R: A Language and Environment for Statistical Computing

Effects of vineyard management on biodiversity at three trophic levels

Bruggisser, O. T., Schmidt-Entling, M. H., & Bacher, S. (2010) · Biological Conservation · doi:10.1016/j.biocon.2010.03.034 · Cited by 186

Ancient Clam Gardens Increased Shellfish Production: Adaptive Strategies from the Past Can Inform Food Security Today

Groesbeck, A. S., Rowell, K., Lepofsky, D., & Salomon, A. K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091235 · Cited by 184

Childhood maternal care is associated with DNA methylation of the genes for brain-derived neurotrophic factor ( BDNF ) and oxytocin receptor ( OXTR ) in peripheral blood cells in adult men and women

Unternaehrer, E., Meyer, A. H., Burkhardt, S. C. A., Dempster, E., Staehli, S., Theill, N., Lieb, R., & Meinlschmidt, G. (2015) · Stress · doi:10.3109/10253890.2015.1038992 · Cited by 181

Evolution combined with genomic study elucidates genetic bases of isobutanol tolerance in Escherichia coli

Minty, J. J., Lesnefsky, A. A., Lin, F., Chen, Y., Zaroff, T. A., Veloso, A. B., Xie, B., McConnell, C. A., Ward, R. J., Schwartz, D. R., et al. (2011) · Microbial Cell Factories · doi:10.1186/1475-2859-10-18 · Cited by 185

BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization

Corbin, L. J., Richmond, R. C., Wade, K. H., Burgess, S., Bowden, J., Smith, G. D., & Timpson, N. J. (2016) · Diabetes · doi:10.2337/db16-0418 · Cited by 184

A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

Greiff, V., Bhat, P., Cook, S. C., Menzel, U., Kang, W., & Reddy, S. T. (2015) · Genome Medicine · doi:10.1186/s13073-015-0169-8 · Cited by 181

Career adaptability and career success in the context of a broader career resources framework

Haenggli, M., & Hirschi, A. (2020) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2020.103414 · Cited by 185

Genome‐wide significant association between alcohol dependence and a variant in the ADH gene cluster

Frank, J., Cichon, S., Treutlein, J., Ridinger, M., Mattheisen, M., Hoffmann, P., Herms, S., Wodarz, N., Soyka, M., Zill, P., et al. (2012) · Addiction Biology · doi:10.1111/j.1369-1600.2011.00395.x · Cited by 176

Exposure to Disinfection By-products, Fetal Growth, and Prematurity: A Systematic Review and Meta-analysis

Grellier, J., Bennett, J., Patelarou, E., Smith, R. B., Toledano, M. B., Rushton, L., Briggs, D. J., & Nieuwenhuijsen, M. J. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181d61ffd · Cited by 184

Severity of OSA Is an Independent Predictor of Incident Atrial Fibrillation Hospitalization in a Large Sleep-Clinic Cohort

Cadby, G., McArdle, N., Briffa, T., Hillman, D. R., Simpson, L., Knuiman, M., & Hung, J. (2015) · Chest · doi:10.1378/chest.15-0229 · Cited by 184

The association of demoralization with mental disorders and suicidal ideation in patients with cancer

Vehling, S., Kissane, D. W., Lo, C., Glaesmer, H., Hartung, T. J., Rodin, G., & Mehnert, A. (2017) · Cancer · doi:10.1002/cncr.30749 · Cited by 182

Medium-term effects of corn biochar addition on soil biota activities and functions in a temperate soil cropped to corn

Domene, X., Mattana, S., Hanley, K., Enders, A., & Lehmann, J. (2014) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2014.01.035 · Cited by 184

Dynamic proteomics emphasizes the importance of selective mRNA translation and protein turnover during Arabidopsis seed germination.

