ggplot2: Elegant Graphics for Data Analysis

Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy

Freeman, K., Geppert, J., Stinton, C., Todkill, D., Johnson, S. A., Clarke, A., & Taylor‐Phillips, S. (2021) · BMJ · doi:10.1136/bmj.n1872 · Cited by 365

Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs

Mizrahi-Man, O., Davenport, E., & Gilad, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0053608 · Cited by 364

Estimating the Stability of Psychological Dimensions via Bootstrap Exploratory Graph Analysis: A Monte Carlo Simulation and Tutorial

Christensen, A. P., & Golino, H. F. (2021) · Psych · doi:10.3390/psych3030032 · Cited by 386

Microplastic contamination of drinking water: A systematic review

Danopoulos, E., Twiddy, M., & Rotchell, J. M. (2020) · PLOS ONE · doi:10.1371/journal.pone.0236838 · Cited by 341

Single-Molecule Imaging Reveals Translation of mRNAs Localized to Stress Granules

Matějů, D., Eichenberger, B., Voigt, F., Eglinger, J., Roth, G., & Chao, J. A. (2020) · Cell · doi:10.1016/j.cell.2020.11.010 · Cited by 341

LC3-Associated Phagocytosis in Myeloid Cells Promotes Tumor Immune Tolerance

Cunha, L. D., Yang, M., Carter, R., Guy, C., Harris, L., Crawford, J. C., Quarato, G., Boada-Romero, E., Kalkavan, H., Johnson, M. D. L., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.061 · Cited by 334

Microglial NF-κB drives tau spreading and toxicity in a mouse model of tauopathy

Wang, C., Fan, L., Khawaja, R. R., Liu, B., Zhan, L., Kodama, L., Chin, M., Li, Y., Le, D., Zhou, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29552-6 · Cited by 333

Genomic RNA Elements Drive Phase Separation of the SARS-CoV-2 Nucleocapsid

Iserman, C., Roden, C., Boerneke, M. A., Sealfon, R. S. G., McLaughlin, G. A., Jungreis, I., Fritch, E. J., Hou, Y. J., Ekena, J., Weidmann, C. A., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.11.041 · Cited by 377

Risk of Major Adverse Cardiac Events Following Noncardiac Surgery in Patients With Coronary Stents

Hawn, M. T., Graham, L. A., Richman, J., Itani, K. M. F., Henderson, W. G., & Maddox, T. M. (2013) · JAMA · doi:10.1001/jama.2013.278787 · Cited by 339

A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2

Islam, R., Parves, M. R., Paul, A. S., Uddin, N., Rahman, M. S., Mamun, A. A., Hossain, M. N., Ali, M., & Halim, M. A. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1761883 · Cited by 339

Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response

HIPSCI Consortium, Alasoo, K., Rodrigues, J., Mukhopadhyay, S., Knights, A. J., Mann, A. L., Kundu, K., Hale, C., Dougan, G., & Gaffney, D. J. (2018) · Nature Genetics · doi:10.1038/s41588-018-0046-7 · Cited by 338

Concentrations of perfluoroalkyl substances (PFASs) in human embryonic and fetal organs from first, second, and third trimester pregnancies

Mamsen, L. S., Björvang, R. D., Mucs, D., Vinnars, M.-T., Papadogiannakis, N., Lindh, C. H., Andersen, C. Y., & Damdimopoulou, P. (2019) · Environment International · doi:10.1016/j.envint.2019.01.010 · Cited by 338

Self-Organizing 3D Human Trunk Neuromuscular Organoids

Martins, J.-M. F., Fischer, C., Urzi, A., Vidal, R. O., Kunz, S., Ruffault, P.-L., Kabuss, L., Hube, I., Gazzerro, E., Birchmeier, C., et al. (2020) · Cell stem cell · doi:10.1016/j.stem.2019.12.007 · Cited by 339

GenVisR: Genomic Visualizations in R

Skidmore, Z. L., Wagner, A. H., Lesurf, R., Campbell, K. M., Kunisaki, J., Griffith, O. L., & Griffith, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw325 · Cited by 338

Genomic surveillance for hypervirulence and multi-drug resistance in invasive Klebsiella pneumoniae from South and Southeast Asia

