Bioinformatics and Machine Learning Strategies for Brain Imaging Genomics
Imaging genomics is an emerging data science field, where integrative analysis of imaging and omics data is performed to provide new insights into the phenotypic characteristics and genetic mechanisms of normal or disordered biological structures and functions, and to impact the development of new diagnostic, therapeutic and preventative approaches. However, due to the unprecedented scale and complexity of these data sets, this field is facing major computational and bioinformatics challenges. In this talk, using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project as an example, we will discuss fundamental concepts, state-of-the-art bioinformatics and machine learning methods, and innovative applications in this young and rapidly evolving field. We show that the broad availability and wide scope of imaging genomics data, coupled with advances in biomedical informatics and computing, have the potential to significantly contribute to multiple US and worldwide health priority areas.