University of Pennsylvania · Mathematics & StatisticsAlzheimer's Drug Discovery Lab
Li Shen · Philadelphia, Pennsylvania
Research Focus
Li Shen's research lab focuses on using innovative data analytic techniques to help find new treatments for Alzheimer's disease. By leveraging advanced machine learning and bioinformatics approaches, the lab aims to analyze large-scale medical data to identify promising drug candidates for repurposing. This work has the potential to improve our understanding of Alzheimer's and contribute to better clinical outcomes for affected individuals.
Alzheimer's DiseaseDrug RepurposingMachine LearningBioinformaticsBig DataMulti-OmicsTranslational ResearchClinical DataNeurobiologyPublic Health
Research Aims
4AIM 01Develop multi-omics data integration methods to identify genes and pathways for drug repositioning in Alzheimer's disease.
AIM 02Create strategies to evaluate candidate targets using associations with AD biomarkers and patient phenotypes.
AIM 03Implement network reinforcement methods to identify potential AD drugs.
AIM 04Assess the identified drugs for repurposing potential using diverse clinical data sources.
Skills the Lab Values
Data IntegrationMachine Learning TechniquesDeep Learning MethodsBioinformatics SoftwareStatistical AnalysisNetwork AnalysisPharmacological Data EvaluationElectronic Health Records AnalysisCognitive Data AnalysisGenetic Data Interpretation
Output against the department
Publications86bottom 12% of dept.115th of 131
this lab
most publishedleast published
Citations45ktop 11% of dept.14th of 131
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.