Wyres, K. L., Nguyen, T. N. T., Lam, M. M. C., Judd, L. M., Châu, N. V. V., Dance, D. A. B., Ip, M., Karkey, A., Ling, C. L., Miliya, T., et al. (2020) · Genome Medicine · doi:10.1186/s13073-019-0706-y · Cited by 324

Peri‐implant soft tissue phenotype modification and its impact on peri‐implant health: A systematic review and network meta‐analysis

Tavelli, L., Barootchi, S., Ávila‐Ortiz, G., Urbán, I., Giannobile, W. V., & Wang, H. (2020) · Journal of Periodontology · doi:10.1002/jper.19-0716 · Cited by 383

The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis

Wijnenga, M. M. J., French, P. J., Dubbink, H. J., Dinjens, W. N. M., Atmodimedjo, P. N., Kros, J. M., Smits, M., Gahrmann, R., Rutten, G.-J. M., Verheul, J. B., et al. (2017) · Neuro-Oncology · doi:10.1093/neuonc/nox176 · Cited by 345

The citation advantage of linking publications to research data

Colavizza, G., Hrynaszkiewicz, I., Staden, I., Whitaker, K., & McGillivray, B. (2020) · PLOS ONE · doi:10.1371/journal.pone.0230416 · Cited by 335

mdatools – R package for chemometrics

Kucheryavskiy, S. (2020) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2020.103937 · Cited by 335

Cancer-Associated Protein Kinase C Mutations Reveal Kinase’s Role as Tumor Suppressor

Antal, C. E., Hudson, A., Kang, E., Zanca, C., Wirth, C., Stephenson, N. L., Trotter, E. W., Gallegos, L. L., Miller, C. J., Furnari, F. B., et al. (2015) · Cell · doi:10.1016/j.cell.2015.01.001 · Cited by 331

Interactome Maps of Mouse Gene Regulatory Domains Reveal Basic Principles of Transcriptional Regulation

Kieffer-Kwon, K.-R., Tang, Z., Mathé, E. A., Qian, J., Sung, M., Li, G., Resch, W., Baek, S., Pruett, N. D., Grøntved, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.11.039 · Cited by 337

Coral bacterial community structure responds to environmental change in a host-specific manner

Ziegler, M., Grupstra, C. G. B., Barreto, M. M., Eaton, M., BaOmar, J., Zubier, K. M., Al-Sofyani, A., Turki, A. J., Ormond, R., & Voolstra, C. R. (2019) · Nature Communications · doi:10.1038/s41467-019-10969-5 · Cited by 330

Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE

Ayton, S., Faux, N. G., Bush, A. I., Initiative, A. D. N., Weiner, M. W., Aisen, P. S. S., Petersen, R. C., Jack, C. R., Jagust, W., Trojanowki, J. Q., et al. (2015) · Nature Communications · doi:10.1038/ncomms7760 · Cited by 359

Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology

Ewart, L., Apostolou, A., Briggs, S. A., Carman, C. V., Chaff, J. T., Heng, A. R., Jadalannagari, S., Janardhanan, J., Jang, K.-J., Joshipura, S. R., et al. (2022) · Communications Medicine · doi:10.1038/s43856-022-00209-1 · Cited by 337

Clinical and economic burden of surgical site infection (SSI) and predicted financial consequences of elimination of SSI from an English hospital

Jenks, P. J., Laurent, M., McQuarry, S., & Watkins, R. (2013) · Journal of Hospital Infection · doi:10.1016/j.jhin.2013.09.012 · Cited by 329

Engineering an allosteric transcription factor to respond to new ligands

Taylor, N. D., Garruss, A. S., Moretti, R., Chan, S., Arbing, M. A., Cascio, D., Rogers, J. K., Isaacs, F. J., Kosuri, S., Baker, D., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3696 · Cited by 328

Natural soil microbes alter flowering phenology and the intensity of selection on flowering time in a wild Arabidopsis relative

Wagner, M. R., Lundberg, D. S., Coleman‐Derr, D., Tringe, S. G., Dangl, J. L., & Mitchell‐Olds, T. (2014) · Ecology Letters · doi:10.1111/ele.12276 · Cited by 334

