BMI Grad Faculty Research Highlights
Primary Faculty Research Highlights
Divisions of Biomedical Informatics & Allergy and Immunology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Sandra Andorf, PhD, is a computational biologist pursuing research at the intersection of immunological and clinical research. Her research spans different disease areas with many of her current projects centering around better understanding the causes and treatments of food allergies. A substantial part of her lab’s work focuses on high-dimensional cellular data such as generated by flow or mass cytometry. In addition to original data, she also focuses on the re-use of existing laboratory-based and clinical trial-based data sets. One goal of her lab is to enable, demonstrate and utilize the full potential of existing individual participant-level clinical study data.
Divisions of Biomedical Informatics & Developmental Biology, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Bruce Aronow, PhD, is a computational biologist with a deep passion for accelerating biomedical discoveries. The Aronow lab aims to understand the molecular and cellular basis of normal organ and system development, physiology, and disease with the goal of preventing, or curing pediatric diseases. Dr. Aronow is one of the most highly cited researchers in the area of computational biomedicine and has led the development of multiple widely used tools, such as ToppGene, ToppFun and ToppCluster
Assistant Professor, Department of Electrical Engineering and Computer Science, University of Cincinnati
Gowtham Atluri, PhD, focuses his research on developing novel data science methodologies that will accelerate the pace of scientific discovery. His main thrust is in developing new algorithms and techniques for analyzing space-time data that are becoming ubiquitous in several domains, including neuroscience, climate science, mobile health, and social sciences. Some key directions in his research that are motivated from the above disciplines include studying networks in space-time data, comparing space-time instances, discovering patterns, and integrating data from different sources.
Divisions of Allergy and Immunology & Human Genetics, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Pediatrics, University of Cincinnati
The Barski Lab studies epigenomics with a primary focus on the immune system. Our main research projects are designed to investigate epigenomic regulation of T cell differentiation, activation and memory. We recently reported an association between the memory state of T cells and their epigenome and identified a transcription factor responsible for epigenome reprogramming during T cell activation. To support these projects, we run a complete “-omics” kitchen, and are developing tools for both wet lab “-omics” biotechnology and dry lab data analysis. Our expertise in both areas has led to multiple collaborative papers and grant applications on topics ranging from the epigenomics of spermatogenesis to the epigenomics of atopic disease to epigenomics of neurodevelopment. Our work also led to commercialization of Scientific Data Analysis Platform developed in the lab.
Lab Website | Google Scholar | ResearchGate | PubMed
Professor, Department of Electrical Engineering and Computer Science, University of Cincinnati
The focus of Dr. Bhatnagar's research has been on data mining and pattern recognition problems, including data mining algorithms for very large and distributed database problems. Dr. Bhatnagar and his group have applied these algorithms in multiple application domains including the bioinformatics and image analysis. Recent projects include subspace clustering and formal concept analysis for very large datasets, which seeks to develop efficient algorithms within the map-reduce paradigm for mining multi-domain subspace clusters from multiple datasets.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Jing Chen, PhD, focuses his research on genetics of preterm birth, phenomics of common and rare disorders, and genomics of pediatric cancers and congenital heart defects. His research aims to develop computational methods to analyze electronic health records for the phenomics of genetic disorders and to develop algorithms to detect pathogenic variants and improve our understanding of the etiology.
Divisions of Critical Care & Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Maya Dewan, MD, MPH, focuses on using the electronic health record to increase situation awareness and aid in the prediction and prevention of deterioration in Pediatric Intensive Care Unit patients.
