The Human Phenome Project

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

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring

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

A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)

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

Children of Alzheimer Patients: An Overview

Jarvik, L. F., & Blazer, D. G. (2005) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/0891988705281859 · Cited by 20

Temperament and Its Implications for Neuroimaging of Anxiety Disorders

Schwartz, C., & Rauch, S. L. (2004) · CNS Spectrums · doi:10.1017/s1092852900009226 · Cited by 19

Concept of Schizophrenia: Past, Present, and Future

Andreasen, N. C. (2010) · doi:10.1002/9781444327298.ch1 · Cited by 19

Systems biology: A biologist's viewpoint

Bose, B. (2013) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2013.07.001 · Cited by 19

Decision Models and Technology Can Help Psychiatry Develop Biomarkers

Barron, D. S., Baker, J. T., Budde, K. S., Bzdok, D., Eickhoff, S. B., Friston, K. J., Fox, P. T., Geha, P., Heisig, S., Holmes, A. J., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.706655 · Cited by 19

Identification of Cancer Cell-Line Origins Using Fluorescence Image-Based Phenomic Screening

Lee, J., Kim, Y. K., Kim, H. J., Hajar, S., Tan, Y. L., Kang, N., Ng, S. H., Yoon, C. N., & Chang, Y. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032096 · Cited by 17

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Zhang, Y.-P., Zhang, Y.-Y., & Duan, D. D. (2016) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2016.02.003 · Cited by 17

Automated measurement of Drosophila jump reflex habituation and its use for mutant screening

Sharma, P., Keane, J., O’Kane, C. J., & Asztalos, Z. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.05.024 · Cited by 16

Using phenome-wide association studies to examine the effect of environmental exposures on human health

Braun, J. M., Kalloo, G., Kingsley, S. L., & Li, N. (2019) · Environment International · doi:10.1016/j.envint.2019.05.071 · Cited by 17

Nonparametric Methods for Molecular Biology

Wittkowski, K. M., & Song, T. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-580-4_2 · Cited by 17

Pharmacogenetics of Monoamine Transporters

Glatt, C. E., & Reus, V. I. (2003) · Pharmacogenomics · doi:10.1517/phgs.4.5.583.23789 · Cited by 16

HPOAnnotator: improving large-scale prediction of HPO annotations by low-rank approximation with HPO semantic similarities and multiple PPI networks

Gao, J., Liu, L., Yao, S., Huang, X., Mamitsuka, H., & Zhu, S. (2019) · BMC Medical Genomics · doi:10.1186/s12920-019-0625-1 · Cited by 15

Syntropy, Genetic Testing and Personalized Medicine

Puzyrev, V. P., Makeeva, O. A., & Freidin, M. B. (2010) · Personalized Medicine · doi:10.2217/pme.10.35 · Cited by 16

Array comparative genomic hybridization and computational genome annotation in constitutional cytogenetics: suggesting candidate genes for novel submicroscopic chromosomal imbalance syndromes

Vooren, S. V., Coessens, B., Moor, B. D., Moreau, Y., & Vermeesch, J. R. (2007) · Genetics in Medicine · doi:10.1097/gim.0b013e318145b27b · Cited by 15

Phenomics: unlocking the hidden genetic variation for breaking the barriers in yield and stress tolerance

Kumar, S., Raju, D., Sahoo, R. N., & Chinnusamy, V. (2016) · Indian Journal of Plant Physiology · doi:10.1007/s40502-016-0261-0 · Cited by 14

Semantic ETL into i2b2 with Eureka!