Galland, M., Huguet, R., Arc, E., Cueff, G., Job, D., & Rajjou, L. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.032227 · Cited by 184

ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models

Marvel, S. W., To, K., Grimm, F. A., Wright, F. A., Rusyn, I., & Reif, D. M. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2089-2 · Cited by 184

Dysbiosis, gut barrier dysfunction and inflammation in dementia: a pilot study

Stadlbauer, V., Engertsberger, L., Komarova, I., Feldbacher, N., Leber, B., Pichler, G., Fink, N., Scarpatetti, M., Schippinger, W., Schmidt, R., et al. (2020) · BMC Geriatrics · doi:10.1186/s12877-020-01644-2 · Cited by 182

The emergence of longevous populations

Colchero, F., Rau, R., Jones, O. R., Barthold, J. A., Conde, D. A., Lenart, A., Nemeth, L., Scheuerlein, A., Schoeley, J., Torres, C., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1612191113 · Cited by 182

Cancer incidence in persons with type 1 diabetes: A five-country study of 9,000 cancers in type 1 diabetic individuals

on behalf of the Diabetes and Cancer Research Consortium, Carstensen, B., Read, S. H., Friis, S., Sund, R., Keskimäki, I., Svensson, A.-M., Ljung, R., Wild, S. H., Kerssens, J. J., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-3884-9 · Cited by 180

Contribution to Alzheimer's disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls

Bellenguez, C., Charbonnier, C., Grenier-Boley, B., Quenez, O., Le Guennec, K., Nicolas, G., Chauhan, G., Wallon, D., Rousseau, S., Richard, A. C., et al. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.07.001 · Cited by 166

Direct GR Binding Sites Potentiate Clusters of TF Binding across the Human Genome

Vockley, C. M., D’Ippolito, A. M., McDowell, I. C., Majoros, W. H., Safi, A., Song, L., Crawford, G. E., & Reddy, T. E. (2016) · Cell · doi:10.1016/j.cell.2016.07.049 · Cited by 182

Satellite observations document trends consistent with a boreal forest biome shift

Berner, L. T., & Goetz, S. J. (2022) · Global Change Biology · doi:10.1111/gcb.16121 · Cited by 182

Comparison of salivary cortisol as measured by different immunoassays and tandem mass spectrometry

Miller, R., Plessow, F., Rauh, M., Gröschl, M., & Kirschbaum, C. (2013) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2012.04.019 · Cited by 181

Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models

Cuevas, J., Crossa, J., Soberanis, V., Pérez‐Elizalde, S., Pérez‐Rodríguez, P., Campos, G. D. L., Montesinos‐López, O. A., & Burgueño, J. (2016) · The Plant Genome · doi:10.3835/plantgenome2016.03.0024 · Cited by 181

Autism traits in the RASopathies

Adviento, B., Corbin, I. L., Widjaja, F., Desachy, G., Enrique, N., Rosser, T., Risi, S., Marco, E. J., Hendren, R. L., Bearden, C. E., et al. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2013-101951 · Cited by 174

Are videoconferenced mental and behavioral health services just as good as in-person? A meta-analysis of a fast-growing practice

Batastini, A. B., Paprzycki, P., Jones, A. C. T., & MacLean, N. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101944 · Cited by 181

Mindfulness and Its Association With Varied Types of Motivation: A Systematic Review and Meta-Analysis Using Self-Determination Theory

Donald, J. N., Bradshaw, E. L., Ryan, R. M., Basarkod, G., Ciarrochi, J., Duineveld, J. J., Guo, J., & Sahdra, B. K. (2020) · Personality and Social Psychology Bulletin · doi:10.1177/0146167219896136 · Cited by 182

Trophic Magnification of Organic Chemicals: A Global Synthesis

Walters, D. M., Jardine, T. D., Cade, B. S., Kidd, K. A., Muir, D. C. G., & Leipzig-Scott, P. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b00201 · Cited by 181

Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast

Csárdi, G., Franks, A., Choi, D. S., Airoldi, E. M., & Drummond, D. A. (2015) · PLOS Genetics · doi:10.1371/journal.pgen.1005206 · Cited by 181

Young Children See a Single Action and Infer a Social Norm: Promiscuous Normativity in 3-Year-Olds

Schmidt, M. F. H., Butler, L. P., Heinz, J., & Tomasello, M. (2016) · Psychological Science · doi:10.1177/0956797616661182 · Cited by 181

Impulsivity traits and addiction-related behaviors in youth

Rømer Thomsen, K., Callesen, M. B., Hesse, M., Kvamme, T. L., Pedersen, M. M., Pedersen, M. U., & Voon, V. (2018) · Journal of Behavioral Addictions · doi:10.1556/2006.7.2018.22 · Cited by 173

Sleep deprivation leads to a loss of functional connectivity in frontal brain regions