Assistant Professor, Department of Biomedical Informatics, University of Cincinnati
Brett Harnett, MS, serves as the director for the UC Center for Health Informatics (CHI) within the Department of Biomedical Informatics. The CHI is the institutional Honest Broker that provides clinical data and other tools for research. He teaches in the BMI graduate program and partners with many investigators on small percentage efforts for grant writing/submissions representing clinical informatics expertise. Skills include data structures, enterprise design, compliance measures (e.g., HIPAA), IRB representation/protocol review, real world evidence research, use of Fast Healthcare Interoperability Resources (FHIR), telehealth, and remote monitoring.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Anil Jegga, DVM, MRes, pursues research in translational bioinformatics, with focus on computational drug discovery and drug repositioning, and systems biology of disease and drug response. He and his team aim to solve biomedical problems and aid translation research by designing, developing, and implementing innovative and novel computational methods.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Pediatrics, University of Cincinnati
Dr. Kouril is an expert in distributed and cloud computing platforms for Big Data. He collaborates with several Cincinnati Children's divisions on multiple innovative technology-related projects. One notable collaboration with the Division of Behavioral Medicine and Clinical Psychology (Jennie Noll, PI) aims to monitor online behavior of abused and non-abused adolescents to look for inappropriate and risky behavior. In addition, Dr. Kouril oversees the Cincinnati Children's Research IT group, which maintains a large computational cluster and petabyte-size storage in multiple performance tiers for the most demanding applications, such as research data warehousing, and virtual desktop infrastructure.
Associate Professor, Biomedical Informatics.
Long (Jason) Lu, PhD, focuses on bringing quantitative approaches from disciplines such as computer science and applied mathematics to study the molecular mechanisms of human diseases. His expertise includes biomolecular network predictions and analysis, machine learning and statistical inference, genomic and transcriptomic sequence analysis, and medical image analysis. Dr. Lu developed a network-based approach that combines proteomics experiments and computational predictions to discover high-density lipoprotein (HDL) subspecies and correlate them with cardiovascular protection function. His approach identified 38 candidate HDL subparticles. Further biochemical characterization of these putative subspecies may facilitate the mechanistic research of cardiovascular disease and guide targeted therapeutics aimed at its mitigation. In studying pediatric brain disorders, Dr. Lu developed a set of novel algorithms for analyzing brain anatomical and functional MRI images. These algorithms will be important tools in aiding physicians in diagnosis and developing treatment plans. Dr. Lu has also introduced a new perspective to characterize gene essentiality from protein domains, which addresses the limitations of traditional gene-level studies of essentiality. To identify such essential domains, he developed an Essential Domain Prediction (EDP) Model and presented the first systematic analysis on gene essentiality on the level of domains. Dr. Lu’s research accomplishments have been recognized nationally and internationally by serving on grant reviewer panels for the National Institutes of Health and the National Science Foundation in the United States, the Natural Sciences and Engineering Research Council of Canada (NSERC), French National Research Agency (ANR), and National Science Centre of Poland (NCN).
Divisions of Biomedical Informatics & Neonatology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Kevin Dufendach, MD, MS, focuses his research on clinical informatics, and improving usability in the science of healthcare delivery. He aims to bring modern technologies, such as machine learning and dynamic interfaces, into patient care. In clinical practice, he focuses on neonatology, congenital diaphragmatic hernia and neonatal respiratory physiology.
Graduate Program Co-director, Divisions of Biomedical Informatics & Emergency Medicine, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Pediatrics, University of Cincinnati
Judith Dexheimer, PhD, aims to to improve patient care and outcomes through the integration of informatics tools including (1) development of novel machine learning algorithms, (2) implementation of machine learning into care and the community, and (3) inclusion of vulnerable populations in research. She has a focus on using informatics as a tool to improve clinical care, identify high-risk patients, and improve the care of understudied populations. During her National Library of Medicine (NLM) informatics training, she studied artificial intelligence and implemented reminder systems directly into clinical care in the adult and pediatric emergency departments. Her research harnesses technology and health informatics approaches to improve healthcare delivery and the quality of care for children. Her research interests include machine learning, natural language processing, decision support, personal health records, and mental health informatics. She wants to provide technology and healthcare information to underserved populations, improve care delivery, and help providers incorporate machine learning approaches directly into clinical care.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Philip Hagedorn, MD, MBI, serves as Chief Research Information Officer for CCHMC. In this role he leads a diverse team of information professionals who collaborate with researchers at the intersection of healthcare, research and technology to accelerate discovery and improve health outcomes. Dr. Hagedorn is active in developing future leaders in the field of clinical informatics and, with this in mind, serves as the program director of CCHMC’s Clinical Informatics fellowship and runs CCHMC’s pediatric residency elective in clinical informatics. His research has focused on the intersection of clinical information systems, quality improvement and safety including work in clinical team communication and the diagnostic process.
