The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
The Human Phenome Project
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Little is known about the impact of activity over time on developing chronic diseases across the full human phenome, which represents the sum of human traits and conditions resulting from genetic and behavioral variation in a population7.”
From Association of step counts over time with the risk of chronic disease in the All of Us Research Program (2022) · cites this paper as [7]
In the citing paper
“Even once we have the information from thousands of genomes, biological insights into the CNS require the assessment of relevant behavioural and cognitive phenotypes, which are not well defined for most neuropsychiatric diseases198,199 and are rarely collected in large populations.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [198]
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,938
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., et al. (1999) · Science · doi:10.1126/science.286.5439.531 · Cited by 11,516
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,569
Finding Groups in Data: An Introduction to Cluster Analysis
Kaufman, L., & Rousseeuw, P. J. (1990) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316801 · Cited by 7,344
Minimum information about a microarray experiment (MIAME)-toward standards for microarray data
Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., et al. (2001) · Nature Genetics · doi:10.1038/ng1201-365 · Cited by 4,109
Mazziotta, J. C., Toga, A. W., Evans, A. C., Fox, P. T., Lancaster, J. L., Zilles, K., Woods, R. P., Paus, T., Simpson, G. V., Pike, G. B., et al. (2001) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2001.0915 · Cited by 2,417
Cited by
Sorted by citations
Multi-omics approaches to disease
Hasin, Y., Seldin, M., & Lusis, A. (2017) · Genome Biology · doi:10.1186/s13059-017-1215-1 · Cited by 2,953
Global Mapping of the Yeast Genetic Interaction Network
Tong, A. H. Y., Lesage, G., Bader, G. D., Ding, H., Xu, H., Xin, X., Young, J., Berriz, G. F., Brost, R. L., Chang, M., et al. (2004) · Science · doi:10.1126/science.1091317 · Cited by 2,089
Evaluating the potential role of pleiotropy in Mendelian randomization studies
Hemani, G., Bowden, J., & Davey Smith, G. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy163 · Cited by 1,496
“• The human phenome can be described as all (measurable or not) characteristics of an individual (104).”
BackgroundReplicating genotype–phenotype associations
NCI-NHGRI Working Group on Replication in Association Studies, Chanock, S. J., Manolio, T., Boehnke, M., Boerwinkle, E., Hunter, D. J., Thomas, G., Hirschhorn, J. N., Abecasis, G., Altshuler, D., et al. (2007) · Nature · doi:10.1038/447655a · Cited by 1,352
Self-citationHoule, D., Govindaraju, D. R., & Omholt, S. W. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2897 · Cited by 1,319
Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype
Barnett, G. C., West, C., Dunning, A. M., Elliott, R. M., Coles, C. E., Pharoah, P. D. P., & Burnet, N. G. (2009) · Nature reviews. Cancer · doi:10.1038/nrc2587 · Cited by 804
Rare-disease genetics in the era of next-generation sequencing: discovery to translation
Boycott, K. M., Vanstone, M. R., Bulman, D. E., & MacKenzie, A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3555 · Cited by 804
Common disorders are quantitative traits
Plomin, R., Haworth, C. M. A., & Davis, O. S. P. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2670 · Cited by 670
A text-mining analysis of the human phenome
van Driel, M. A., Bruggeman, J., Vriend, G., Brunner, H. G., & Leunissen, J. A. M. (2006) · European Journal of Human Genetics · doi:10.1038/sj.ejhg.5201585 · Cited by 664