An investigation into per- and polyfluoroalkyl substances (PFAS) in nineteen Australian wastewater treatment plants (WWTPs)

Coggan, T. L., Moodie, D., Kolobaric, A., Szabo, D., Shimeta, J., Crosbie, N. D., Lee, E., Fernandes, M., & Clarke, B. O. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e02316 · Cited by 327

Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments

Karstens, L., Asquith, M. J., Davin, S., Fair, D. A., Gregory, W. T., Wolfe, A. J., Braun, J. G., & McWeeney, S. K. (2019) · mSystems · doi:10.1128/msystems.00290-19 · Cited by 343

Commensal microbiota regulates skin barrier function and repair via signaling through the aryl hydrocarbon receptor

Uberoi, A., Bartow‐McKenney, C., Zheng, Q., Flowers, L. J., Campbell, A. E., Knight, S. A. B., Chan, N., Wei, M. H., Lovins, V. M., Bugayev, J., et al. (2021) · Cell Host & Microbe · doi:10.1016/j.chom.2021.05.011 · Cited by 328

Omalizumab facilitates rapid oral desensitization for peanut allergy

MacGinnitie, A. J., Rachid, R. A., Gragg, H., Little, S. V., Lakin, P. R., Cianferoni, A., Heimall, J. R., Makhija, M., Robison, R. G., Chinthrajah, R. S., et al. (2016) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2016.08.010 · Cited by 325

Dynamic changes in glioma macrophage populations after radiotherapy reveal CSF-1R inhibition as a strategy to overcome resistance

Akkari, L., Bowman, R. L., Tessier, J., Klemm, F., Handgraaf, S. M., de Groot, M. H. P., Quail, D. F., Tillard, L., Gadiot, J., Huse, J. T., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aaw7843 · Cited by 317

The Q Exactive HF, a Benchtop Mass Spectrometer with a Pre-filter, High-performance Quadrupole and an Ultra-high-field Orbitrap Analyzer

Scheltema, R. A., Hauschild, J.-P., Lange, O., Hornburg, D., Denisov, E. V., Damoc, E., Kuehn, A., Makarov, A., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.043489 · Cited by 337

Identification of a Nuclear Exosome Decay Pathway for Processed Transcripts

Meola, N., Domanski, M., Karadoulama, E., Chen, Y., Gentil, C., Pultz, D., Vitting-Seerup, K., Lykke-Andersen, S., Andersen, J. S., Sandelin, A., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.09.025 · Cited by 290

Host species identity, site and time drive temperate tree phyllosphere bacterial community structure

Laforest‐Lapointe, I., Messier, C., & Kembel, S. W. (2016) · Microbiome · doi:10.1186/s40168-016-0174-1 · Cited by 329

Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests

Mahé, F., de Vargas, C., Bass, D., Czech, L., Stamatakis, A., Lara, E., Singer, D., Mayor, J. R., Bunge, J., Sernaker, S., et al. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0091 · Cited by 323

Monoterpenes Support Systemic Acquired Resistance within and between Plants

Riedlmeier, M., Ghirardo, A., Wenig, M., Knappe, C., Koch, K., Georgii, E., Dey, S., Parker, J. E., Schnitzler, J.-P., & Vlot, A. C. (2017) · The Plant Cell · doi:10.1105/tpc.16.00898 · Cited by 323

Nitrogen and phosphorus fertilization consistently favor pathogenic over mutualistic fungi in grassland soils

Lekberg, Y., Arnillas, C. A., Borer, E. T., Bullington, L. S., Fierer, N., Kennedy, P. G., Leff, J., Luis, A. D., Seabloom, E. W., & Henning, J. A. (2021) · Nature Communications · doi:10.1038/s41467-021-23605-y · Cited by 346

Vascular transcription factors guide plant epidermal responses to limiting phosphate conditions

Wendrich, J. R., Yang, B., Vandamme, N., Verstaen, K., Smet, W., de Velde, C. V., Minne, M., Wybouw, B., Mor, E., Arents, H. E., et al. (2020) · Science · doi:10.1126/science.aay4970 · Cited by 327

