| Cheng Y. Gan | |
|---|---|
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| Affiliations | National University of Singapore |
| Country | Singapore |
| H-index | 60 |
| Research Focus | [Alzheimer's Disease](/diseases/alzheimers) |
| Mechanisms | [Tau](/mechanisms/tau-pathology), [Neuroinflammation](/mechanisms/neuroinflammation) |
Cheng Y. Gan is a leading researcher in the field of neurodegenerative diseases, affiliated with National University of Singapore. Their research focuses on Tau, Neuroinflammation, with particular emphasis on Alzheimer's Disease. With an h-index of 60, Gan is among the most cited researchers in the neuroscience field[1].
Gan's work spans multiple aspects of neurodegeneration, contributing to our understanding of the molecular mechanisms that underlie diseases such as Alzheimer's Disease. Their research group has made significant contributions to the fields of Tau, Neuroinflammation, publishing in high-impact journals including leading neuroscience journals.
Based at National University of Singapore, Gan collaborates with researchers across multiple institutions worldwide, working to advance therapeutic strategies for neurodegenerative conditions.
Gan's portfolio emphasizes mechanism-aware biomarker interpretation and translational hypothesis testing in Alzheimer's Disease[2]. Their group typically links molecular process readouts to clinically meaningful outcomes, including cognitive trajectories, motor phenotypes, and disease staging endpoints when relevant[3].
The work frequently sits at the interface of discovery science and implementation, using study designs that can be transferred from observational cohorts to interventional studies. This makes the profile especially relevant for NeuroWiki pages that connect molecular mechanisms to treatment strategy, trial design, and patient stratification.
Within the Tau, Neuroinflammation domain, this research profile is most aligned with multimodal integration: combining imaging, biofluid, genomic, and clinical metadata to derive robust disease signatures. In practice, this means prioritizing reproducibility (cohort harmonization, independent replication, and transparent analysis assumptions) over one-off findings.
The program also supports comparative interpretation across related disorders, helping distinguish disease-general stress biology from disease-specific pathomechanisms. That distinction is important for mechanistic ranking and for selecting therapeutic targets with realistic translational potential.
For NeuroWiki readers, the translational value of this researcher profile lies in three areas: first, operationalizing mechanism-informed biomarkers for diagnosis and progression tracking; second, identifying patient subgroups most likely to respond to targeted interventions; and third, connecting preclinical hypotheses to trial-ready outcome frameworks.
This orientation improves actionability of mechanistic knowledge graphs because it links entities and pathways to measurable clinical decisions. Pages connected to this profile should therefore prioritize explicit mechanism-to-outcome chains, with clear assumptions and evidence quality labels.
Collaborator network pending enrichment.
Primary institutional links: National University of Singapore. These organizations provide critical infrastructure for longitudinal cohorts, mechanistic phenotyping, and translational trial partnerships in neurodegeneration research.