Results 151 to 160 of about 1,154,991 (281)

Estimation of the Gene-Environment Interaction in Breast Cancer Patients

مجله اپیدمیولوژی ایران, 2006
Background and objectives: There is growing interest in assessing gene-environment interaction in the course of case-control studies. Difficulties related to the sampling of controls have led to the development of a range of non-traditional methods that
P Yavari, MA Pourhosseingholi
doaj  

Inferring Gene-by-Environment Interactions with a Bayesian Whole-Genome Regression Model [PDF]

, 2020
Matthew Kerin, Jonathan Marchini
openalex   +1 more source

Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure [PDF]

, 2022
Preethi Thunga, Lisa Truong, Yvonne Rericha, Jane K. La Du, Mackenzie Morshead, Robert L. Tanguay, David M. Reif   +6 more
openalex   +1 more source

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

Molecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg, Joachim von Braun, Julio Celis, Anton Berns, Michael Baumann, Tit Albreht, Nancy Abou‐Zeid, Vanderlei Bagnato, Christian Brandts, Chien‐Jen Chen, Massimiliano di Pietro, Manjit Dosanjh, Thomas Dubois, Alexander Eggermont, Angelika Eggert, Ingemar Ernberg, Sara Faithfull, Johannes Förner, Stefan Fröhling, Manuel Heitor, Leroy Hood, Wei Jiang, Bengt Jönsson, Ravi Kannan, Maria Leptin, Su Li, Peter Lindgren, Douglas Lowy, Jun Ma, Alex Markham, Péter Nagy, Simon Oberst, M. Iqbal Parker, Danielle Rodin, Kevin Ryan, Joachim Schüz, Richard Sullivan, Josep Tabernero, Peter Turkson, Oliver Várhelyi, Harold Varmus, Chijie Wang, Elisabete Weiderpass, Nils Wilking   +43 more
wiley   +1 more source

Gene-environment interaction and personality/behaviour

Annals of General Psychiatry, 2006
Göktürk Camilla, Wargelius Hanna, Olerud Ingrid, Sjöberg Rickard, Nilsson Kent, Lindström Leif, Hallman Jarmila, Oreland Lars, Öhrvik John, Leppert Jerzy   +9 more
doaj   +1 more source

Role of Maternal Obesity in Offspring Cardiovascular Development and Congenital Heart Defects

Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Background Congenital heart disease is a leading cause of death in newborns, yet many of its molecular mechanisms remain unknown. Both maternal obesity and diabetes increase the risk of congenital heart disease in offspring, with recent studies ...
Ashleigh McMullan, James B. Zwierzynski, Nina Jain, Laura S. Haneline, Weinian Shou, Kok Lim Kua, Swetansu K. Hota, Matthew D. Durbin   +7 more
doaj   +1 more source

Additional file 3: ExampleData_GxE_1.01_210corr_840noise. of Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression

, 2017
Anke Hüls, Katja Ickstadt, Tamara Schikowski, Ursula Krämer   +3 more
openalex   +1 more source

Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma

Molecular Oncology, EarlyView.
Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken, Andrea Abel Gutierrez, Imke van Rossum, Cornelia G. Spruijt, Michiel Vermeulen, Guido van Mierlo, Blanca Scheijen, Annemiek B. van Spriel   +7 more
wiley   +1 more source

Educational Tracking and the Polygenic Prediction of Education

Sociological Science
Educational systems that separate students into curriculum tracks later may place less emphasis on socioeconomic family background and allow individuals' personal skills and interests more time to manifest.
Hannu Lahtinen, Pekka Martikainen, Kaarina Korhonen, Tim Morris   +3 more
doaj   +1 more source

Varying coefficient model for gene–environment interaction: a non-linear look [PDF]

, 2011
Shujie Ma, Lijian Yang, Roberto Romero, Yuehua Cui   +3 more
openalex   +1 more source