Standardization of terminology in dermoscopy/dermatoscopy: Results of the third consensus conference of the International Society of Dermoscopy

Kittler, H., Marghoob, A. A., Argenziano, G., Carrera, C., Curiel‐Lewandrowski, C. N., Hofmann‐Wellenhof, R., Malvehy, J., Menzies, S. W., Puig, S., Rabinovitz, H. S., et al. (2016) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2015.12.038 · Cited by 336

Prevalence of post-traumatic stress disorder symptoms in adult critical care survivors: a systematic review and meta-analysis

Righy, C., Rosa, R. G., da Silva, R. T. A., Kochhann, R., Migliavaca, C. B., Robinson, C. C., Teche, S. P., Teixeira, C., Bozza, F. A., & Falavigna, M. (2019) · Critical Care · doi:10.1186/s13054-019-2489-3 · Cited by 319

Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database

Zappia, L., Phipson, B., & Oshlack, A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006245 · Cited by 319

Dream: powerful differential expression analysis for repeated measures designs

Hoffman, G. E., & Roussos, P. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btaa687 · Cited by 319

Quantifying Wikipedia Usage Patterns Before Stock Market Moves

Moat, H., Curme, C., Avakian, A., Kenett, D., Stanley, H. E., & Preis, T. (2013) · Scientific Reports · doi:10.1038/srep01801 · Cited by 336

Treatment outcomes of childhood tuberculous meningitis: a systematic review and meta-analysis

Chiang, S. S., Khan, F. A., Milstein, M. B., Tolman, A. W., Benedetti, A., Starke, J. R., & Becerra, M. C. (2014) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(14)70852-7 · Cited by 324

Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico

Vågene‬, Å. J., Herbig, A., Campana, M. G., García, N. M. R., Warinner, C., Sabin, S. J., Spyrou, M. A., Valtueña, A. A., Huson, D. H., Tuross, N., et al. (2018) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0446-6 · Cited by 324

Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco

Moritz, D., Wang, C., Nelson, G. L., Lin, H., Smith, A. M., Howe, B., & Heer, J. (2018) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2865240 · Cited by 317

Learning What Not to Say: The Role of Statistical Preemption and Categorization in A -Adjective Production

Boyd, J. K., & Goldberg, A. E. (2011) · Language · doi:10.1353/lan.2011.0012 · Cited by 311

Major role of nitrite-oxidizing bacteria in dark ocean carbon fixation

Pachiadaki, M., Sintes, E., Bergauer, K., Brown, J. M., Record, N. R., Swan, B. K., Mathyer, M. E., Hallam, S., López‐García, P., Takaki, Y., et al. (2017) · Science · doi:10.1126/science.aan8260 · Cited by 317

Target Capture and Massively Parallel Sequencing of Ultraconserved Elements for Comparative Studies at Shallow Evolutionary Time Scales

Smith, B. T., Harvey, M. G., Faircloth, B. C., Glenn, T. C., & Brumfield, R. T. (2013) · Systematic Biology · doi:10.1093/sysbio/syt061 · Cited by 316

A Genome-wide Map of CTCF Multivalency Redefines the CTCF Code

Nakahashi, H., Kieffer, K.-R., Resch, W., Vian, L., Dose, M., Stavreva, D. A., Hakim, O., Pruett, N. D., Nelson, S., Yamane, A., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.04.024 · Cited by 306

Pathogenic tau-induced piRNA depletion promotes neuronal death through transposable element dysregulation in neurodegenerative tauopathies

Sun, W., Samimi, H., Gamez, M., Zare, H., & Frost, B. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0194-1 · Cited by 300

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

Alexander‐Bloch, A. F., Vértes, P. E., Stidd, R., Lalonde, F. M., CLASEN, L. S., Rapoport, J. L., Giedd, J. N., Bullmore, E. T., & Gogtay, N. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr388 · Cited by 319

ECharts: A declarative framework for rapid construction of web-based visualization

Li, D., Mei, H., Shen, Y., Su, S., Zhang, W., Wang, J., Zu, M., & Chen, W. (2018) · Visual Informatics · doi:10.1016/j.visinf.2018.04.011 · Cited by 315

Biology and Taxonomy of crAss-like Bacteriophages, the Most Abundant Virus in the Human Gut

Guerin, E., Shkoporov, A. N., Stockdale, S. R., Clooney, A. G., Ryan, F. J., Sutton, T., Draper, L. A., González-Tortuero, E., Ross, R. P., & Hill, C. (2018) · Cell Host & Microbe · doi:10.1016/j.chom.2018.10.002 · Cited by 307

Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias.