Center for Autoimmune Genomics and Etiology & Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Kenneth Kaufman, PhD, research interests lie in the genetics of complex diseases, including systemic lupus erythematosus or SLE (an autoimmune disease) and rheumatoid arthritis. He and his team aim to discover the type of genetic variants that increase the risk of disease or cause disease, using next-generation DNA sequencing and advanced computational methods. He and his colleagues aim to uncover the systems and biological processes these variants affect to assist in developing new treatments for diseases.
Assistant Professor, Experimental Hematology & Cancer Biology
Komurov lab focuses on the systems biology of cancer. We develop and employ computational data mining tools to interrogate clinically exploitable cancer mechanisms from cancer genomics data, and use experimental approaches in vitro and in animal models for their molecular characterization. Specifically, we are studying the core aberrations in the genomic, RNA and protein homeostasis networks in cancers, their role in cancer pathogenicity and therapy response, and the synthetic vulnerabilities imposed by these defects on the tumor cell. In addition, we are developing computational methods and software to enable intuitive and effective functional mining of genomic data.
Professor, Department of Internal Medicine, University of Cincinnati
Mark Eckman, MD, is a general internist and decision scientist. His research interests lie in applications of decision analysis to the care of individual patients and to broader issues of health policy. His methodological interests have included the development of patient-specific decision support tools, cost-effectiveness analysis, and the continued study and development of new decision analytic methods. He uses quantitative methods to help make decisions about the allocation of increasingly scarce health care resources. He also has a long-standing interest in decision analytic issues surrounding anticoagulation therapy within a variety of clinical situations, including atrial fibrillation, venous thromboembolism, and thrombophilic states.
Division of Pediatric Gastroenterology Hepatology and Nutrition, Cincinnati Children’s Hospital Medical Center
Secondary appointments in Biomedical Informatics and Anderson Center for Health System Excellence
Assistant Professor, Department of Pediatrics, University of Cincinnati
Jasbir Dhaliwal, MBBS, MSc, is a clinician scientist whose primary focus is to employ predictive analytics to study the clinical and biological determinants of outcomes in Inflammatory Bowel Disease (IBD), an inherently complex and heterogenous disease. Our lab has a strong interest in pathology deep learning approaches. Furthermore, she is interested in population health and further understanding social determinants of health as a means of closing gaps in outcomes of care. At present her team is working on registry data (ImproveCareNow) and data within the EMR. In the current era of precision medicine, personalized approaches should benefit ‘all’ and not further perpetuate health inequalities.
Division of Molecular Cardiovascular Biology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
The Ikegami lab investigates the biological functions of the nuclear envelope –the organelle that encloses the genome– and how nuclear envelope dysfunctions cause human disease. Situated between the cytoplasm and the nucleoplasm, the nuclear envelope is a hub for nucleocytoplasmic communications. The nuclear envelope plays important roles in positioning the nucleus within the cell, protecting DNA from physical, chemical, and biochemical insults, selectively transporting molecules in and out of the nucleus, and organizing chromosomes and regulating gene expression by directly interacting with chromatin. Our current research focuses on: (1) the role of the nuclear envelope in the 3D organization of chromosomes and gene regulation; (2) the relationship between the loss of nuclear envelope integrity and tissue inflammation; and (3) the pathogenesis of cardiomyopathies and accelerated aging disorders caused by nuclear envelope gene mutations. We also investigate fundamental mechanisms of gene regulation and epigenetic memory during the cell cycle and develop new methodologies to study gene regulation in single cells. Our group uses a diverse experimental and computational techniques including functional genomics, mouse genetics, microscopy, cell engineering, stem cell differentiation, and bioinformatics.
Divisions of Cancer and Blood Diseases & Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Frank Huang, PhD, focuses his research on developing machine learning (deep learning) and statistical methods to integrate multiple types of omics data, including DNA-seq, RNA-seq, Chip-seq, Methylation, large-scale pharmaco-genomics data, and electronic health records, for driver signaling pathway analysis, drug repositioning, drug combination prediction, and elucidation of drug-resistant mechanisms. He collaborates with clinicians from different disciplines, including cancer, immunology, and neurology, to apply computational solutions to medical problems arising from clinical practice.
Associate Professor, Imaging Research Center, Cincinnati Children’s Hospital Medical Center & Department of Radiology, Biomedical Engineering, and Biomedical Informatics, Electrical Engineering and Computer Science, University of Cincinnati.
