<table class="infobox infobox-researcher">
<tr>
<th class="infobox-header" colspan="2">Hongkui Zeng</th>
</tr>
<tr>
<td class="infobox-image" colspan="2">
<em>Photo placeholder</em>
</td>
</tr>
<tr>
<td class="label">Affiliations</td>
<td>Allen Institute for Brain Science</td>
</tr>
<tr>
<td class="label">Country</td>
<td>USA</td>
</tr>
<tr>
<td class="label">H-index</td>
<td>120</td>
</tr>
<tr>
<td class="label">Research Focus</td>
<td>[Alzheimer's Disease](/diseases/alzheimers)</td>
</tr>
<tr>
<td class="label">Mechanisms</td>
<td>Cell Types, Transcriptomics, Connectomics, Brain Development</td>
</tr>
</table>
Hongkui Zeng
Overview
Hongkui Zeng is a leading researcher in the field of neurodegenerative diseases, affiliated with Allen Institute for Brain Science. Their research focuses on Cell Types, Transcriptomics, Connectomics, Brain Development, with particular emphasis on Alzheimer's Disease. With an h-index of 120, Zeng is among the most cited researchers in the neuroscience field[@google2026].
Zeng'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 Cell Types, Transcriptomics, Connectomics, Brain Development, publishing in high-impact journals including Nature.
...<table class="infobox infobox-researcher">
<tr>
<th class="infobox-header" colspan="2">Hongkui Zeng</th>
</tr>
<tr>
<td class="infobox-image" colspan="2">
<em>Photo placeholder</em>
</td>
</tr>
<tr>
<td class="label">Affiliations</td>
<td>Allen Institute for Brain Science</td>
</tr>
<tr>
<td class="label">Country</td>
<td>USA</td>
</tr>
<tr>
<td class="label">H-index</td>
<td>120</td>
</tr>
<tr>
<td class="label">Research Focus</td>
<td>[Alzheimer's Disease](/diseases/alzheimers)</td>
</tr>
<tr>
<td class="label">Mechanisms</td>
<td>Cell Types, Transcriptomics, Connectomics, Brain Development</td>
</tr>
</table>
Hongkui Zeng
Overview
Hongkui Zeng is a leading researcher in the field of neurodegenerative diseases, affiliated with Allen Institute for Brain Science. Their research focuses on Cell Types, Transcriptomics, Connectomics, Brain Development, with particular emphasis on Alzheimer's Disease. With an h-index of 120, Zeng is among the most cited researchers in the neuroscience field[@google2026].
Zeng'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 Cell Types, Transcriptomics, Connectomics, Brain Development, publishing in high-impact journals including Nature.
Based at Allen Institute for Brain Science, Zeng collaborates with researchers across multiple institutions worldwide, working to advance therapeutic strategies for neurodegenerative conditions.
Research Focus
Disease Areas
- [Alzheimer's Disease](/diseases/alzheimers-disease)
Mechanisms of Interest
- Cell Types
- Transcriptomics
- Connectomics
- Brain Development
Programmatic Emphasis
Zeng's portfolio emphasizes mechanism-aware biomarker interpretation and translational hypothesis testing in Alzheimer's Disease[@long2019]. Their group typically links molecular process readouts to clinically meaningful outcomes, including cognitive trajectories, motor phenotypes, and disease staging endpoints when relevant.
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.
Methods and Data Strategy
Within the Cell Types, Transcriptomics, Connectomics, Brain Development 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.
Translational Relevance
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.
Key Publications
[A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain](https://doi.org/10.1038/s41586-023-06812-z). Nature, 2023.[@highresolution2023]
[Brain-wide cell-type-specific transcriptomic signatures of healthy ageing in mice](https://pubmed.ncbi.nlm.nih.gov/?term=Brain-wide+cell-type-specific+transcriptomic+signatures+of+healthy+ageing+in+mice). Nature, 2025.[@brainwide2025]
Recent Research
Recent PubMed-indexed publications (2024-present):
[Analysis of the composition of Anshen Dingzhi Pill and its mechanism on improving cognitive impairment in sleep deprivation model rats.](https://pubmed.ncbi.nlm.nih.gov/41544731/). Journal of ethnopharmacology. 2026.
[Altered cerebral morphometry and individual-based morphological brain network in children with beta-thalassaemia major.](https://pubmed.ncbi.nlm.nih.gov/41619874/). Neuroscience. 2026.
[Discovery of Potent and Subtype-Selective α7 nAChR Antagonists for Organophosphate Poisoning Protection.](https://pubmed.ncbi.nlm.nih.gov/41774019/). Journal of medicinal chemistry. 2026.
[Meta-Learning Enhanced Multi-Source Domain Adaptation for zero-calibration motor imagery EEG decoding.](https://pubmed.ncbi.nlm.nih.gov/41825840/). Journal of neuroscience methods. 2026.
Collaborators and Research Network
[Ed Lein](/researchers/ed-lein), [Christof Koch](/researchers/christof-koch), [Michael Hawrylycz](/researchers/michael-hawrylycz)
Institutional Context
Primary institutional links: [Allen Institute for Brain Science](/institutions/allen-institute-for-brain-science). These organizations provide critical infrastructure for longitudinal cohorts, mechanistic phenotyping, and translational trial partnerships in neurodegeneration research.
Open Questions and Future Directions
- How can Cell Types, Transcriptomics, Connectomics, Brain Development signals be standardized across cohorts and sites without losing disease-stage sensitivity?
- Which biomarker combinations best separate causal mechanism activity from downstream epiphenomena?
- What trial designs can most efficiently translate mechanistic findings in Alzheimer's Disease into clinically meaningful interventions?
External Links
- Google Scholar: [Search for Hongkui Zeng](https://scholar.google.com/scholar?q=author%3A%22Hongkui+Zeng%22)
- PubMed: [Author search for Hongkui Zeng](https://pubmed.ncbi.nlm.nih.gov/?term=Hongkui+Zeng%5BAuthor%5D)
See Also
- [Researchers and Institutions Index](/researchers)
- [Diseases Index](/diseases)
- [Mechanisms Index](/mechanisms)
References
[Unknown, A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain (2023)](https://doi.org/10.1038/s41586-023-06812-z)
Unknown, Brain-wide cell-type-specific transcriptomic signatures of healthy ageing in mice (2025)
Unknown, Google Scholar author search for Hongkui Zeng (2026)
[Unknown, Long and Holtzman, Alzheimer disease an update on pathobiology and treatment strategies 2019 (2019)](https://pubmed.ncbi.nlm.nih.gov/30617256/)