Rodebaugh, T. L., Scullin, R. B., Langer, J. K., Dixon, D. J., Huppert, J. D., Bernstein, A., Zvielli, A., & Lenze, E. J. (2016) · Journal of Abnormal Psychology · doi:10.1037/abn0000184 · Cited by 312

Sewage Reflects the Microbiomes of Human Populations

Newton, R. J., McLellan, S. L., Dila, D. K., Vineis, J. H., Morrison, H. G., Eren, A. M., & Sogin, M. L. (2015) · mBio · doi:10.1128/mbio.02574-14 · Cited by 299

Longitudinal four-dimensional mapping of subcortical anatomy in human development

Raznahan, A., Shaw, P. W., Lerch, J. P., Clasen, L. S., Greenstein, D., Berman, R., Pipitone, J., Chakravarty, M. M., & Giedd, J. N. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316911111 · Cited by 312

Indole-3-lactic acid associated with Bifidobacterium-dominated microbiota significantly decreases inflammation in intestinal epithelial cells

Ehrlich, A. M., Pacheco, A. R., Henrick, B. M., Taft, D. H., Xu, G., Huda, M. N., Mishchuk, D. O., Goodson, M. L., Slupsky, C. M., Barile, D., et al. (2020) · BMC Microbiology · doi:10.1186/s12866-020-02023-y · Cited by 326

Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology

Taylor, S. L., Leong, L. E. X., Choo, J. M., Wesselingh, S., Yang, I. A., Upham, J. W., Reynolds, P. N., Hodge, S., James, A. L., Jenkins, C., et al. (2018) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2017.03.044 · Cited by 314

Animal to human translation: a systematic scoping review of reported concordance rates

Leenaars, C. H. C., Kouwenaar, C., Stafleu, F. R., Bleich, A., Ritskes-Hoitinga, M., De Vries, R. B. M., & Meijboom, F. L. B. (2019) · Journal of Translational Medicine · doi:10.1186/s12967-019-1976-2 · Cited by 314

Bacteroides dorei dominates gut microbiome prior to autoimmunity in Finnish children at high risk for type 1 diabetes

Davis‐Richardson, A. G., Ardissone, A. N., Dias, R., Simell, V., Leonard, M. T., Kemppainen, K. M., Drew, J. C., Schatz, D., Atkinson, M. A., Kolaczkowski, B., et al. (2014) · Frontiers in Microbiology · doi:10.3389/fmicb.2014.00678 · Cited by 316

Mitochondrial metabolism coordinates stage-specific repair processes in macrophages during wound healing

Willenborg, S., Sanin, D. E., Jais, A., Ding, X., Ulas, T., Nüchel, J., Popović, M., MacVicar, T., Langer, T., Schultze, J. L., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.10.004 · Cited by 310

Metabolic flexibility determines human NK cell functional fate in the tumor microenvironment

Poznanski, S. M., Singh, K., Ritchie, T. M., Aguiar, J. A., Fan, I. Y., Portillo, A. L., Rojas, E. A. P., Vahedi, F., El‐Sayes, A., Xing, S., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.03.023 · Cited by 309

Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation

Clark, M. M., Hildreth, A., Batalov, S., Ding, Y., Chowdhury, S., Watkins, K., Ellsworth, K., Camp, B., Kint, C. I., Yacoubian, C., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aat6177 · Cited by 300

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning

Mason, D. M., Friedensohn, S., Weber, C. R., Jordi, C., Wagner, B., Meng, S. M., Ehling, R. A., Bonati, L., Dahinden, J., Gainza, P., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00699-9 · Cited by 308

ggbio: an R package for extending the grammar of graphics for genomic data

Yin, T., Cook, D., & Lawrence, M. (2012) · Genome biology · doi:10.1186/gb-2012-13-8-r77 · Cited by 303

