in Models of Intestinal Tumor Initiation

Vermeulen, L., Morrissey, E. R., van der Heijden, M., Nicholson, A. M., Sottoriva, A., Buczacki, S. J. A., Kemp, R., Tavaré, S., & Winton, D. J. (2013) · Science · doi:10.1126/science.1243148 · Cited by 404

STRUCTURE PLOT: a program for drawing elegant STRUCTURE bar plots in user friendly interface

Ramasamy, R. K., Ramasamy, S., Bindroo, B. B., & Naik, V. G. (2014) · SpringerPlus · doi:10.1186/2193-1801-3-431 · Cited by 397

Cytoplasmic protein aggregates interfere with nucleocytoplasmic transport of protein and RNA

Woerner, A. C., Frottin, F., Hornburg, D., Feng, L., Meissner, F., Patra, M., Tatzelt, J., Mann, M., Winklhofer, K. F., Hartl, F. U., et al. (2015) · Science · doi:10.1126/science.aad2033 · Cited by 406

Genomic Selection in Plant Breeding

Newell, M. A., & Jannink, J. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-0446-4_10 · Cited by 413

Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women

Callahan, B. J., DiGiulio, D. B., Goltsman, D. S. A., Sun, C. L., Costello, E. K., Jeganathan, P., Biggio, J. R., Wong, R. J., Druzin, M. L., Shaw, G. M., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705899114 · Cited by 391

Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits

Pérez‐Jaramillo, J. E., Carrión, V. J., Bosse, M., Ferrão, L. F. V., de Hollander, M., Garcia, A. A. F., Ramírez, C. A., Mendes, R., & Raaijmakers, J. M. (2017) · The ISME Journal · doi:10.1038/ismej.2017.85 · Cited by 392

Handling Complex Meta-analytic Data Structures Using Robust Variance Estimates: a Tutorial in R

Tanner-Smith, E. E., Tipton, E., & Polanin, J. R. (2016) · Journal of Developmental and Life-Course Criminology · doi:10.1007/s40865-016-0026-5 · Cited by 390

Climate change fingerprints in recent European plant phenology

Menzel, A., Yuan, Y., Matiu, M., Sparks, T. H., Scheifinger, H., Gehrig, R., & Estrella, N. (2020) · Global Change Biology · doi:10.1111/gcb.15000 · Cited by 415

plotROC: A Tool for Plotting ROC Curves

Sachs, M. C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v079.c02 · Cited by 391

R in action: data analysis and graphics with R

Kabacoff, R. I. (2011) · doi:10.5281/zenodo.13513756 · Cited by 381

Drivers of change in estuarine‐coastal ecosystems: Discoveries from four decades of study in San Francisco Bay

Cloern, J. E., & Jassby, A. D. (2012) · Reviews of Geophysics · doi:10.1029/2012rg000397 · Cited by 391

Four Key Steps Control Glycolytic Flux in Mammalian Cells

Tanner, L. B., Goglia, A. G., Wei, M. H., Sehgal, T., Parsons, L. R., Park, J. O., White, E., Toettcher, J. E., & Rabinowitz, J. D. (2018) · Cell Systems · doi:10.1016/j.cels.2018.06.003 · Cited by 383

Helminth Colonization Is Associated with Increased Diversity of the Gut Microbiota

Lee, S. C., Tang, M. S., Lim, Y. A. L., Choy, S. H., Kurtz, Z. D., Cox, L. M., Gundra, U. M., Cho, I., Bonneau, R., Blaser, M. J., et al. (2014) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0002880 · Cited by 394

Modeling microbial abundances and dysbiosis with beta-binomial regression

Martin, B. D., Witten, D., & Willis, A. D. (2020) · The Annals of Applied Statistics · doi:10.1214/19-aoas1283 · Cited by 379

Metabolic and metagenomic outcomes from early-life pulsed antibiotic treatment

Nobel, Y. R., Cox, L. M., Kirigin, F. F., Bokulich, N. A., Yamanishi, S., Teitler, I., Chung, J., Sohn, J., Barber, C. M., Goldfarb, D. S., et al. (2015) · Nature Communications · doi:10.1038/ncomms8486 · Cited by 389

Characterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery

Greater Middle East Variome Consortium, Scott, E. M., Halees, A., Itan, Y., Spencer, E. G., He, Y., Azab, M. A., Gabriel, S. B., Belkadi, A., Boisson, B., et al. (2016) · Nature Genetics · doi:10.1038/ng.3592 · Cited by 376

Scientific literature analysis on big data and internet of things applications on circular economy: A bibliometric study

