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Michael C. Neale

Researcher at Virginia Commonwealth University

Publications -  647
Citations -  72612

Michael C. Neale is an academic researcher from Virginia Commonwealth University. The author has contributed to research in topics: Twin study & Population. The author has an hindex of 121, co-authored 620 publications receiving 66343 citations. Previous affiliations of Michael C. Neale include VU University Amsterdam & University of East London.

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Associations between ovarian hormones and emotional eating across the menstrual cycle: Do ovulatory shifts in hormones matter?

TL;DR: In aggregate, the current findings and past data suggest that hormone levels are more significant predictors of EE than pronounced hormonal changes across the menstrual cycle.
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The genetic covariation between fear conditioning and self-report fears.

TL;DR: Experimentally derived fear conditioning measures share only a small portion of the genetic factors underlying individual differences in subjective fears, cautioning against relying too heavily on the former as an endophenotype for genetic studies of phobic disorders.
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Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation

TL;DR: A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data, and these results are used to develop a quantitative framework to understand the immunobiology of transplantation.
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Level of family dysfunction and genetic influences on smoking in women.

TL;DR: It is suggested that heritability of CS decreased rather than increased with higher levels of dysfunction in the family of origin, suggesting the hypothesis that genetic effects for psychiatric and drug-use disorders become stronger in more adverse environments is not universally true.
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Multiple Regression With Data Collected From Relatives: Testing Assumptions of the Model.

TL;DR: This model is extended to cover data collected from relatives, where the observations are not independent and further extensions of the model are developed that permit tests of several assumptions implicit in multiple regression.