68118-Huang, Xiaoqing

Xiaoqing Huang, PhD

Assistant Research Professor of Biostatistics & Health Data Science

Email
huanxi@iu.edu
Address
HITS, Office 3059

Indianapolis, IN
PubMed:

Bio

My research focuses on developing advanced statistical methodologies, machine learning models, and artificial intelligence techniques, including deep learning and large language models, to enhance the understanding of complex biological systems and advance drug development. I am trained in both theoretical and applied statistics during their doctoral studies at Indiana University, bringing additional expertise from prior roles at the U.S. Food and Drug Administration (FDA) and the National Institutes of Health (NIH).

I have a broad range of research projects spanning Alzheimer’s disease, oncology, and real-world data analytics. Besides, I am collaborating with Eli Lilly to support Phase III clinical trials, contributing statistical insight to ensure trial rigor and regulatory alignment.

Currently, my active research projects in method development involving longitudinal data modeling, text data mining, imaging biomarker identification, interpretability-enhanced AI, and multimodal data integration, which bridges statistical innovation with practical impact in clinical research and biomedical science.

 

Key Publications

  1. Huang X, Jannu A, Song Z, Garfe N, Lasagna-Reeves C, Jonhson T, Huang K, Zhang J. Predicting Alzheimer’s Disease Subtypes and Understanding Their Molecular Characteristics in Living Patients with Transcriptomic Trajectory Profiling. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2025 January. (IF: 13)
  2. Huang X, Raza Muneer Ahemad Hullur A, Jafari E, Shridhar K, Huang K, Mackie K, Zhou M, Wang Y. Leveraging Transcription Factor Physical Proximity for Enhancing Gene Regulation Inference. ISMB/ECCB 2025. 2025 May.
  3. Huang X, Ang A, Huang K, Zhang J, Wang Y. Inhomogeneous graph trend filtering via a l{2,0} norm cardinality penalty. IEEE Transactions on Signal and Information Processing over Networks. 2025 March.
  4. Huang X, Huang K, Johnson T, Radovich M, Zhang J, Ma J, Wang Y. ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways. NAR Genom Bioinform. 2021 Dec;3(4):lqab097. doi: 10.1093/nargab/lqab097. eCollection 2021 Dec. PubMed PMID: 34729476; PubMed Central PMCID: PMC8557386.
  5. Huang X*, Wojtowicz D*, Sason I*, Kim YA, Leiserson MDM, Przytycka TM, Sharan R. Hidden Markov models lead to higher resolution maps of mutation signature activity in cancer. Genome Med. 2019 Jul 26;11(1):49. doi: 10.1186/s13073-019-0659-1. PubMed PMID: 31349863; PubMed Central PMCID: PMC6660659. (IF: 15)
  6. Huang X*, Wojtowicz D*, Przytycka TM. Detecting presence of mutational signatures in cancer with confidence. Bioinformatics. 2018 Jan 15;34(2):330-337. doi: 10.1093/bioinformatics/btx604. PubMed PMID: 29028923; PubMed Central PMCID: PMC5860213. (Citation > 105)
  7. Li S, Liu J, Peyton M, Lazaro O, McCabe SD, Huang X, Liu Y, Shi Z, Zhang Z, Walker BA, Johnson TS. Multiple Myeloma Insights from Single-Cell Analysis: Clonal Evolution, the Microenvironment, Therapy Evasion, and Clinical Implications. Cancers (Basel). 2025 Feb 14;17(4). doi: 10.3390/cancers17040653. Review. PubMed PMID: 40002248; PubMed Central PMCID: PMC11852428.
  8. Song Z, Huang X, Jannu A, Johnson T, Zhang J, Huang K. Identify Alzheimer’s disease subtypes and markers from multi-omic data of human brain and blood with a subspace merging algorithm. International Conference on Intelligent Biology and Medicine. ICIBM 2024
  9. Wang Y, Zhou Y, Huang X, Huang K, Zhang J, Ma J. Learning Sparse Group Models Through Boolean Relaxation. 2024 International Conference on Learning Representations. 2024 May.
  10. Martinez P, Patel H, You Y, Jury N, Perkins A, Lee-Gosselin A, Taylor X, You Y, Viana Di Prisco G, Huang X, Dutta S, Wijeratne AB, Redding-Ochoa J, Shahid SS, Codocedo JF, Min S, Landreth GE, Mosley AL, Wu YC, McKinzie DL, Rochet JC, Zhang J, Atwood BK, Troncoso J, Lasagna-Reeves CA. Bassoon contributes to tau-seed propagation and neurotoxicity. Nat Neurosci. 2022 Dec;25(12):1597-1607. doi: 10.1038/s41593-022-01191-6. Epub 2022 Nov 7. PubMed PMID: 36344699; PubMed Central PMCID: PMC9708566.
  11. Taylor X, Cisternas P, Jury N, Martinez P, Huang X, You Y, Redding-Ochoa J, Vidal R, Zhang J, Troncoso J, Lasagna-Reeves CA. Activated endothelial cells induce a distinct type of astrocytic reactivity. Commun Biol. 2022 Mar 29;5(1):282. doi: 10.1038/s42003-022-03237-8. PubMed PMID: 35351973; PubMed Central PMCID: PMC8964703.
  12. Johnson TS, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Zaid MA, Huang X, Wang Y, Bartlett C, Zhang Y, Walker BA, Liu Y, Huang K, Zhang J. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease. Genome Med. 2022 Feb 1;14(1):11. doi: 10.1186/s13073-022-01012-2. PubMed PMID: 35105355; PubMed Central PMCID: PMC8808996. 
  13. Martinez P, Patel H, You Y, Garfe N, Perkins A, You Y, Huang X, Dutta S, Wijeratne A, Redding J, Mosley A, Rochet C, Zhang J, Troncoso J, Lasagna-Reeves C. Pathological tau interactors and their role in propagation and neurodegeneration. Alzheimer's & Dementia. 2022.
  14. Chai G, Huang X, Ma Y, Mehta S, Radin R, Ready T, Soon J, Wittayanukorn S, Woods C, Zhao Y. Generating Real-World Evidence for Prescription Opioid Use with Geographically Referenced Data Enrichment and Machine Learning. American Statistical Association (ASA) Biopharmaceutical Section. 2019.

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