Nobre, G. C., & Tavares, E. (2017) · Scientometrics · doi:10.1007/s11192-017-2281-6 · Cited by 375

Identification of Enteroendocrine Regulators by Real-Time Single-Cell Differentiation Mapping

Gehart, H., van Es, J. H., Hamer, K., Beumer, J., Kretzschmar, K., Dekkers, J. F., Rios, A., & Clevers, H. (2019) · Cell · doi:10.1016/j.cell.2018.12.029 · Cited by 346

Carbon pools recover more quickly than plant biodiversity in tropical secondary forests

Martin, P. A., Newton, A. C., & Bullock, J. M. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2013.2236 · Cited by 383

Comprehensive identification of RNA–protein interactions in any organism using orthogonal organic phase separation (OOPS)

Queiroz, R. M. L., Smith, T. S., Villanueva, E., Monti, M., Pizzinga, M., Martí-Solano, M., Mirea, D.-M., Ramakrishna, M., Harvey, R. F., Dezi, V., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-018-0001-2 · Cited by 367

PlantCV v2: Image analysis software for high-throughput plant phenotyping

Gehan, M. A., Fahlgren, N., Abbasi, A., Berry, J. C., Callen, S. T., Chavez, L., Doust, A. N., Feldman, M. J., Gilbert, K. B., Hodge, J. G., et al. (2017) · PeerJ · doi:10.7717/peerj.4088 · Cited by 379

Transport of microplastics by two collembolan species

Maaß, S., Daphi, D., Lehmann, A., & Rillig, M. C. (2017) · Environmental Pollution · doi:10.1016/j.envpol.2017.03.009 · Cited by 384

Circulating Nucleic Acids Are Associated With Outcomes of Patients With Pancreatic Cancer

Bernard, V., Kim, D. U., Lucas, F. A. S., Castillo, J., Allenson, K., Mulu, F. C., Stephens, B. M., Huang, J. H., Semaan, A., Guerrero, P. A., et al. (2018) · Gastroenterology · doi:10.1053/j.gastro.2018.09.022 · Cited by 364

ggtreeExtra: Compact Visualization of Richly Annotated Phylogenetic Data

Xu, S., Dai, Z., Guo, P., Fu, X., Liu, S., Zhou, L., Tang, W., Feng, T., Chen, M., Zhan, L., et al. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab166 · Cited by 364

Cryo-EM Structures of SARS-CoV-2 Spike without and with ACE2 Reveal a pH-Dependent Switch to Mediate Endosomal Positioning of Receptor-Binding Domains

Zhou, T., Tsybovsky, Y., Gorman, J., Rapp, M., Cerutti, G., Chuang, G., Katsamba, P. S., Sampson, J. M., Schön, A., Bimela, J. S., et al. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.11.004 · Cited by 345

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19

Ziegler, C. G. K., Miao, V. N., Owings, A. H., Navia, A. W., Tang, Y., Bromley, J. D., Lotfy, P., Sloan, M., Laird, H., Williams, H. B., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.023 · Cited by 358

Gene expression and functional deficits underlie TREM2-knockout microglia responses in human models of Alzheimer’s disease

McQuade, A., Kang, Y. J., Hasselmann, J., Jairaman, A., Sotelo, A., Coburn, M., Shabestari, S. K., Chadarevian, J. P., Fote, G., Tu, C. H., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19227-5 · Cited by 361

Host-Protozoan Interactions Protect from Mucosal Infections through Activation of the Inflammasome

Chudnovskiy, A., Mortha, A., Kana, V., Kennard, A., Ramirez, J. D., Rahman, A., Remark, R., Mogno, I., Ng, R., Gnjatic, S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.076 · Cited by 325

Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches

Nearing, J. T., Douglas, G. M., Comeau, A., & Langille, M. G. I. (2018) · PeerJ · doi:10.7717/peerj.5364 · Cited by 368

A primer of acoustic analysis for landscape ecologists

Villanueva-Rivera, L. J., Pijanowski, B. C., Doucette, J. S., & Pekin, B. K. (2011) · Landscape Ecology · doi:10.1007/s10980-011-9636-9 · Cited by 357

Autism-related dietary preferences mediate autism-gut microbiome associations

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Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries

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ggplot2

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Graphs with ggplot2

Ryan, C. (2021) · CRC Press eBooks · doi:10.1201/9781003106845-12

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Visualization with ggplot2

Paul, A. (2025) · Chapman & Hall/CRC eBooks · doi:10.1201/9781003423386-8