Lili He, PhD, is a computer scientist with expertise in deep learning, machine learning, medical imaging processing, and analysis (ranging from neuroimaging to body imaging). Dr. He has broad experience in 1) image reconstruction and synthesis; 2) image segmentation and interpretation; 3) biomarker discovery; 4) disease diagnosis; and 5) clinical outcome predictions. She is driving the clinical translation and implementation of Artificial Intelligence (AI) technologies in context of improved value of medical imaging and promoting the equitable care and safety of children nationwide and beyond. Dr. He’s long-standing commitment and current research are centered on the development and validation of robust clinically effective AI diagnostic tools for clinicians to use at the bedside to improve diagnosis, prediction, and prevention of patient outcomes for high-risk infants and children. Dr. He currently directs the laboratory of AI for Computer-Aided Diagnosis at Cincinnati Children’s Hospital Medical. She has led multiple National Institute of Health-, and Institution- funded studies to develop imaging prognostic biomarkers and deep learning models for early detection/ prediction of various important clinical outcomes, including Cognitive, Language, and Motor Deficits, Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder, Liver, and Crohn’s Diseases.
Assistant Professor, Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center
Dr. Hagan’s research is focused on using computational and systems biology approaches to understand immune development, aging, and response to vaccination and infection. Some of his recent work examined the role of the microbiome and gut dysbiosis in regulating vaccine-induced immunity. He also led a comparative analysis of transcriptional responses across 13 different vaccines, including the recently developed Pfizer COVID-19 mRNA vaccine, in order to understand how variation in adjuvants and vaccine platforms can impact immune responses. He is particularly interested in the development of computational tools for integration of multi-omics data, including transcriptome, metabolome, epigenome, and microbiome data, to identify interactions across the many components of the immune system in health and disease.
Divisions of Human Genetics & Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Yaping Liu, PhD, has a broad background in epigenomics, single-cell multi-omics, computational biology, gene regulation, population genetics and liquid biopsy. These skills and interests drive him to understand the interactions between genetic and epigenetic variations, bridging the gaps between genotype and phenotype. His lab focuses on developing and applying machine learning and high-throughput experimental methods to understand gene regulation and non-coding genetic variants.
Professor, Departments of Biomedical Informatics & Environmental and Public Health Sciences, University of Cincinnati
Mario Medvedovic, PhD, is developing and applying new statistical and computational methods for the analysis of “big data” in the context of biomedical research. His recent work is focused on the connectivity map analysis of single cell transcriptional signatures and the development of methodologies for analysis of signaling pathways using transcriptional signatures of genetic perturbations.
Lab Website | Google Scholar | ResearchGate | PubMed
Graduate Program Director
Professor, Department of Environmental and Public Health Sciences, Department of Computer Science, University of Cincinnati & Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Dr. Meller pursues research in the areas of structural bioinformatics, computational genomics, and Big Biomedical Data. Dr. Meller and his group have developed several widely used methods for the prediction of protein structure, protein-protein interactions, and functional hot spots in proteins, including Sable, Sppider, and Minnou. To date, these methods and web servers have been used by over 100,000 users in many countries. Dr. Meller and his group have been involved in many collaborative projects aiming at the identification of markers associated with disease subtypes in cancer and autoimmunity, modeling of signal transduction pathways, and development of allosteric inhibitors of critical protein-protein interactions in autophagy, bone marrow transplants, and pathogen-host interactions.
Rieveschl Chair and Director, Division of Biomedical Informatics at Cincinnati Children’s Hospital Medical Center
Professor, University of Cincinnati College of Medicine
Dr. Mendonca's research covers a broad range of areas. Her focus lies in leveraging health information technology and informatics methodologies to enhance clinical practice, advance population-level health prevention, and drive translational research. She has played a crucial role in utilizing electronic health record data for epidemiology studies, accurate predictions, and effective phenotype modeling, contributing to improved patient care and clinical decision-making. Dr. Mendonca focuses on developing automated semantic and statistical methods to extract biomedical data from patient records while maintaining patient privacy. She studies ways to generate new research knowledge from electronic health records data, social and environmental data, and patient generated data. Recent projects include the understanding of diabetes burden in children and adolescents, computable social phenotyping, and health disparities in pediatric cancer and respiratory diseases. Dr. Mendonca has been involved in many multi-institution projects, including a NIH-funded Environmental Influences on Child Health Outcomes (ECHO) study and the Children’s Respiratory Research and Environment Workgroup (CREW), where she uses informatics tools to harmonize data among several large cohorts, combining clinical data, social determinants of health and behavior, and biological markers.
