| P50 | author | Scott M Williams | Q47430724 |
| | Melinda C. Aldrich | Q88947663 |
| | Carmen Marsit | Q37378932 |
| P2093 | author name string | Robert A Hiatt | |
| | Timothy H Ciesielski | |
| P2860 | cites work | Vitamin C for preventing and treating the common cold | Q24201652 |
| | Replication in Genome-Wide Association Studies | Q24288830 |
| | Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors | Q24288911 |
| | Transforming Epidemiology for 21st Century Medicine and Public Health | Q24289006 |
| | Integrative cancer epidemiology--the next generation | Q24594622 |
| | Genome-wide and fine-resolution association analysis of malaria in West Africa | Q24632119 |
| | Transdisciplinary translational behavioral (TDTB) research: opportunities, barriers, and innovations | Q26751401 |
| | Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes | Q28680760 |
| | Genome-wide association study indicates two novel resistance loci for severe malaria | Q28943391 |
| | A four-phase model of transdisciplinary team-based research: goals, team processes, and strategies | Q29011228 |
| | A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants | Q29547210 |
| | Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels | Q29547214 |
| | Maternal pesticide exposure from multiple sources and selected congenital anomalies | Q29615590 |
| | A generalized combinatorial approach for detecting gene-by-gene and gene-by-environment interactions with application to nicotine dependence | Q30443642 |
| | Medicine. Big data meets public health | Q30872287 |
| | Marshall and Galea respond to "data theory in epidemiology". | Q30875063 |
| | Invited commentary: Agent-based models for causal inference—reweighting data and theory in epidemiology | Q30875068 |
| | Children's Environmental Health: A Brief History | Q31010465 |
| | Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity | Q33185819 |
| | Failure to replicate a genetic association may provide important clues about genetic architecture | Q33463308 |
| | Modeling of environmental effects in genome-wide association studies identifies SLC2A2 and HP as novel loci influencing serum cholesterol levels | Q33523269 |
| | DNA repair polymorphisms modify bladder cancer risk: a multi-factor analytic strategy | Q33802272 |
| | Systematic review and evidence integration for literature-based environmental health science assessments | Q33840915 |
| | Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer | Q33951229 |
| | Characterizing genetic interactions in human disease association studies using statistical epistasis networks | Q34017084 |
| | Causal thinking and complex system approaches in epidemiology | Q34029885 |
| | Multiple analytical approaches reveal distinct gene-environment interactions in smokers and non smokers in lung cancer | Q34113745 |
| | Gene-gene and gene-environmental interactions of childhood asthma: a multifactor dimension reduction approach. | Q34166205 |
| | Validated context-dependent associations of coronary heart disease risk with genotype variation in the chromosome 9p21 region: the Atherosclerosis Risk in Communities study | Q34180975 |
| | Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis | Q34328362 |
| | A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits | Q34353866 |
| | Formalizing the role of agent-based modeling in causal inference and epidemiology. | Q43178348 |
| | Human microbiome visualization using 3D technology. | Q44071172 |
| | Is epidemiology correcting its vision problem? A perspective on our perspective: 2012 presidential address for American College of Epidemiology. | Q44150302 |
| | A multilevel model of postmenopausal breast cancer incidence. | Q44319574 |
| | Promoting innovation and creativity in epidemiology for the 21st century | Q46092356 |
| | Epidemiology: key to translational, team, and transdisciplinary science | Q46191678 |
| | Toward a transdisciplinary understanding and a global control of emerging infectious diseases | Q46271935 |
| | The birth weight "paradox" uncovered? | Q46341172 |
| | The science of team science: overview of the field and introduction to the supplement | Q46510271 |
| | Tools for innovative thinking in epidemiology. | Q50956852 |
| | Analysis of multiple SNPs in genetic association studies: comparison of three multi-locus methods to prioritize and select SNPs. | Q51910939 |
| | Invited commentary: The virtual epidemiologist—promise and peril. | Q53669244 |
