Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: To understand the relationship beten genomic variations among population and complex diseases, it is essential to detect eQTLs which are associated with phenotypic effects. Hover, detecting eQTLs remains a challenge due to complex underlying mechanisms and the very large number of genetic loci involved compared to the number of samples. Thus, to address the problem, it is desirable to take advantage of the structure of the data and prior information about genomic locations such as conservation scores and transcription factor binding sites.#R##N##R##N#,  propose a novel regularized regression approach for detecting eQTLs which takes into account related traits simultaneously while incorporating many regulatory features.  first present a Bayesian network for a multi-task learning problem that includes priors on SNPs, making it possible to estimate the significance of each covariate adaptively. Then  find the maximum a posteriori (MAP) estimation of regression coefficients and estimate ights of covariates jointly. This optimization procedure is efficient since it can be achieved by using a projected gradient descent and a coordinate descent procedure iteratively. Experimental results on simulated and real yeast datasets confirm that our model outperforms previous methods for finding eQTLs.
['Seunghak Lee', 'Jun Zhu', 'Eric P. Xing']
I am writing a research paper on a idea Adaptive Multi-Task Lasso: with Application to eQTL Detection
[{"from": "human", "value": "I am writing a research paper on a idea Adaptive Multi-Task Lasso: with Application to eQTL Detection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: To understand the relationship beten genomic variations among population and complex diseases, it is essential to detect eQTLs which are associated with phenotypic effects. Hover, detecting eQTLs remains a challenge due to complex underlying mechanisms and the very large number of genetic loci involved compared to the number of samples. Thus, to address the problem, it is desirable to take advantage of the structure of the data and prior information about genomic locations such as conservation scores and transcription factor binding sites.#R##N##R##N#,  propose a novel regularized regression approach for detecting eQTLs which takes into account related traits simultaneously while incorporating many regulatory features.  first present a Bayesian network for a multi-task learning problem that includes priors on SNPs, making it possible to estimate the significance of each covariate adaptively. Then  find the maximum a posteriori (MAP) estimation of regression coefficients and estimate ights of covariates jointly. This optimization procedure is efficient since it can be achieved by using a projected gradient descent and a coordinate descent procedure iteratively. Experimental results on simulated and real yeast datasets confirm that our model outperforms previous methods for finding eQTLs."}]