Divisions of Asthma & Global Health, Cincinnati Children’s Hospital Medical Center
Professor, University of Cincinnati College of Medicine
Dr. Mersha is a Professor of Pediatrics in the Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati College of Medicine, where he leads the Population Genetics, Ancestry and Bioinformatics Laboratory (pGAB). His research combines genetic ancestry, bioinformatics, and statistical and functional genomics to unravel genetic and non-genetic contributions to complex diseases in human populations, particularly in allergic disorders. Much of his research is at the intersection of basic, clinical, and translational research, and he is interested in crossline disciplines to dissect how biologic predisposition and environmental exposures interact to shape racial disparities in asthma and other complex disorders. Dr. Mersha is recognized in the field of genetic ancestry, race, ethnicity, admixture mapping and functional genomics related to complex diseases. His research helps in dissecting how biologic predisposition and environmental exposures interact to shape racial disparities in complex diseases. He has received multiple awards, including a Faculty Research Achievement Award from Cincinnati Children’s Hospital Medical Center, Keystone Symposia Early Career Investigator Award, and African Professionals Network Business and Professional Achievement Award. His research continues to be funded by the National Institute of Health (NIH).
Assistant Professor, Divisions of Immunobiology & Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Department of Pediatrics and Department of Computer Science, University of Cincinnati
Dr. Emily Miraldi’s research program is focused on mathematical modeling of the immune system in vivo. These models span mechanistic (e.g., dynamic gene regulatory networks) to deep learning (e.g., prediction of cellular epigenomes from DNA sequence), integrating cutting-edge measurement technologies (e.g., single-cell genomics, chromatin state, proteomics). Situated at Cincinnati Children’s Hospital, her group is dedicated to the design of computational methods and systems-immunology studies that will ultimately improve the health of children. Close collaboration with physician and experimental colleagues enables iterative experimental testing of computational predictions and model refinement, leading to novel insights into immune-cell function and new therapeutic strategies in the context of autoimmunity, infectious disease and cancer. Her interdisciplinary, team-oriented computational-experimental studies push the boundaries of both immunology and computational biology.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Instructor, Department of Pediatrics, University of Cincinnati
Divisions of Pulmonary Medicine, Biomedical Informatics, James M. Anderson Center for Health Systems Excellence
Nathan Pajor, MD, MS is a pediatric pulmonologist and learning health systems scientist focused on improved outcomes for children with chronic mechanical ventilator dependence through the use of clinical data derived from the EHR and from mechanical ventilators. He is the informatics site lead for Cincinnati Children’s participation in the PEDSnet network which facilitates sharing of electronic health records data from large children’s hospitals. His lab also focuses on the improved capture and use of device data to better understand pathophysiology and the resultant variability in outcomes that exist in this heterogeneous population.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics and Psychiatry at the University of Cincinnati and Joint appointment at Oak Ridge National Laboratory.
John Pestian, Ph.D., MBA, lab focuses on developing advanced technology for the care of neuropsychiatric illness. Using natural language processing, machine learning, and other forms of artificial intelligence, his team integrates multimodal data and analyzes it to understand the patient’s traits and state characteristics that will aid in the early identification of a neurological and psychiatric illness. He and his colleagues have over 130 published papers and 20 patents and have started multiple start-up businesses. Together they have had over $500 million in grants and economic impact, and their innovations have been used to help over two million people. Lately, the Pestian Lab, CCHMC and UC Colleague, and Oak Ridge National Lab have been focused on developing trajectories of early identification for anxiety, depression, suicide, and school violence using verbal and non-verbal language (decode.cchmc.org)
Center for Autoimmune Genomics and Etiology & Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Pediatrics, University of Cincinnati
Alexey Porollo, PhD, is a computational biologist who focuses on the structural and functional annotation of proteins, comparative genome analysis of non-model organisms, and metagenomics. His lab pursues the development of new prediction and annotation methods using data mining, machine learning, and deep learning algorithms.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Assistant Professor, Department of Electrical Engineering and Computer Science, University of Cincinnati
Surya Prasath, PhD, focuses on the application of machine learning and mathematical modeling in the areas of image processing and computer vision. His main research interests include deep learning, image processing, computer vision with applications in biomedical imaging and multi-modal data.