| | MDR and PRP: A Comparison of Methods for High-Order Genotype-Phenotype Associations | Q57428591 |
| | Problems with Genome-Wide Association Studies | Q59192517 |
| | The association of polymorphisms in 5-fluorouracil metabolism genes with outcome in adjuvant treatment of colorectal cancer | Q61088814 |
| | Causes | Q67875197 |
| | Causal diagrams for epidemiologic research | Q77794178 |
| | It's not easy being interdisciplinary | Q80304673 |
| | Integrating social and biologic factors in health research: a systems view | Q80440893 |
| | Problems with genome-wide association studies | Q80554408 |
| | The role of the epidemiologist in clinical and translational science | Q83220425 |
| | Methodological innovations in public health education: transdisciplinary problem solving | Q86808397 |
| | Proceedings of the second international molecular pathological epidemiology (MPE) meeting | Q34475686 |
| | ViSEN: methodology and software for visualization of statistical epistasis networks | Q34610905 |
| | The increasing dominance of teams in production of knowledge | Q34618686 |
| | Pioneering the Transdisciplinary Team Science Approach: Lessons Learned from National Cancer Institute Grantees | Q34789248 |
| | A modified entropy-based approach for identifying gene-gene interactions in case-control study | Q34853867 |
| | Influence of environmental exposure on human epigenetic regulation | Q34864517 |
| | Eco-bio-social research on community-based approaches for Chagas disease vector control in Latin America | Q34986702 |
| | Causal models in epidemiology: past inheritance and genetic future | Q35012051 |
| | The potential of transdisciplinary research for sustaining and extending linkages between the health and social sciences | Q35586058 |
| | Preparing Emerging Doctoral Scholars for Transdisciplinary Research: A Developmental Approach | Q35633872 |
| | Maternal psychiatric disease and epigenetic evidence suggest a common biology for poor fetal growth | Q35754231 |
| | Computational analysis of gene-gene interactions using multifactor dimensionality reduction | Q35938533 |
| | Multilocus analysis of atopy in Korean children using multifactor-dimensionality reduction | Q36225622 |
| | Integration of molecular pathology, epidemiology and social science for global precision medicine | Q36463854 |
| | "Toward a clearer definition of confounding" revisited with directed acyclic graphs | Q36489218 |
| | "Drivers" of translational cancer epidemiology in the 21st century: needs and opportunities | Q36589104 |
| | The PAH gene, phenylketonuria, and a paradigm shift | Q36795399 |
| | Diabetes genes identified by genome-wide association studies are regulated in mice by nutritional factors in metabolically relevant tissues and by glucose concentrations in islets | Q36877444 |
| | Lead neurotoxicity and socioeconomic status: conceptual and analytical issues | Q36953497 |
| | An information-gain approach to detecting three-way epistatic interactions in genetic association studies | Q37039893 |
| | Caring for children with phenylketonuria | Q37095892 |
| | A new tool for epidemiology: the usefulness of dynamic-agent models in understanding place effects on health | Q37163750 |
| | Curses--winner's and otherwise--in genetic epidemiology | Q37243708 |
| | No-boundary thinking in bioinformatics research | Q37308031 |
| | Social epidemiology: social determinants of health in the United States: are we losing ground? | Q37586394 |
| | Implications of the exposome for exposure science | Q37809970 |
| | Correcting away the hidden heritability | Q37864684 |
| | L.E.A.D.: a framework for evidence gathering and use for the prevention of obesity and other complex public health problems | Q38115768 |
| | Micronutrient status in phenylketonuria. | Q38151456 |
| | Epigenetic epidemiology of cancer | Q38240033 |
| | Invited commentary: driving for further evolution | Q38376284 |
| | Future research perspectives on environment and health: the requirement for a more expansive concept of translational cancer research | Q39760740 |
| | Expectations and challenges stemming from genome-wide association studies | Q40051982 |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | transdisciplinarity | Q249542 |
| P304 | page(s) | 123-134 | |
| P577 | publication date | 2016-11-10 | |
| P1433 | published in | Translational Research | Q15761127 |
| P1476 | title | Transdisciplinary approaches enhance the production of translational knowledge | |
| P478 | volume | 182 | |