Post, A. R., Kurç, T., Rathod, H., Agravat, S. B., Mansour, M., Torian, W. M., & Saltz, J. H. (2013) · Europe PMC (PubMed Central) · Cited by 14

Atherosclerosis: From Genetic Polymorphisms to System Genetics

Cambien, F., & Tiret, L. (2005) · Cardiovascular Toxicology · doi:10.1385/ct:5:2:143 · Cited by 14

Whole Person Modeling: a transdisciplinary approach to mental health research

Felsky, D., Cannitelli, A., & Pipitone, J. (2023) · Discover Mental Health · doi:10.1007/s44192-023-00041-6 · Cited by 16

Cytogenetic genotype-phenotype studies: Improving genotyping, phenotyping and data storage

Feenstra, I., Brunner, H. G., & van Ravenswaaij‐Arts, C. M. A. (2006) · Cytogenetic and Genome Research · doi:10.1159/000095919 · Cited by 13

An Integrative Network Approach to Map the Transcriptome to the Phenome

Mehan, M. R., Nunez-Iglesias, J., Kalakrishnan, M., Waterman, M. S., & Zhou, X. J. (2009) · Journal of Computational Biology · doi:10.1089/cmb.2009.0037 · Cited by 13

Visualizing information across multidimensional post-genomic structured and textual databases

Tao, Y., Friedman, C., & Lussier, Y. A. (2004) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti210 · Cited by 13

Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data

Morales, J. F., Song, T., Auerbach, A. D., & Wittkowski, K. M. (2008) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1372 · Cited by 13

Learning to Recognize Phenotype Candidates in the Auto-Immune Literature Using SVM Re-Ranking

Collier, N., Tran, M.-V., Le, H.-Q., Ha, Q.-T., Oellrich, A., & Rebholz‐Schuhmann, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072965 · Cited by 12

Multimodal learning for mapping genotype–phenotype dynamics

Khodaee, F., Zandie, R., & Edelman, E. R. (2025) · Nature Computational Science · doi:10.1038/s43588-024-00765-7 · Cited by 12

Toward knowledge support for analysis and interpretation of complex traits

Collier, N., Oellrich, A., & Groza, T. (2013) · Genome biology · doi:10.1186/gb-2013-14-9-214 · Cited by 12

Phenotype Data: A Neglected Resource in Biomedical Research?

Groth, P., & Weiss, B. (2006) · Current Bioinformatics · doi:10.2174/157489306777828008 · Cited by 12

An ontologically founded architecture for information systems in clinical and epidemiological research

Uciteli, A., Groß, S., Kireyev, S., & Heinrich Herre, B. (2011) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-2-s4-s1 · Cited by 12

Study designs and methods post genome-wide association studies

Ziegler, A., & Sun, Y. V. (2012) · Human Genetics · doi:10.1007/s00439-012-1209-8 · Cited by 12

COPD: CardiOPulmonary Disease?

Kawut, S. M. (2013) · European Respiratory Journal · doi:10.1183/09031936.00009413 · Cited by 12

Stroke Genome-Wide Association Studies

Meschia, J. F. (2010) · Stroke · doi:10.1161/strokeaha.109.576769 · Cited by 12

Phenomics as an approach to Comparative Developmental Physiology

McCoy, J. C. S., Spicer, J. I., Ibbini, Z., & Tills, O. (2023) · Frontiers in Physiology · doi:10.3389/fphys.2023.1229500 · Cited by 14

Information Technology

Chueh, H. C., & Murphy, S. N. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-373639-0.00010-8 · Cited by 11

Trends in Precision Medicine

Kaur, J., Rahat, B., Thakur, S., & Kaur, J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809411-2.00015-5 · Cited by 14

Cerebrospinal fluid monoamine metabolite concentrations as intermediate phenotypes between glutamate-related genes and psychosis

Andreou, D., Söderman, E., Axelsson, T., Sedvall, G. C., Terenius, L. Y., Agartz, I., & Jönsson, E. G. (2015) · Psychiatry Research · doi:10.1016/j.psychres.2015.06.023 · Cited by 11

True monolayer cell culture in a confined 3D microenvironment enables lineage informatics

Ramunas, J., Illman, M., Kam, A., Farn, K., Kelly, L., Morshead, C. M., & Jervis, E. (2006) · Cytometry Part A · doi:10.1002/cyto.a.20341 · Cited by 11