Verweij, I. M., Romeijn, N., Smit, D. J., Piantoni, G., Van Someren, E. J., & van der Werf, Y. D. (2014) · BMC Neuroscience · doi:10.1186/1471-2202-15-88 · Cited by 180

Cerebrospinal fluid neurogranin and YKL ‐40 as biomarkers of Alzheimer's disease

Janelidze, S., Hertze, J., Zetterberg, H., Landqvist Waldö, M., Santillo, A., Blennow, K., & Hansson, O. (2016) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.266 · Cited by 179

Solving conservation planning problems with integer linear programming

Beyer, H. L., Dujardin, Y., Watts, M. E., & Possingham, H. P. (2016) · Ecological Modelling · doi:10.1016/j.ecolmodel.2016.02.005 · Cited by 174

Effect of a Primary Care Management Intervention on Mental Health–Related Quality of Life Among Survivors of Sepsis: A Randomized Clinical Trial

Schmidt, K., Worrack, S., Von Korff, M., Davydow, D., Brunkhorst, F., Ehlert, U., Pausch, C., Mehlhorn, J., Schneider, N., Scherag, A., et al. (2016) · JAMA · doi:10.1001/jama.2016.7207 · Cited by 179

Genetic link between family socioeconomic status and children’s educational achievement estimated from genome-wide SNPs

Krapohl, E., & Plomin, R. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.2 · Cited by 160

Predicting pre-columbian anthropogenic soils in amazonia

McMichael, C. H., Palace, M. W., Bush, M. B., Braswell, B., Hagen, S., Neves, E. G., Silman, M. R., Tamanaha, E. K., & Czarnecki, C. (2014) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2013.2475 · Cited by 179

Benchmark of filter methods for feature selection in high-dimensional gene expression survival data

Bommert, A., Welchowski, T., Schmid, M., & Rahnenführer, J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbab354 · Cited by 182

Generalized estimating equations: A pragmatic and flexible approach to the marginal GLM modelling of correlated data in the behavioural sciences

Pekár, S., & Brabec, M. (2018) · Ethology · doi:10.1111/eth.12713 · Cited by 178

Benzodiazepine, z-drug and pregabalin prescriptions and mortality among patients in opioid maintenance treatment—A nation-wide register-based open cohort study

Abrahamsson, T., Berge, J., Öjehagen, A., & Håkansson, A. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2017.01.013 · Cited by 169

BNST neurocircuitry in humans

Avery, S. N., Clauss, J. A., Winder, D. G., Woodward, N., Heckers, S., & Blackford, J. U. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.017 · Cited by 164

The Effectiveness of Online Cognitive Behavioral Treatment in Routine Clinical Practice

Ruwaard, J., Lange, A., Schrieken, B., Dolan, C. V., & Emmelkamp, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040089 · Cited by 173

Collaborative assessment and management of suicidality (CAMS): Feasibility trial for next-day appointment services

Comtois, K. A., Jobes, D. A., S. O'Connor, S., Atkins, D. C., Janis, K., E. Chessen, C., Landes, S. J., Holen, A., & Yuodelis-Flores, C. (2011) · Depression and Anxiety · doi:10.1002/da.20895 · Cited by 177

Resting-state functional connectivity of the amygdala and longitudinal changes in depression severity in adolescent depression

Connolly, C. G., Ho, T. C., Blom, E. H., LeWinn, K. Z., Sacchet, M. D., Tymofiyeva, O., Simmons, A. N., & Yang, T. T. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.09.026 · Cited by 177

Association of Parent Training With Child Language Development: A Systematic Review and Meta-analysis

Roberts, M. Y., Curtis, P. R., Sone, B. J., & Hampton, L. H. (2019) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2019.1197 · Cited by 179

On Reduced Amino Acid Alphabets for Phylogenetic Inference

Susko, E., & Roger, A. J. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm144 · Cited by 177

An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls

Chernozhukov, V., Wüthrich, K., & Zhu, Y. (2021) · Journal of the American Statistical Association · doi:10.1080/01621459.2021.1920957 · Cited by 176

A Meta-Analytic Review of Racial Discrimination: Relationships to Health and Culture

Carter, R. T., Johnson, V. E., Kirkinis, K., Roberson, K., Muchow, C., & Galgay, C. (2019) · Race and Social Problems · doi:10.1007/s12552-018-9256-y · Cited by 176