Network‐based global inference of human disease genes
Wu, X., Jiang, R., Zhang, M. Q., & Li, S. (2008) · Molecular Systems Biology · doi:10.1038/msb.2008.27 · Cited by 659
Age, Gene/Environment Susceptibility-Reykjavik Study: multidisciplinary applied phenomics
Harris, T. B., Launer, L. J., Eiriksdottir, G., Kjartansson, O., Jonsson, P. V., Sigurdsson, G., Thorgeirsson, G., Aspelund, T., Garcia, M. E., Cotch, M. F., et al. (2007) · American Journal of Epidemiology · doi:10.1093/aje/kwk115 · Cited by 592
Advanced sequencing technologies: methods and goals
Shendure, J., Mitra, R. D., Varma, C., & Church, G. M. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1325 · Cited by 569
Zooming In on a Quantitative Trait for Tomato Yield Using Interspecific Introgressions
Fridman, E., Carrari, F. O., Liu, Y., Fernie, A. R., & Zamir, D. (2004) · Science · doi:10.1126/science.1101666 · Cited by 539
Abundant Pleiotropy in Human Complex Diseases and Traits
Sivakumaran, S., Agakov, F. V., Τheodoratou, E., Prendergast, J. G. D., Zgaga, L., Manolio, T. A., Rudan, I., McKeigue, P., Wilson, J. F., & Campbell, H. J. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.10.004 · Cited by 538
The endophenotype concept in psychiatric genetics
FLINT, J., & MUNAFÒ, M. R. (2007) · Psychological Medicine · doi:10.1017/s0033291706008750 · Cited by 477
Uncovering the structure of self-regulation through data-driven ontology discovery
Eisenberg, I. W., Bissett, P. G., Enkavi, A. Z., Li, J. K., MacKinnon, D. P., Marsch, L. A., & Poldrack, R. A. (2019) · Nature Communications · doi:10.1038/s41467-019-10301-1 · Cited by 509
Long-term neural and physiological phenotyping of a single human
Poldrack, R. A., Laumann, T. O., Koyejo, S., Gregory, B., Hover, A. M., Chen, M.-Y., Gorgolewski, K. J., Luci, J. J., Joo, S. J., Boyd, R. L., et al. (2015) · Nature Communications · doi:10.1038/ncomms9885 · Cited by 486
Deep phenotyping for precision medicine
Robinson, P. N. (2012) · Human Mutation · doi:10.1002/humu.22080 · Cited by 479
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430
Royal Australian And New Zealand College Of Psychiatrists Clinical Practice Guidelines Team For The Treatment Of Schizophrenia And Related Disorders (2005) · Australian & New Zealand Journal of Psychiatry · doi:10.1080/j.1440-1614.2005.01516.x · Cited by 435
Toward constructing an endophenotype strategy for bipolar disorders
Hasler, G., Drevets, W. C., Gould, T. D., Gottesman, I. I., & Manji, H. K. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.11.006 · Cited by 423
The modular nature of genetic diseases
Oti, M., & Brunner, H. G. (2006) · Clinical Genetics · doi:10.1111/j.1399-0004.2006.00708.x · Cited by 411
Robinson, P. N., & Mundlos, S. (2010) · Clinical Genetics · doi:10.1111/j.1399-0004.2010.01436.x · Cited by 357
Comparing the human and chimpanzee genomes: Searching for needles in a haystackPreprint
Varki, A. P., & Altheide, T. K. (2005) · Genome Research · doi:10.1101/gr.3737405 · Cited by 339
Skuse, D., Warrington, R., Bishop, D., Chowdhury, U., Lau, J., Mandy, W., & Place, M. (2004) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-200405000-00008 · Cited by 342
Cannon, T. D., Hennah, W., van Erp, T. G. M., Thompson, P. M., Lonnqvist, J., Huttunen, M., Gasperoni, T., Tuulio-Henriksson, A., Pirkola, T., Toga, A. W., et al. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.11.1205 · Cited by 337
Kochinke, K., Zweier, C., Nijhof, B., Fencková, M., Čížek, P., Honti, F., Keerthikumar, S., Oortveld, M. A. W., Kleefstra, T., Kramer, J. M., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.024 · Cited by 337
Navigating the channels and beyond: unravelling the genetics of the epilepsies
Helbig, I., Scheffer, I. E., Mulley, J. C., & Berkovic, S. F. (2008) · The Lancet Neurology · doi:10.1016/s1474-4422(08)70039-5 · Cited by 281