Clinical Phenome Scanning

Ghebranious, N., McCarty, C. A., & Wilke, R. A. (2007) · Personalized Medicine · doi:10.2217/17410541.4.2.175 · Cited by 11

Primary and Secondary Hypertension

Blumenfeld, J. D., Liu, F., & Laragh, J. H. (2012) · Elsevier eBooks · doi:10.1016/b978-1-4160-6193-9.10046-6 · Cited by 11

Genetic epidemiology: some special contributions of birth cohorts

Pembrey, M. E. (2004) · Paediatric and Perinatal Epidemiology · doi:10.1111/j.1365-3016.2004.00530.x · Cited by 12

The Neurodevelopmental Model of Schizophrenia: Updated

Bearden, C. E., MEYER, S. E., Loewy, R. L., Niendam, T. A., & Cannon, T. D. (2015) · Wiley eBooks · doi:10.1002/9780470939406.ch14 · Cited by 11

Meta‐analysis: Congruence of genomic and phenotypic differentiation across diverse natural study systems

Wood, Z. T., Wiegardt, A. K., Barton, K. L., Clark, J. D., Homola, J. J., Olsen, B. J., King, B. L., Kovach, A. I., & Kinnison, M. T. (2021) · Evolutionary Applications · doi:10.1111/eva.13264 · Cited by 9

Creating an Ontology‐Based Human Phenotyping System: The Rockefeller University Bleeding History Experience

Mauer, A. C., Barbour, E. M., Khazanov, N. A., Levenkova, N., Mollah, S. A., & Coller, B. S. (2009) · Clinical and Translational Science · doi:10.1111/j.1752-8062.2009.00147.x · Cited by 10

Reimagining What We Measure in Atherosclerosis—a “Phenotype Stack”

MacRae, C. A., & Califf, R. M. (2020) · Circulation Research · doi:10.1161/circresaha.120.315941 · Cited by 10

Strategies for the Study of Neuropsychiatric Disorders Using Endophenotypes in Developing Countries: A Potential Databank from China

Chan, R. C. K., Gottesman, I. I., Ge, X., & Sham, P. C. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00207 · Cited by 10

The Genetics of Congestive Heart Failure

MacRae, C. A. (2010) · Heart Failure Clinics · doi:10.1016/j.hfc.2009.11.004 · Cited by 10

Genetics of Psychiatric Disorders

Nürnberger, J. I., Berrettini, W. H., & Niculescu, A. B. (2008) · Humana Press eBooks · doi:10.1007/978-1-59745-252-6_29 · Cited by 9

Cancerome: A hidden informative subnetwork of the diseasome

Jalili, M., Salehzadeh‐Yazdi, A., Yaghmaie, M., Ghavamzadeh, A., & Alimoghaddam, K. (2016) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2016.07.010 · Cited by 9

Phenotyping for early predictors of obesity and the metabolic syndrome

Dulloo, A. G., & Montani, J.-P. (2010) · International Journal of Obesity · doi:10.1038/ijo.2010.233 · Cited by 9

Genetic dissection of intermediate phenotypes as a way to discover novel cancer susceptibility alleles

Carvajal‐Carmona, L. G. (2010) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2010.03.013 · Cited by 7

PhenOMIM: An OMIM-based secondary database purported for phenotypic comparison

van Triest, H. J. W., Chen, D., Ji, X., Qi, S., & Li‐Ling, J. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6090600 · Cited by 8

Changing the Diagnostic Concept of Schizophrenia: The NIMH Research Domain Criteria Initiative

Morris, S. E., Vaidyanathan, U., & Cuthbert, B. N. (2016) · Nebraska Symposium on Motivation/The Nebraska symposium on motivation · doi:10.1007/978-3-319-30596-7_8 · Cited by 8

AiProAnnotator: Low-rank Approximation with network side information for high-performance, large-scale human Protein abnormality Annotator

