Dissecting the shared genetic architecture of psychiatric and psychological traits with application to prediction of genetic risk. Identification of the early phase of psychiatric disorders is considered critical for early intervention which is the essence of prevention. At present, the main obstacle to targeted early intervention strategies in psychiatric disorders is the non-specific nature of early stage symptoms. Many psychiatric disorders present with symptoms of depressed mood and anxiety ....Dissecting the shared genetic architecture of psychiatric and psychological traits with application to prediction of genetic risk. Identification of the early phase of psychiatric disorders is considered critical for early intervention which is the essence of prevention. At present, the main obstacle to targeted early intervention strategies in psychiatric disorders is the non-specific nature of early stage symptoms. Many psychiatric disorders present with symptoms of depressed mood and anxiety in the early stages, yet best intervention treatments are dependent on the final (unknown) diagnosed disorder. Prediction of genetic risk is likely to make an important contribution for identification of individuals at risk of specific psychiatric disorders so that the best early intervention treatment can be administered. Read moreRead less
New statistical methods for identifying micro-ribonucleic acid (miRNA) regulatory networks. Understanding gene regulatory networks is critical in the understanding of fundamental biological systems. These networks have important implications for the discovery of fundamental mechanisms relating to the diagnosis and management of many illnesses. This research will provide new statistical methods to identify regulatory micro-ribonucleic acid modules and to understand their relationship in gene regu ....New statistical methods for identifying micro-ribonucleic acid (miRNA) regulatory networks. Understanding gene regulatory networks is critical in the understanding of fundamental biological systems. These networks have important implications for the discovery of fundamental mechanisms relating to the diagnosis and management of many illnesses. This research will provide new statistical methods to identify regulatory micro-ribonucleic acid modules and to understand their relationship in gene regulatory networks through multiple covariance estimation and multivariate classification techniques. My results should enable researchers to better understand the regulation underlying biological systems, leading to improved human health, medical and biological research outcomes.Read moreRead less