The Chromosome-Level Genome Sequence of the Autotetraploid Alfalfa and Resequencing of Core Germplasms Provide Genomic Resources for Alfalfa Research

Shen, C., Du, H., Chen, Z., Lu, H., Zhu, F., Chen, H., Meng, X., Liu, Q., Liu, P., Zheng, L., et al. (2020) · Molecular Plant · doi:10.1016/j.molp.2020.07.003 · Cited by 311

Triglycerides Promote Lipid Homeostasis during Hypoxic Stress by Balancing Fatty Acid Saturation

Ackerman, D., Tumanov, S., Qiu, B., Michalopoulou, E., Spata, M., Azzam, A., Xie, H. J., Simon, M. C., & Kamphorst, J. J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.08.015 · Cited by 307

A spatio-temporal analysis for exploring the effect of temperature on COVID-19 early evolution in Spain

Briz‐Redón, Á., & Serrano‐Aroca, Á. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.138811 · Cited by 303

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

Rellán‐Álvarez, R., Lobet, G., Lindner, H., Pradier, P., Sebastián, J., Yee, M., Geng, Y., Trontin, C., LaRue, T., Schrager‐Lavelle, A., et al. (2015) · eLife · doi:10.7554/elife.07597 · Cited by 306

CeNDR, the Caenorhabditis elegans natural diversity resource

Cook, D. E., Zdraljevic, S., Roberts, J. P., & Andersen, E. C. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw893 · Cited by 284

A Large Panel of Isogenic APP and PSEN1 Mutant Human iPSC Neurons Reveals Shared Endosomal Abnormalities Mediated by APP β-CTFs, Not Aβ

Kwart, D., Gregg, A., Scheckel, C., Murphy, E. A., Paquet, D., Duffield, M. D., Fak, J. J., Olsen, O., Darnell, R. B., & Tessier‐Lavigne, M. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.010 · Cited by 327

Breastmilk Feeding Practices Are Associated with the Co-Occurrence of Bacteria in Mothers’ Milk and the Infant Gut: the CHILD Cohort Study

Fehr, K. B., Moossavi, S., Sbihi, H., Boutin, R. C. T., Bode, L., Robertson, B., Yonemitsu, C., Field, C. J., Becker, A. B., Mandhane, P. J., et al. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.06.009 · Cited by 316

Coronavirus conspiracy suspicions, general vaccine attitudes, trust and coronavirus information source as predictors of vaccine hesitancy among UK residents during the COVID-19 pandemic

Allington, D., McAndrew, S., Moxham-Hall, V. L., & Duffy, B. (2021) · Psychological Medicine · doi:10.1017/s0033291721001434 · Cited by 301

MEMBPLUGIN: studying membrane complexity in VMD

Guixà-González, R., Rodríguez‐Espigares, I., Ramírez‐Anguita, J. M., Carrió, P., Martinez‐Seara, H., Toni Giorgino, A., & Selent, J. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu037 · Cited by 300

Blobology: exploring raw genome data for contaminants, symbionts and parasites using taxon-annotated GC-coverage plots

Kumar, S., Jones, M., Koutsovoulos, G., Clarke, M., & Blaxter, M. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00237 · Cited by 300

A systematic evaluation of single-cell RNA-sequencing imputation methods

Hou, W., Ji, Z., Ji, H., & Hicks, S. C. (2020) · Genome biology · doi:10.1186/s13059-020-02132-x · Cited by 307

Adolescent friendships predict later resilient functioning across psychosocial domains in a healthy community cohort

van Harmelen, A.-L., Kievit, R. A., Ioannidis, K., Neufeld, S., Jones, P. B., Bullmore, E., Dolan, R., The NSPN Consortium, Fonagy, P., & Goodyer, I. (2017) · Psychological Medicine · doi:10.1017/s0033291717000836 · Cited by 284

Plant Extracellular Vesicles Contain Diverse Small RNA Species and Are Enriched in 10- to 17-Nucleotide “Tiny” RNAs

Baldrich, P., Rutter, B. D., Karimi, H. Z., Podicheti, R., Meyers, B. C., & Innes, R. W. (2019) · The Plant Cell · doi:10.1105/tpc.18.00872 · Cited by 299

Is Putin’s popularity real?