Default Mode Connectivity in Major Depressive Disorder Measured Up to 10 Days After Ketamine Administration

Evans, J. W., Szczepanik, J., Brutsché, N., Park, L. T., Nugent, A. C., & Zarate, C. A. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.027 · Cited by 173

Neuropathological correlates and genetic architecture of microglial activation in elderly human brain

Felsky, D., Roostaei, T., Nho, K., Risacher, S. L., Bradshaw, E. M., Petyuk, V., Schneider, J. A., Saykin, A., Bennett, D. A., & De Jager, P. L. (2019) · Nature Communications · doi:10.1038/s41467-018-08279-3 · Cited by 169

A genome‐wide approach to children's aggressive behavior: The EAGLE consortium

Pappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., Nolte, I. M., Tiesler, C. M. T., Bakermans‐Kranenburg, M. J., Davies, G. E., et al. (2016) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32333 · Cited by 195

Effects of arabinoxylan and resistant starch on intestinal microbiota and short-chain fatty acids in subjects with metabolic syndrome: a randomised crossover study

Hald, S., Schioldan, A. G., Moore, M. E., Dige, A., Lærke, H. N., Agnholt, J., Bach Knudsen, K. E., Hermansen, K., Marco, M. L., Gregersen, S., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159223 · Cited by 180

Assessing the Effect of Race Bias in Post-traffic Stop Outcomes Using Propensity Scores

Ridgeway, G. (2006) · Journal of Quantitative Criminology · doi:10.1007/s10940-005-9000-9 · Cited by 176

Antifungal drug resistance evoked via RNAi-dependent epimutations

Calo, S., Shertz-Wall, C., Lee, S. C., Bastidas, R. J., Nicolás, F. E., Granek, J. A., Mieczkowski, P., Torres-Martínez, S., Ruiz-Vázquez, R. M., Cardenas, M. E., et al. (2014) · Nature · doi:10.1038/nature13575 · Cited by 175

Altered Belowground Carbon Cycling Following Land-Use Change to Perennial Bioenergy Crops

Anderson-Teixeira, K. J., Masters, M. D., Black, C. K., Zeri, M., Hussain, M. Z., Bernacchi, C. J., & DeLucia, E. H. (2013) · Ecosystems · doi:10.1007/s10021-012-9628-x · Cited by 175

Blue light reduces photosynthetic efficiency of cyanobacteria through an imbalance between photosystems I and II

Luimstra, V. M., Schuurmans, J. M., Verschoor, A. M., Hellingwerf, K. J., Huisman, J., & Matthijs, H. C. P. (2018) · Photosynthesis Research · doi:10.1007/s11120-018-0561-5 · Cited by 173

Efficient removal of per- and polyfluoroalkyl substances (PFASs) in drinking water treatment: Nanofiltration combined with active carbon or anion exchange

Franke, V., McCleaf, P., Lindegren, K., & Ahrens, L. (2019) · Environmental Science: Water Research & Technology · doi:10.1039/c9ew00286c · Cited by 174

Analysis of culture-dependent versus culture-independent techniques for identification of bacteria in clinically obtained bronchoalveolar lavage fluid

Dickson, R. P., Erb-Downward, J. R., Prescott, H. C., Martinez, F. J., Curtis, J. L., Lama, V. N., & Huffnagle, G. B. (2014) · Journal of Clinical Microbiology · doi:10.1128/jcm.01028-14 · Cited by 176

The Comparative Effects of Large Carnivores on the Acquisition of Carrion by Scavengers

Allen, M. L., Elbroch, L. M., Wilmers, C. C., & Wittmer, H. U. (2015) · The American Naturalist · doi:10.1086/681004 · Cited by 174

Predicting depression in rheumatoid arthritis: The signal importance of pain extent and fatigue, and comorbidity

Wolfe, F., & Michaud, K. (2009) · Arthritis Care & Research · doi:10.1002/art.24428 · Cited by 171

Microinfarcts, brain atrophy, and cognitive function: The Honolulu Asia Aging Study Autopsy Study

Launer, L. J., Hughes, T. M., & White, L. R. (2011) · Annals of Neurology · doi:10.1002/ana.22520 · Cited by 171

Relationship between work–family conflict and turnover intention in nurses: A meta‐analytic review