Unravelling the human genome–phenome relationship using phenome-wide association studies
Bush, W. S., Oetjens, M. T., & Crawford, D. C. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.36 · Cited by 269
Electronic health records-driven phenotyping: challenges, recent advances, and perspectives
Pathak, J., Kho, A. N., & Denny, J. C. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002428 · Cited by 274
Eisenberg, D. T. A., MacKillop, J., Modi, M. E., Beauchemin, J., Dang, D., Lisman, S. A., Lum, J. K., & Wilson, D. S. (2007) · Behavioral and Brain Functions · doi:10.1186/1744-9081-3-2 · Cited by 264
Cancer phenomics: RET and PTEN as illustrative models
Zbuk, K. M., & Eng, C. (2006) · Nature reviews. Cancer · doi:10.1038/nrc2037 · Cited by 241
Phenomics: the systematic study of phenotypes on a genome-wide scale
Bilder, R. M., Sabb, F. W., Cannon, T. D., London, E. D., Jentsch, J. D., Parker, D. S., Poldrack, R. A., Evans, C. J., & Freimer, N. B. (2009) · Neuroscience · doi:10.1016/j.neuroscience.2009.01.027 · Cited by 242
Self-citationAdvances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models
Banda, J. M., Seneviratne, M. G., Hernandez‐Boussard, T., & Shah, N. H. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013315 · Cited by 228
Celli, B. R., Decramer, M., Wedzicha, J. A., Wilson, K. C., Agustí, A. G. N., Criner, G. J., MacNee, W., Make, B. J., Rennard, S. I., Stockley, R. A., et al. (2015) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201501-0044st · Cited by 230
Master, H., Annis, J., Huang, S., Beckman, J. A., Ratsimbazafy, F., Marginean, K., Carroll, R., Natarajan, K., Harrell, F. E., Roden, D. M., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-02012-w · Cited by 220
Predictive validity of a method for evaluating temperament in young guide and service dogs
Duffy, D. L., & Serpell, J. A. (2012) · Applied Animal Behaviour Science · doi:10.1016/j.applanim.2012.02.011 · Cited by 220
Tebani, A., Afonso, C., Marret, S., & Bekri, S. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17091555 · Cited by 228
Suravajhala, P., Kogelman, L. J. A., & Kadarmideen, H. N. (2016) · Genetics Selection Evolution · doi:10.1186/s12711-016-0217-x · Cited by 232
Endophenotypes for psychiatric disorders: ready for primetime?
Bearden, C. E., & Freimer, N. B. (2006) · Trends in Genetics · doi:10.1016/j.tig.2006.04.004 · Cited by 208
Self-citationLin, Y. (2015) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2015.10.011 · Cited by 217
Heart Failure in Pediatric Patients With Congenital Heart Disease
Hinton, R. B., & Ware, S. M. (2017) · Circulation Research · doi:10.1161/circresaha.116.308996 · Cited by 215
Creation and implications of a phenome-genome network
Butte, A. J., & Kohane, I. S. (2006) · Nature Biotechnology · doi:10.1038/nbt1150 · Cited by 201
Aggregometry detects platelet hyperreactivity in healthy individuals
Yee, D. L., Sun, C. W., Bergeron, A. L., Dong, J.-F., & Bray, P. F. (2005) · Blood · doi:10.1182/blood-2005-03-1290 · Cited by 203
Celli, B. R., Decramer, M., Wedzicha, J. A., Wilson, K. C., Agustí, A. G. N., Criner, G. J., MacNee, W., Make, B. J., Rennard, S. I., Stockley, R. A., et al. (2015) · European Respiratory Journal · doi:10.1183/09031936.00009015 · Cited by 205
The path to personalised medicine in COPD
Agustí, A. G. N. (2014) · Thorax · doi:10.1136/thoraxjnl-2014-205507 · Cited by 193
Friedman, L., & Glover, G. H. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.07.012 · Cited by 191
Data integration and genomic medicine
Louie, B., Peter Mork, B., Martin-Sanchez, F. J., Halevy, A. Y., & Tarczy-Hornoch, P. Z. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.02.007 · Cited by 193