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Voyager 2

Wongsuphasawat, K., Qu, Z., Moritz, D., Chang, R., Ouk, F., Anand, A., Mackinlay, J. D., Howe, B., & Heer, J. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025768 · Cited by 292

Combined immune checkpoint blockade as a therapeutic strategy for BRCA1 -mutated breast cancer

Nolan, E., Savas, P. S., Policheni, A. N., Darcy, P. K., Vaillant, F., Mintoff, C., Dushyanthen, S., Mansour, M., Pang, J., Fox, S. B., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aal4922 · Cited by 297

Potential Impact of DSM-5 Criteria on Autism Spectrum Disorder Prevalence Estimates

Maenner, M. J., Rice, C. E., Arneson, C. L., Cunniff, C., Schieve, L. A., Carpenter, L. A., Van Naarden Braun, K., Kirby, R. S., Bakian, A. V., & Durkin, M. S. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.3893 · Cited by 292

Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders

Yang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290

KAMO : towards automated data processing for microcrystals

Yamashita, K., Hirata, K., & Yamamoto, M. (2018) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798318004576 · Cited by 292

The Human Skin Double-Stranded DNA Virome: Topographical and Temporal Diversity, Genetic Enrichment, and Dynamic Associations with the Host Microbiome

Hannigan, G. D., Meisel, J. S., Tyldsley, A. S., Zheng, Q., Hodkinson, B. P., SanMiguel, A. J., Minot, S. S., Bushman, F. D., & Grice, E. A. (2015) · mBio · doi:10.1128/mbio.01578-15 · Cited by 319

How self‐generated thought shapes mood–the relation between mind‐wandering and mood depends on the socio‐temporal content of thoughts

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NPC1 regulates ER contacts with endocytic organelles to mediate cholesterol egress

Höglinger, D., Burgoyne, T., Sanchez-Heras, E., Hartwig, P., Colaco, A., Newton, J., Futter, C. E., Spiegel, S., Platt, F. M., & Eden, E. R. (2019) · Nature Communications · doi:10.1038/s41467-019-12152-2 · Cited by 299

Transposable elements are the primary source of novelty in primate gene regulationPreprint

Trizzino, M., Park, Y., Beltrame, M. H., Aracena, K. A., Mika, K. M., Çalışkan, M., Perry, G. H., Lynch, V. J., & Brown, C. D. (2017) · Genome Research · doi:10.1101/gr.218149.116 · Cited by 286

Disentangling the mechanisms shaping the surface ocean microbiota

Logares, R., Deutschmann, I. M., Junger, P. C., Giner, C. R., Krabberød, A. K., Schmidt, T., Rubinat-Ripoll, L., Mestre, M., Salazar, G., Ruiz‐González, C., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00827-8 · Cited by 283

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

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Global trends in infectious diseases at the wildlife–livestock interface

Wiethoelter, A., Beltrán‐Alcrudo, D., Kock, R. A., & Mor, S. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422741112 · Cited by 310

Understanding the Average Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of Seven Randomized Experiments

Meager, R. (2019) · American Economic Journal Applied Economics · doi:10.1257/app.20170299 · Cited by 287

NeuralNetTools : Visualization and Analysis Tools for Neural Networks

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A flexible multiplexed immunosensor for point-of-care in situ wound monitoring

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Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

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A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria

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Advanced Morphological — Behavioral Test Platform Reveals Neurodevelopmental Defects in Embryonic Zebrafish Exposed to Comprehensive Suite of Halogenated and Organophosphate Flame Retardants

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ggplot2

Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4 · Cited by 34,873

Graphs with ggplot2

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

^DOWNLOAD E.B.O.O.K.# ggplot2: Elegant Graphics for Data Analysis (Use R!) Full PDF

PDF, ^. E. B. O. O. K. #. G. E. G. F. D. A. (. R. F. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4189363

DOWNLOAD in [PDF] ggplot2: Elegant Graphics for Data Analysis (Use R!) Full Pages

Pages, D. I. [. G. E. G. F. D. A. (. R. F. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4188991

Visualization with ggplot2

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