Yildiz, B., Yildiz, H., & Ayaz Arda, O. (2021) · Journal of Advanced Nursing · doi:10.1111/jan.14846 · Cited by 172

High-Fiber, Whole-Food Dietary Intervention Alters the Human Gut Microbiome but Not Fecal Short-Chain Fatty Acids

Oliver, A., Chase, A. B., Weihe, C., Orchanian, S. B., Riedel, S. F., Hendrickson, C. L., Lay, M., Sewall, J. M., Martiny, J. B. H., & Whiteson, K. (2021) · mSystems · doi:10.1128/msystems.00115-21 · Cited by 171

The impact of cognitive behavioural therapy for insomnia on objective sleep parameters: a meta-analysis and systematic review

Mitchell, L. J., Bisdounis, L., Ballesio, A., Omlin, X., & Kyle, S. D. (2019) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2019.06.002 · Cited by 171

Traumatic brain injury in homeless and marginally housed individuals: a systematic review and meta-analysis

Stubbs, J. L., Thornton, A. E., Sevick, J. M., Silverberg, N. D., Barr, A. M., Honer, W. G., & Panenka, W. J. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(19)30188-4 · Cited by 173

A multi-method exploratory study of stress, coping, and substance use among high school youth in private schools

Leonard, N. R., Gwadz, M. V., Ritchie, A., Linick, J. L., Cleland, C. M., Elliott, L., & Grethel, M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01028 · Cited by 173

The effects of mindfulness training on weight-loss and health-related behaviours in adults with overweight and obesity: A systematic review and meta-analysis

Ruffault, A., Czernichow, S., Hagger, M. S., Ferrand, M., Erichot, N., Carette, C., Boujut, E., & Flahault, C. (2017) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2016.09.002 · Cited by 173

Traits of butterfly communities change from specialist to generalist characteristics with increasing land-use intensity

Börschig, C., Klein, A.-M., von Wehrden, H., & Krauss, J. (2013) · Basic and Applied Ecology · doi:10.1016/j.baae.2013.09.002 · Cited by 172

Factor analytic mixed models for the provision of grower information from national crop variety testing programs

Smith, A. B., Ganesalingam, A., Kuchel, H., & Cullis, B. R. (2015) · Theoretical and Applied Genetics · doi:10.1007/s00122-014-2412-x · Cited by 172

Pharmacologically controlled drinking in the treatment of alcohol dependence or alcohol use disorders: a systematic review with direct and network meta-analyses on nalmefene, naltrexone, acamprosate, baclofen and topiramate

Palpacuer, C., Duprez, R., Huneau, A., Locher, C., Boussageon, R., Laviolle, B., & Naudet, F. (2018) · Addiction · doi:10.1111/add.13974 · Cited by 172

Heterogeneity in NECTIN4 Expression Across Molecular Subtypes of Urothelial Cancer Mediates Sensitivity to Enfortumab Vedotin

(2021) · doi:10.1158/1078-0432.ccr-20-4175 · Cited by 172

Estimating prevalence of subjective cognitive decline in and across international cohort studies of aging: a COSMIC study

(2020) · doi:10.1186/s13195-020-00734-y · Cited by 172

Genetic evolution of T-cell resistance in the course of melanoma progression

Sucker, A., Zhao, F., Real, B., Heeke, C., Bielefeld, N., Maβen, S., Horn, S., Moll, I., Maltaner, R., Horn, P. A., et al. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-0567 · Cited by 171

Earlier versus later cognitive event-related potentials (ERPs) in attention-deficit/hyperactivity disorder (ADHD): A meta-analysis

Kaiser, A., Aggensteiner, P.-M., Baumeister, S., Holz, N. E., Banaschewski, T., & Brandeis, D. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.01.019 · Cited by 171

Estimating and mapping the carbon saturation deficit of French agricultural topsoils

Angers, D. A., Arrouays, D., Saby, N. P. A., & Walter, C. (2011) · Soil Use and Management · doi:10.1111/j.1475-2743.2011.00366.x · Cited by 171

AutoMoDe: A novel approach to the automatic design of control software for robot swarms

Francesca, G., Brambilla, M., Brutschy, A., Trianni, V., & Birattari, M. (2014) · Swarm Intelligence · doi:10.1007/s11721-014-0092-4 · Cited by 171

Social media use, mental health and sleep: A systematic review with meta-analyses