Agustí, A. G. N., Sobradillo, P., & Celli, B. R. (2010) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201009-1414pp · Cited by 186
Taylor, J. G., Nolan, V. G., Mendelsohn, L. G., Kato, G. J., Gladwin, M. T., & Steinberg, M. H. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002095 · Cited by 185
Towards an Ontology of Cognitive Control
Lenartowicz, A., Kalar, D. J., Congdon, E. L., & Poldrack, R. A. (2010) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2010.01100.x · Cited by 184
From syndrome families to functional genomics
Brunner, H. G., & van Driel, M. A. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1383 · Cited by 175
Patwardhan, B., Kalpana, J., & Arvind, C. (2005) · The Journal of Alternative and Complementary Medicine · doi:10.1089/acm.2005.11.349 · Cited by 174
Hansen, P. J. (2020) · Journal of Animal Science · doi:10.1093/jas/skaa288 · Cited by 159
Tangled webs: Tracing the connections between genes and cognition
Fisher, S. E. (2006) · Cognition · doi:10.1016/j.cognition.2006.04.004 · Cited by 157
Freimer, N. B., & Sabatti, C. (2004) · Nature Genetics · doi:10.1038/ng1433 · Cited by 152
Self-citationMartin-Sanchez, F. J., Iakovidis, I., Norager, S., Maojo, V., de Groen, P., van der Lei, J., Jones, T., Abraham‐Fuchs, K., Apweiler, R., Babić, A., et al. (2003) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2003.09.003 · Cited by 151
Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeastPreprint
Skelly, D. A., Merrihew, G. E., Riffle, M. E., Connelly, C. F., Kerr, E. O., Johansson, M., Jaschob, D., Graczyk, B., Shulman, N., Wakefield, J., et al. (2013) · Genome Research · doi:10.1101/gr.155762.113 · Cited by 146
Neuropsychology 3.0: Evidence-Based Science and Practice
Bilder, R. M. (2010) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617710001396 · Cited by 141
The use of 3D face shape modelling in dysmorphology
BMJ Publishing Group Ltd and Royal College of Paediatrics and Child Health (2007) · Archives of Disease in Childhood · doi:10.1136/adc.2006.103507 · Cited by 139
Kis, A., Bence, M., Lakatos, G., Pergel, E., Turcsán, B., Pluijmakers, J., Vas, J., Elek, Z., Brúder, I., Földi, L., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0083993 · Cited by 138
Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology
Lürig, M., Donoughe, S., SVENSSON, E. I., Porto, A., & Tsuboi, M. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.642774 · Cited by 142
Pharmacogenomics and ???Individualized Drug Therapy???
Nebert, D. W., Jorge-Nebert, L. F., & Vesell, E. S. (2003) · American Journal of PharmacoGenomics · doi:10.2165/00129785-200303060-00002 · Cited by 137
Arterial stiffness and influences of the metabolic syndrome: A cross-countries study
Scuteri, A., Cunha, P., Rosei, E. A., Badariere, J., Bekaert, S., Cockcroft, J. R., Cotter, J., Cucca, F., Buyzere, M. D., Meyer, T. D., et al. (2014) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2014.01.041 · Cited by 134
Numbering the hairs on our heads: The shared challenge and promise of phenomics
Houle, D. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906195106 · Cited by 134
Systems Pharmacology to Predict Drug Toxicity: Integration Across Levels of Biological Organization
Bai, J. P. F., & Abernethy, D. R. (2012) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-011112-140248 · Cited by 133
Chemobehavioural phenomics and behaviour-based psychiatric drug discovery in the zebrafish
Kokel, D., & Peterson, R. T. (2008) · Briefings in Functional Genomics and Proteomics · doi:10.1093/bfgp/eln040 · Cited by 133
Gersting, S. W., Kemter, K. F., Staudigl, M., Messing, D. D., Danecka, M. K., Lagler, F. B., Sommerhoff, C. P., Roscher, A. A., & Muntau, A. C. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.05.013 · Cited by 125
