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Indiana University School of Medicine
Indiana University School of Medicine
Center for Computational Biology and Bioinformatics

Mentors

INGEN4DS scholars work alongside a mentorship team consisting of one faculty member conducting genomics-related wet lab research in the biomedical sciences and one computational faculty member using advanced bioinformatics and data science techniques.

If accepted to the program, you may conduct up to three rotations with the co-mentor teams of your choice before selecting a research lab to complete your research project.

INGEN4DS research mentors have a broad area of expertise and use genomics data in their research. Their general areas of research are highlighted below.

Mentor Research Area
Liana Apostolva, MS, MD, FAAN Early symptomatic and pre-symptomatic stages of Alzheimer's Disease, and development and validation of sensitive imaging and genetic biomarkers for Alzheimer's disease and other dementing disorders.
Wade Clapp, MD Understanding the cellular and molecular pathogenesis of genetic diseases with a predisposition to cancer, and identifying novel drug targets and experimental therapeutics.
Joan Cook-Mills, Ph.D Mechanisms for development of allergic disease, asthma and food allergy in neonates and children of allergic mothers.
Michael Eadon, MD, BA The translation and implementation of pharmacogenomics into clinical practice, the identification of novel predictors of renal injury from large genomic, transcriptomic, and proteomic datasets.
Howard Edenberg, PhD The genetics and genomics of complex genetic disorders, especially alcohol and other substance use disorders.
Carmella Evans-Molina, PhD, MS, MD Defining the molecular pathways of β-cell dysfunction that contribute to diabetes pathophysiology, and using “omics” approaches to identify novel serum biomarkers of early β-cell stress in pre-symptomatic type 1 diabetes.
Anthony Firulli, PhD Transcriptional mechanisms that control cell specification and differentiation of multi-potential cells. Modeling genetic mutations found in patients in vivo to deduce their contributions to congenital defects.
Melisa Fischel, PhD Tumor cell and its interaction with tumor microenvironment, Redox signaling, transcriptional regulation, DNA repair, pancreatic cancer
Tatiana Foroud, PhD Identification of genes contributing to a variety of complex disorders including Parkinson disease, Alzheimer disease, intracranial aneurysms, alcohol dependence, and cancer.
Eri Hashino, PhD Elucidating the epigenetic mechanisms underlying directed pluripotent stem cell differentiation to become sensory neurons and hair cells in the inner ear.
Takashi Hato, MD Investigating mechanisms of sepsis-induced acute kidney injury using advanced imaging along with multiomics analyses. 
Heather Hundley, PhD Post-transcriptional regulation of gene expression to identify the molecular mechanisms that regulate RNA editing and the consequences of aberrant editing on gene expression.
Mark Kaplan, PhD Understanding the transcriptional regulation of T helper cells as they regulate inflammatory immunity.
Rachel Katzenellenbogen, MD Human papillomavirus and the cancers associated with this infection.
Jungsu Kim, PhD Understanding the molecular and cellular basis of neuronal and glial dysfunction in Alzheimer’s disease, other aging-associated neurodegenerative diseases, and normal brain aging.
Bruce Lamb, PhD Alzheimer’s Disease, Animal Models, Microglia, Neuroinflammation, Neurodegeneration, Traumatic Brain Injury
Xiongbin Lu, PhD Cancer genomics, targeted cancer therapy, cancer immunotherapy and biomedical engineering.
Hui-chen Lu, PhD How activity-dependent processes during brain development fine-tune the establishment of neural circuits and how sensory experiences affect neural circuit wiring and cognitive behaviors.
Amber Mosley, PhD Regulation of RNA Polymerase II elongation and termination using systems level approaches including next-generation sequencing and protein mass spectrometry.
Harikrishina Nakshatri, PhD Use of single-cell analytics and spatial transcriptomics to study breast cancer resistance to therapy and identify therapeutic targets of breast cancer stem cells, and serum biomarkers of cancer progression.
Ken Nephew, PhD Use of next-generation sequencing approaches to study epigenetics, women’s cancers and how cancer stem cells contribute to recurrence and drug resistance.
Hongxia Ren, PhD Understand the molecular and genetic mechanisms in the brain that regulate metabolic  homeostasis and developing novel therapeutics for neurological and metabolic diseases.
Jamie Renbarger, MD Personalized medicine and pharmacogenomics in the treatment of childhood cancers.
Andy Saykin, MS, PsyD Network science and AI/machine learning for integrative analysis of multi-modal neuroimaging, multiomics biomarkers, and clinical/cognitive data in precision medicine for Alzheimer’s and other cognitive disorders of aging.
Chanden Sen, MS, PhD Tissue injury, repair, regeneration, and infection.
Todd Skarr, PhD Identifying and functionally testing genetic variants in the drug metabolism genes that are associated with clinical drug efficacy and toxicity.
Brian Walker, PhD Tumor-acquired genomic abnormalities, including translocations, copy number changes, and mutations that cause early relapse or progression of multiple myeloma (MM) and related plasma cell dyscrasias.
Stephanie Ware, MD, PhD Genetic and developmental basis of pediatric heart disease.
Lei Yang, PhD Utilizes human embryonic stem cells, induced pluripotent stem cells, mouse genetic models and tissue engineering approaches to study early-stage heart development, inherited cardiovascular diseases, and whole heart regeneration.
Xinna Zhang, PhD Cancer genomics, targeted therapy and immunotherapy.
 