Ahmed, O., Walsh, E. I., Dawel, A., Alateeq, K., Espinoza Oyarce, D. A., & Cherbuin, N. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.08.193 · Cited by 188

Thyroid hormone regulates distinct paths to maturation in pigment cell lineages

Saunders, L. M., Mishra, A. K., Aman, A. J., Lewis, V. M., Toomey, M. B., Packer, J. S., Qiu, X., McFaline-Figueroa, J. L., Corbo, J. C., Trapnell, C., et al. (2019) · eLife · doi:10.7554/elife.45181 · Cited by 170

Overcoming Resistance Through Narratives: Findings from a Meta-Analytic Review

Ratcliff, C. L., & Sun, Y. (2020) · Human Communication Research · doi:10.1093/hcr/hqz017 · Cited by 170

Release of micro- and nanoparticles from biodegradable plastic during in situ composting

Sintim, H. Y., Bary, A. I., Hayes, D. G., English, M. E., Schaeffer, S. M., Miles, C. A., Zelenyuk, A., Suski, K., & Flury, M. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.04.179 · Cited by 170

Effect of the Macroalgae Asparagopsis Taxiformis on Methane Production and Rumen Microbiome Assemblage

Roque, B. M., Brooke, C. G., Ladau, J., Polley, T., Marsh, L. J., Najafi, N., Pandey, P., Singh, L., Kinley, R., Salwen, J. K., et al. (2019) · Animal Microbiome · doi:10.1186/s42523-019-0004-4 · Cited by 166

Predicting crop yields and soil‐plant nitrogen dynamics in the US Corn Belt

Archontoulis, S. V., Castellano, M. J., Licht, M. A., Nichols, V., Baum, M., Huber, I., Martinez‐Feria, R., Puntel, L., Ordóñez, R. A., Iqbal, J., et al. (2020) · Crop Science · doi:10.1002/csc2.20039 · Cited by 166

RIM-DB: a taxonomic framework for community structure analysis of methanogenic archaea from the rumen and other intestinal environments

Seedorf, H., Kittelmann, S., Henderson, G., & Janssen, P. H. (2014) · PeerJ · doi:10.7717/peerj.494 · Cited by 168

Radiogenomic Analysis to Identify Imaging Phenotypes Associated with Drug Response Gene Expression Programs in Hepatocellular Carcinoma

Kuo, M. D., Gollub, J., Sirlin, C. B., Ooi, C., & Chen, X. (2007) · Journal of Vascular and Interventional Radiology · doi:10.1016/j.jvir.2007.04.031 · Cited by 168

APOE-related risk of mild cognitive impairment and dementia for prevention trials: An analysis of four cohorts

Qian, J., Wolters, F. J., Beiser, A., Haan, M., Ikram, M. A., Karlawish, J., Langbaum, J. B., Neuhaus, J. M., Reiman, E. M., Roberts, J. S., et al. (2017) · PLOS Medicine · doi:10.1371/journal.pmed.1002254 · Cited by 169

TLDR: Extreme Summarization of Scientific Documents

Cachola, I., Lo, K., Cohan, A., & Weld, D. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020 · doi:10.18653/v1/2020.findings-emnlp.428 · Cited by 169

The Impact of Trade on Inequality in Developing Countries

Pavcnik, N. (2017) · doi:10.3386/w23878 · Cited by 169

Locally rare species influence grassland ecosystem multifunctionality

Soliveres, S., Manning, P., Prati, D., Gossner, M. M., Alt, F., Arndt, H., Baumgartner, V., Binkenstein, J., Birkhofer, K., Blaser, S., et al. (2016) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2015.0269 · Cited by 168

Predawn and high intensity application of supplemental blue light decreases the quantum yield of PSII and enhances the amount of phenolic acids, flavonoids, and pigments in Lactuca sativa

Ouzounis, T., Razi Parjikolaei, B., Fretté, X., Rosenqvist, E., & Ottosen, C.-O. (2015) · Frontiers in Plant Science · doi:10.3389/fpls.2015.00019 · Cited by 168

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Human Monocyte Subsets Are Transcriptionally and Functionally Altered in Aging in Response to Pattern Recognition Receptor Agonists

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Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning

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Evolution at two levels of gene expression in yeast

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Human exposure pathways to poly- and perfluoroalkyl substances (PFAS) from indoor media: a systematic review

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