Gao, J., Yao, S., Mamitsuka, H., & Zhu, S. (2018) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2018.8621517 · Cited by 8

Closing the ‘phenotype gap’ in precision medicine: improving what we measure to understand complex disease mechanisms

MacRae, C. A. (2019) · Mammalian Genome · doi:10.1007/s00335-019-09810-7 · Cited by 8

Yeast Phenomics—Large-scale Mapping of the Genetic Basis for Organismal Traits

(2014) · CRC Press eBooks · doi:10.1201/b16437-11 · Cited by 8

High-Resolution and Multidimensional Phenotypes Can Complement Genomics Data to Diagnose Diseases in the Neonatal Population

Xiao, T., Dong, X., Lu, Y., & Zhou, W. (2022) · Phenomics · doi:10.1007/s43657-022-00071-0 · Cited by 8

Terms and Concepts

Paus, T. (2013) · Springer eBooks · doi:10.1007/978-3-642-36450-1_1 · Cited by 8

Heritability and Familiality of Temperament and Character Dimensions in Korean Families with Schizophrenic Linkage Disequilibrium

Lee, B. D., Park, J., Lee, Y. M., Moon, E., Jeong, H. J., Chung, Y., & Yi, Y. M. (2016) · Clinical Psychopharmacology and Neuroscience · doi:10.9758/cpn.2016.14.2.203 · Cited by 8

A hybrid approach to finding phenotype candidates in genetic texts

Collier, N., Tran, M.-V., Le, H.-Q., Oellrich, A., Kawazoe, A., Hall-May, M., & Rebholz‐Schuhmann, D. (2012) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-69224 · Cited by 8

Biomechanisms of Comorbidity: Reviewing Integrative Analyses of Multi-omics Datasets and Electronic Health Records

Pouladi, N., Achour, L., Li, H., Berghout, J., Kenost, C., Gonzalez‐Garay, M. L., & Lussier, Y. A. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-040 · Cited by 8

Integrating genealogy and dental variation: contributions to biological anthropology

Paul, K. S., Feezell, R., Hughes, T. E., & Brook, A. H. (2022) · American Journal of Biological Anthropology · doi:10.1002/ajpa.24662 · Cited by 7

Phenome Centers and Global Harmonization

Chitayat, S., & Rudan, J. F. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800344-2.00010-0 · Cited by 7

A Conceptual Modeling Approach To Improve Human Genome Understanding

Pastor, Ó., Levín, A. M., Casamayor, J. C., Celma, M., & van der Kroon, M. (2011) · Springer eBooks · doi:10.1007/978-3-642-15865-0_16 · Cited by 7

Biobanking across the phenome - at the center of chronic disease research

Imboden, M., & Probst-Hensch, N. M. (2013) · BMC Public Health · doi:10.1186/1471-2458-13-1094 · Cited by 7

A resource to acquire and summarize pharmacogenetics knowledge in the literature.

Rubin, D. L., Whirl‐Carrillo, M., Woon, M., Conroy, J. M., Klein, T. E., & Altman, R. B. (2004) · PubMed · Cited by 7

The Emergence of a New Paradigm of Pharmacogenomics

Flordellis, C. S. (2005) · Pharmacogenomics · doi:10.2217/14622416.6.5.515 · Cited by 7

Cognitive Phenotypes and Endophenotypes: Concepts and Criteria

Bearden, C. E., Winkler, A. M., Karlsgodt, K. H., & Bilder, R. M. (2016) · Innovations in cognitive neuroscience · doi:10.1007/978-1-4614-3846-5_4 · Cited by 6

Phenotype analysis of congenital and neurodevelopmental disorders in the next generation sequencing era

Carey, J. C. (2017) · American Journal of Medical Genetics Part C Seminars in Medical Genetics · doi:10.1002/ajmg.c.31568 · Cited by 6

