There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
Principal Investigator | |
Principal Investigator's Name: | Kun Huang |
Institution: | Indiana University School of Medicine |
Department: | Hematology Oncology |
Country: | |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Additional Investigators | |
Investigator's Name: | Yi Zhao |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Huanmei Wu |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Sha Cao |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Chi Zhang |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Jun Wan |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Xiaowen Liu |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Jie Zhang |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Zhi Han |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Jie Zhang |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |
Investigator's Name: | Li Chen |
Proposed Analysis: | Understanding disease pathology, identifying biological markers and suggesting early diagnosis and intervention strategies are critically important in AD research. In the project, we aim to use ADNI data to develop methodologies to gain better knowledge about the role of different data modalities in disease development and progression by integrating genomics, proteomics/metabolomics, neuroimaging and clinical data. In addition, in AD research, it is important to investigate longitudinal trajectories of variations in metabolism, brain structure and function, and neuropsychological behaviors. We propose to use ADNI data to develop novel methodologies to analyze longitudinal data. |