Celli, B. R., Decramer, M., Wedzicha, J. A., Wilson, K. C., Agusti, A. A., Criner, G. J., MacNee, W., Make, B. J., Rennard, S. I., Stockley, R. A., et al. (2015) · European Respiratory Review · doi:10.1183/16000617.00000315 · Cited by 117
Pathak, J., Wang, J., Kashyap, S., Basford, M., Li, R., Masys, D. R., & Chute, C. G. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2010-000061 · Cited by 113
Avery, C. L., He, Q., North, K. E., Ambite, J. L., Boerwinkle, E., Fornage, M., Hindorff, L. A., Kooperberg, C. L., Meigs, J. B., Pankow, J. S., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002322 · Cited by 113
mtDNA phylogeny and evolution of laboratory mouse strainsPreprint
Goios, A., Pereira, L., Bogue, M. A., Macaulay, V. A., & Amorim, A. (2007) · Genome Research · doi:10.1101/gr.5941007 · Cited by 108
Molecular regulation of copper excretion in the liver
Wijmenga, C., & Klomp, L. W. J. (2004) · Proceedings of The Nutrition Society · doi:10.1079/pns2003316 · Cited by 106
Genome-Wide Association Studies of Skeletal Phenotypes: What We Have Learned and Where We Are Headed
Hsu, Y., & Kiel, D. P. (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-1890 · Cited by 109
Alshali, K. Z., House, A. A., Hanley, A. J., Khan, H. M. R., Harris, S. B., Mamakeesick, M., Zinman, B., Fenster, A., Spence, J. D., & Hegele, R. A. (2004) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2004.08.016 · Cited by 99
Oti, M., Huynen, M. A., & Brunner, H. G. (2008) · Trends in Genetics · doi:10.1016/j.tig.2007.12.005 · Cited by 101
Phenotyping plants: genes, phenes and machines
Pieruschka, R., & Poorter, H. (2012) · Functional Plant Biology · doi:10.1071/fpv39n11_in · Cited by 95
LMNA mutation position predicts organ system involvement in laminopathies
Hegele, R. A. (2005) · Clinical Genetics · doi:10.1111/j.1399-0004.2005.00447.x · Cited by 93
Human monogenic disorders — a source of novel drug targets
Brinkman, R. R., Dubé, M., Rouleau, G. A., Orr, A. C., & Samuels, M. E. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1828 · Cited by 90
Ghodke‐Puranik, Y., Joshi, K., Chopra, A., & Patwardhan, B. (2005) · European Journal of Epidemiology · doi:10.1007/s10654-005-5081-x · Cited by 92
Maximizing the potential of functional genomics
Steinmetz, L. M., & Davis, R. W. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1293 · Cited by 91
Personal genomes in progress: from the Human Genome Project to the Personal Genome Project
Lunshof, J. E., Bobe, J. R., Aach, J., Angrist, M. H., Thakuria, J. V., Vorhaus, D. B., Hoehe, M. R., & Church, G. M. (2010) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2010.12.1/jlunshof · Cited by 90
Metabolomic approaches to phenotype characterization and applications to complex diseases
Orešič, M., Vidal‐Puig, A., & Hänninen, V. A. (2006) · Expert Review of Molecular Diagnostics · doi:10.1586/14737159.6.4.575 · Cited by 88
Malanga, C. J., & Kosofsky, B. E. (2003) · Developmental Brain Research · doi:10.1016/j.devbrainres.2003.09.019 · Cited by 88
The Myth of Optimality in Clinical Neuroscience
Holmes, A. J., & Patrick, L. M. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.12.006 · Cited by 89
Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes
Scharfe, C., Lu, H. H., Neuenburg, J. K., Allen, E. A., Li, G.-C., Klopstock, T., Cowan, T. M., Enns, G. M., & Davis, R. W. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000374 · Cited by 88
The bipolar disorder phenome database: a resource for genetic studies
Potash, J. B., Toolan, J., Steele, J., Miller, E. B., Pearl, J., Zandi, P. P., Schulze, T. G., Kassem, L., Simpson, S. G., Lopez, V., et al. (2007) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2007.06122045 · Cited by 80
Moving from the Oslerian paradigm to the post-genomic era: are asthma and COPD outdated terms?