Divisions of Clinical Pharmacology & Research in Patient Services, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Pediatrics, University of Cincinnati
Laura Ramsey, PhD, pursues research in pharmacogenetics, from basic research to implementation in patient care. Dr. Ramsey aims to elucidate the genetic underpinnings of how a person responds to or metabolizes a drug, and to translate this knowledge into clinical care.
Professor, Environmental Health and Biomedical Engineering, University of Cincinnati
Marepalli Rao, PhD, is a biostatistician who has a broad interest in current challenges in statistical genetics, survival analysis, internet health data, data mining, machine learning, tissue engineering, medical imaging and data science.
ResearchGate | PubMed
Divisions of Biomedical Informatics & Immunobiology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Krishna M. Roskin, PhD, is a computational immunologists who's laboratory uses sequence analysis of antibody and T cell receptor genes and single-cell bioinformatics bioinformatics to understand how the human immune system can respond inappropriately or fail to respond in allergy, immunodeficiency, transplant rejection, and autoimmunity.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Associate Professor, Department of Biomedical Informatics, University of Cincinnati
Nathan Salomonis, PhD, is a computational biologist who develops novel approaches and computational tools to examine the interplay between diverse modes of gene regulation, including transcription, alternative splicing, genetics, and epigenetics that underlie disease interaction networks, with focus on human cardiovascular diseases and cancer. His research group develops novel methods for single cell transcriptome profiling using scRNA-seq, new computational genomics techniques to understand the role of alternative splicing and elucidate lineage fate choices in differentiation. Dr. Salomonis developed AltAnalyze, a widely used software package for the analysis of genomic data.
The role of alternative splicing in both human development and disease is profound. Unique alternative isoforms govern opposing transcriptional, signaling and cell survival responses that can drive differentiation to new lineages or blunt responses to chemotherapies. My research aims to reveal hidden splicing single-cell networks that underlie normal cell differentiation and disease. This work spans the last 25 years and over 115
peer reviewed manuscripts. To aid in this work, my lab has developed numerous computational approaches to resolve single-cell populations and define core regulatory networks that derive from altered transcriptional or splicing programs. These tools include the highly used and cited applications AltAnalyze, GenMAPP and GO-Elite, ICGS2, cellHarmony, DoubletDecon, MultiPath-PSI, and DeepImmuno and scTriangulate. These tools have provided the engine for us to establish a functional relationship between splicing regulation in cell-fate determination in embryonic stem cells (PNAS 2010), identify new bipotential transitional cell states in hematopoiesis (Nature 2016), discover splicing-defined subtypes of early-stage myelodysplasia (Blood 2018), cell-state differentiation defects in Neutropenia (Nature 2020) and rewiring of splicing regulatory networks in leukemia (Nat. Comm. 2020) and cardiomyopathy (Nat. Comm. 2021). Our current work applies deep learning to design new cancer vaccines, identify novel isoforms that alter tumor extracellular signaling and game theory to resolve clonal heterogeneity in cancer. In addition to these direct research roles, I co-direct the NHBLI LungMAP II Data Coordination Center and Pediatric Cell Atlas initiatives at Cincinnati Children’s Hospital and participate in CZI funded Human Cell Atlas bioinformatics efforts.
Divisions of Biomedical Informatics & Oncology, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Mayur Sarangdhar, PhD, is interested in unraveling the underlying causes and mechanisms of drug toxicity. His research focuses on integrating high-dimensional computational approaches with a systems biology knowledgebase to accelerate the discovery of novel drug-toxicity relationships buried in heterogeneous big data. His group is developing integrative analytical approaches that combine machine learning techniques with toxicity data, genotype-phenotype relationships and gene-regulatory mechanisms to help facilitate modelling novel and effective therapeutics.