An Integrative Network Approach to Map the Transcriptome to the Phenome

Mehan, M. R., Nunez-Iglesias, J., Kalakrishnan, M., Waterman, M. S., & Zhou, X. J. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-78839-3_20 · Cited by 6

Translational Bioinformatics for Genomic Medicine

Butte, A. J., & Chen, D. P. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-382227-7.00023-9 · Cited by 6

Genomics

Ball, D., Pembrey, M. E., & Stephens, D. (2007) · Elsevier eBooks · doi:10.1016/b978-012370624-9/50007-4 · Cited by 6

Phenotyping in the era of genomics: MaTrics—a digital character matrix to document mammalian phenotypic traits

Stefen, C., Wagner, F., Asztalos, M., Giere, P., Grobe, P., Hiller, M., Hofmann, R., Jähde, M., Lächele, U., Lehmann, T., et al. (2022) · Mammalian Biology · doi:10.1007/s42991-021-00192-5 · Cited by 5

Brains and Education: Towards Neurocognitive Phenomics

Duch, W. (2013) · Nicolaus Copernicus University Repository (Nicolaus Copernicus University) · Cited by 6

Genetics of Psychiatric Disorders

Nürnberger, J. I., Berrettini, W., & Niculescu, A. B. (2016) · Springer eBooks · doi:10.1007/978-1-4939-2528-5_29 · Cited by 6

Translating knowledge into practice in the "post-genome" era

Scriver, C. R. (2004) · Acta Paediatrica · doi:10.1080/08035250310024682 · Cited by 6

Cognitive phenomics

Bilder, R. M., Poldrack, R. A., Parker, D. S., Reise, S. P., Jentsch, J. D., Cannon, T. D., London, E. D., Sabb, F. W., Foland‐Ross, L. C., Rizk‐Jackson, A., et al. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511642197.022 · Cited by 5

Phenotype Extraction Based on Word Embedding to Sentence Embedding Cascaded Approach

Xing, W., Yuan, X., Li, L., Hu, L., & Peng, J. (2018) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2018.2838137 · Cited by 5

The Origin of Foresight

Amsteus, M. (2012) · World Futures · doi:10.1080/02604027.2012.693853 · Cited by 5

Only connect: personal genomics and the future of American medicine.

Angrist, M. H. (2010) · PubMed · doi:10.2165/11534710-000000000-00000 · Cited by 5

Introduction to “Phenomics”

Hancock, J. M. (2014) · CRC Press eBooks · doi:10.1201/b16437-4 · Cited by 5

Phenomics Research on Coronary Heart Disease Based on Human Phenotype Ontology

Shi, Q. W., Gao, K., Zhao, H., Wang, J., Zhai, X., Lu, P., Chen, J., & Wang, W. (2014) · BioMed Research International · doi:10.1155/2014/240284 · Cited by 4

Digital Candidate Gene Approach (DigiCGA) for Identification of Cancer Genes

Zhu, M., Li, X., & Zhao, S. (2010) · Methods in molecular biology · doi:10.1007/978-1-60761-759-4_7 · Cited by 4

Only Connect

Angrist, M. H. (2010) · Molecular Diagnosis & Therapy · doi:10.1007/bf03256355 · Cited by 7

Manifold-based learning for high-throughput single-peanut phenotyping

Peng, W.-K., Lin, X., Deng, P., Jiang, J., Ding, C., & Yuan, S.-J. (2026) · npj Systems Biology and Applications · doi:10.1038/s41540-026-00688-1 · Cited by 3

First decade of post-genomic era. Hopes, disappointments, new answers

Kosztolányi, G. (2010) · Orvosi Hetilap · doi:10.1556/oh.2010.29014 · Cited by 3

The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases

Koebbe, L. L., Hess, T., Giel, A.-S., Bigge, J., Gehlen, J., Schueller, V., Geppert, M., Dumoulin, F. L., Heller, J., Schepke, M., et al. (2024) · Physiological Genomics · doi:10.1152/physiolgenomics.00120.2023 · Cited by 4