Vanfleteren, L. E. G. W., Kocks, J. W. H., Stone, I. S., Breyer‐Kohansal, R., Greulich, T., Lacedonia, D., Buhl, R., Fabbri, L. M., Pavord, I. D., Barnes, N. C., et al. (2013) · Thorax · doi:10.1136/thoraxjnl-2013-203602 · Cited by 80
Evaluation of research in biomedical ontologies
Hoehndorf, R., Dumontier, M., & Gkoutos, G. V. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs053 · Cited by 86
Advances in Genomic Analysis of Stroke
Lanktree, M. B., Dichgans, M., & Hegele, R. A. (2010) · Stroke · doi:10.1161/strokeaha.109.570523 · Cited by 78
Whole-animal imaging, gene function, and the Zebrafish Phenome Project
Cheng, K. C., Xin, X., Clark, D. P., & Rivière, P. J. L. (2011) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2011.08.006 · Cited by 77
Co-clustering phenome–genome for phenotype classification and disease gene discovery
Hwang, T., Atluri, G., Xie, M., Dey, S., Hong, C., Kumar, V., & Kuang, R. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks615 · Cited by 77
Burgel, P., Paillasseur, J.-L., & Roche, N. (2014) · BioMed Research International · doi:10.1155/2014/420134 · Cited by 76
Phenomics: Building Scaffolds for Biological Hypotheses in the Post-Genomic Era
Bilder, R. M. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.11.013 · Cited by 76
A collaborative knowledge base for cognitive phenomics
Sabb, F. W., Bearden, C. E., Glahn, D. C., Parker, D. S., Freimer, N. B., & Bilder, R. M. (2008) · Molecular Psychiatry · doi:10.1038/sj.mp.4002124 · Cited by 76
Self-citationPrinciples of phenomics in endometriosis
Viganò, P., Somigliana, E., Panina‐Bordignon, P., Rabellotti, E., Vercellini, P., & Candiani, M. (2012) · Human Reproduction Update · doi:10.1093/humupd/dms001 · Cited by 80
The virtuous cycle of human genetics and mouse models in drug discovery
Nadeau, J. H., & Auwerx, J. H. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0009-9 · Cited by 78
Bader, V., Tomppo, L., Trossbach, S. V., Bradshaw, N. J., Prikulis, I., Leliveld, S. R., Lin, C.-Y., Ishizuka, K., Sawa, A., Ramos, A., et al. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds273 · Cited by 70
Whiteley, A., Derôme, N., Rogers, S., St.-Cyr, J., Laroche, J., Labbe, A., Nolte, A., Renaut, S., Jeukens, J., & Bernatchez, L. (2008) · Genetics · doi:10.1534/genetics.108.089938 · Cited by 78
A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery
Hwang, T., & Kuang, R. (2010) · SIAM International Conference on Data Mining · doi:10.1137/1.9781611972801.51 · Cited by 67
Metadata
- Authors
- Freimer, N., & Sabatti, C.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Freimer, Nelson
- Venue
- Nature Genetics
- Published
- 2003-05
- Volume
- 34
- Issue
- 1
- Pages
- 15-21
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2014022579
- Cited by
- 372
- References
- 33
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 6 · 2023: 7 · 2022: 6 · 2021: 11 · 2020: 7 · 2019: 10 · 2018: 15 · 2017: 7 · 2016: 22 · 2015: 18 · 2014: 13 · 2013: 25 · 2012: 26
- FWCI
- 14.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- phenomics, phenotypic data, genotype-phenotype correlation, genome-wide genotyping, phenotyping, international research collaboration
- MeSH terms
- Animals, Data Interpretation, Statistical, Genetics, Medical, Humans, International Cooperation, Phenotype, Research Support as Topic, Cohort Studies, Genomics, Models, Animal, Databases, Genetic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review