Mentor Research Field
 Leng Han, PhD Use of computational biology, RNA biology, and systems biology to better understand the molecular mechanisms of complex diseases, identify novel prognostic and diagnostic biomarkers, and to develop innovative therapeutic strategies.
Kun Huang, PhD Develop machine learning/AI and systems biology methods to integrate multi-omics data for human disease research.
Sarath Janga, PhD Understanding the design principles and inferring post-transcriptional gene regulatory networks, and developing new integrative bioengineering methods for novel diagnostics, within the broader field of genomics and systems biology.
Travis Johnson, PhD  Development and application of novel machine learning techniques to single-cell RNA sequencing, spatial transcriptomics, bulk RNA sequencing, and multi-omic data.
Xiaochun Li, PhD

Analysis of observational data, Causal inference, High-dimensional data analysis, Latent class modeling, Bioinformatics, Medical Informatics, Machine learning.
Yunlong Liu, PhD Designs and implements computational methods for analyzing single-cell and spatial transcriptomics and for studying the roles of genetic variants on transcriptional regulation, RNA stability, and splicing regulation. 
Kwangsik Nho, PhD Integrates next-generation sequencing (multi-omics), clinical/fluid biomarkers, and advanced multimodal neuroimaging, to enhance the understanding of molecular mechanisms of neurodegenerative disorders.
Gang Peng, PhD Creating and implementing bioinformatics techniques and tools to analyze high throughput multi-omics data, with a particular emphasis on studying the correlation among epigenomics, exercise, and aging.
Sara Quinney, PhD Integrates clinical pharmacology studies and electronic health records with pharmacometric modeling to personalize drug therapy in special populations including pregnant women, children, patients with cancer, and obesity.
Jie Ren, PhD Development of data driven statistical methods with implementation in high-throughput genomics data.
Tae-Hwi Linus Schwantes-An, PhD Utilizing multi-omics approaches to identify genetic underpinnings of cardiometabolic diseases such as liver diseases and pulmonary arterial hypertension risk, progression, and outcomes. 
 Jing Su, PhD Use of bioinformatics and medical informatics, graph artificial intelligence, real-world data, and spatial omics data for precision medicine in chronic complex diseases such as chronic kidney diseases, alcohol use disorder, and cancers.
Haixu Tang, PhD The algorithmic and machine learning problems in genomics and proteomics. Development of privacy-preserving algorithms for analyzing human genomic data.
Jun Wan, PhD, MS Integration of a wide variety of omics data to achieve comprehensive patterns of gene regulatory networks, while developing cutting-edge analyses on high-throughput data and next generation sequencing data
Juexin Wang, PhD Developing and applying machine-learning approaches to model single-cell and spatial transcriptomics data and to analyze data in kidney diseases, cancer, and nervous system diseases.
Yijie Wang, PhD, MSC Building novel mathematical and computational tools and approaches that harness large data sets to direct hypothesis-driven experimentation and hypothesis-free interpretation.
Jingwen Yan, PhD, MS Developing computational and bioinformatics approaches for integrative analysis of high throughput multiomics data and rich biological knowledge including pathways and networks, with applications to Alzheimer’s disease.
Yuzhen Ye, PhD Bioinformatics and computational metagenomics. Development of novel methods for characterizing microbiome-based marker genes and building predictive models for microbiome-based host phenotype prediction.
Jie Zhang, PhD Developing and applying translational bioinformatics and system biology methods to identify disease genes, pathways, and biomarkers with applications in cancers, neurological diseases, and other types of diseases.
Xuhong Zhang, PhD Development and application of computational and statistical techniques, machine learning and deep learning models to theoretical and methodological problems.
Yi Zhao, PhD Causal mediation analysis, High-dimensional data analysis, Neuroimaging data analysis, Proteomics/metabolomics studies, Multiview data integration.
Laura Zhou, PhD Developing statistical methods for relevant problems in biomedical research, particularly in the field of immunomics, genomics, and precision medicine, including neural networks and polygenic risk scores.