Les promesses des sciences omiques à l’ère de la médecine de précision

Tebani, A., & Bekri, S. (2022) · La Revue de Médecine Interne · doi:10.1016/j.revmed.2022.07.009 · Cited by 7

Creating High-Quality Synthetic Health Data: Framework for Model Development and Validation

Sichani, E. K., Smith, A. M., Emam, K. E., & Mosquera, L. (2024) · JMIR Formative Research · doi:10.2196/53241 · Cited by 3

Information Technology

Murphy, S. N., Chueh, H. C., & Herrick, C. D. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-802101-9.00013-2 · Cited by 3

Fenotipos clínicos en enfermedad pulmonar obstructiva crónica: ¿volver al futuro?

Rafael Silva, O. (2012) · Revista médica de Chile · doi:10.4067/s0034-98872012000700016 · Cited by 3

A Critical Need for Clinical Context in the Genomic Era

MacRae, C. A. (2015) · Circulation · doi:10.1161/circulationaha.115.018371 · Cited by 3

Experiential Learning Styles and Neurocognitive PhenomicsPreprint

Duch, W. (2020) · doi:10.31234/osf.io/s3te7 · Cited by 3

Vaccine hesitancy for COVID-19 explored in a phenomic study of 259 socio-cognitive-behavioural measures in the UK-REACH study of 12,431 UK healthcare workersPreprint

McManus, I. C., Woolf, K., Martin, C., Nellums, L. B., Guyatt, A. L., Melbourne, C., Bryant, L., Gupta, A., John, C., Tobin, M. D., et al. (2021) · medRxiv · doi:10.1101/2021.12.08.21267421 · Cited by 3

WayStation to HUGOBase

(2005) · Nature Genetics · doi:10.1038/ng0805-783 · Cited by 3

Modular organization of the human disease genes: a text-based network inference

Xuan, H., Li, X., & Ren, S. (2015) · Bioinformation · doi:10.6026/97320630011432 · Cited by 2

Structured Genome-Scale Variant and Clinical Data Reporting for Meta-Analysis in an Era of Genomic Medicine

Dinwiddie, D. L., Saunders, C., Farrow, E., Soden, S. E., Miller, N., & Kingsmore, S. F. (2013) · Journal of Genomes and Exomes · doi:10.4137/jge.s10180 · Cited by 2

Addressing the Complexity of COPD

Agustí, A. G. N., Sobradillo, P., & Celli, B. R. (2010) · Cited by 2

COPD

MacNee, W., Vestbo, J., & Agustí, A. G. N. (2015) · Elsevier eBooks · doi:10.1016/b978-1-4557-3383-5.00043-9 · Cited by 2

Cascade word embedding to sentence embedding: A class label enhanced approach to phenotype extraction

Xing, W., Yuan, X., Li, L., & Peng, J. (2017) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2017.8217694 · Cited by 2

High-throughput omics in the precision medicine ecosystem

Tebani, A., & Bekri, S. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-819178-1.00003-4 · Cited by 5

Bipolar Disorder

Fears, S. C., & Reus, V. I. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-410529-4.00104-2 · Cited by 2

Introduction to “Phenomics”

(2014) · CRC Press eBooks · doi:10.1201/b16437-2 · Cited by 2

Nucleic Acids Research Advance Access published September 28, 2006 PhenomicDB: a new cross-species genotype/phenotype resource

Groth, P., Pavlova, N., Kalev, I., Tonov, S., Georgiev, G., Pohlenz, H.-D., & Weiss, B. (2006)

PhenomicDB: a new cross-species genotype/phenotype resource. Nucleic acids research, 35(Database issue):D696–699. PMID

Groth, P., Pavlova, N., Kalev, I., Tonov, S., Georgiev, G., Pohlenz, H.-D., & Weiss, B. (2007)

PhenomicDB: a new cross-species genotype/phenotype resource. Nucleic acids research

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