Associate Professor, Internal Medicine, University of Cincinnati
Daniel P. Schauer, MD, MSc, has expertise in the decision sciences, patient-centered outcomes and comparative effectiveness research. Much of his current research is focused on obesity and outcomes associated with bariatric surgery, using large publicly available datasets such as the National Health Interview Survey, the National Death Index, and the Nationwide Inpatient Sample. Additionally, as associate program director for resident research, he oversees all of the resident research in the Department of Internal Medicine.
Divisions of Biomedical Informatics & Hospital Medicine, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Andrew Spooner, MD, MS, FAAP, serves as the Chief Medical Information Officer for CCHMC. His research interests span medication-dosing decision support, problem-based reasoning, digital patient engagement and pediatric aspects of electronic health records. His aim is to improve children’s health using information technology, electronic health records and other digital tools.
Department of Biomedical Informatics, University of Cincinnati
Dr. Tachinardi is a highly accomplished professor of biomedical informatics who is currently leading groundbreaking projects aimed at integrating clinical, social, environmental and biological data to enhance healthcare and biomedical sciences. He is serving as the Interim-Chair of the Department of Biomedical Informatics at the College of Medicine - University of Cincinnati, where he is also an Associate-Dean holding the position of Chief Health Digital Officer, a role that he shares with UC-Health.
With his extensive background in academic medical organizations, Dr. Tachinardi possesses a unique perspective on the challenges and opportunities of data sharing in the healthcare industry. He specializes in developing and operating data infrastructures that support health sciences research, as well as quality and operational healthcare functions. Dr. Tachinardi's areas of focus also include developing decision support tools and introducing novel technologies to support precision care and health promotion.
Department of Radiology & Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Professor, Department of Radiology, University of Cincinnati
Alexander J. Towbin, MD, is a radiologist, the Neil D. Johnson Chair of Radiology Informatics, Associate Chief of Radiology (Clinical Operations and Radiology Informatics), and Associate Chief Medical Information Officer at Cincinnati Children's Hospital Medical Center. He is a recognized leader in pediatric abdominal imaging, pediatric oncologic imaging, imaging informatics, and quality improvement. His research focuses on imaging of the liver, cancer imaging, clinical informatics, quality improvement and machine learning.
Associate Professor, Biomedical Informatics.
Dr. Wagner has a long-standing interest in applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification. He is also involved in a number of projects that implement complex software and data infrastructure. For the National Heart Lung and Blood Institute-funded Pediatric Cardiology Genomics Consortium, part of the Bench to Bassinet project, he plays a leadership role in the development and maintenance of the Data Hub (a.k.a. HeartsMart), which now houses tens of thousands of whole exome and thousands of whole genome sequencing data sets. He is co-principal investigator on the Longitudinal Pediatric Data Resource (LPDR) project funded through the Newborn Screening Translational Research Network and National Institute of Child Health and Human Development. The LPDR is being used by researchers nationwide to mine health outcome data over the lifespan of children who screen positive for rare and often devastating genetic disorders. Dr. Wagner also leads the Rheumatology Disease Research Informatics Core of the Cincinnati Rheumatic Diseases Core Center, which is funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases.
Scientific Director, Center for Autoimmune Genomics and Etiology
Divisions of Human Genetics, Biomedical Informatics, and Developmental Biology, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Matt Weirauch, PhD, is a bioinformatician and geneticist who aims to achieve a thorough understanding of human and viral transcriptional regulation mechanisms in complex diseases. He has helped develop new computational tools and experimental data to attain a mechanistic understanding of gene regulation. His lab has long been interested in gene regulation, recently expanding their focus to include the role of viruses in human gene regulation and how this contributes to human disease processes.
Associate Professor, Department of Biomedical Informatics, University of Cincinnati
Danny Wu, PhD, focuses his research on human-computer interaction, applied machine learning, natural language processing, and visual analytics to maximize the value of electronic health records to improve care delivery and quality, support clinical and translational research, and facilitate learner-centered medical education. In addition to research, Wu is dedicated to education and service. He joined the American Medical Informatics Association (AMIA) in 2011 and became a fellow of AMIA in 2021.
Divisions of Pulmonary Biology & Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Professor, Department of Pediatrics, University of Cincinnati
Yan Xu, PhD, focuses on developing and applying bioinformatics and systems biology approaches to gain a better understanding of molecular mechanisms behind lung development and disease. Her current lines of research center on the revealing of cell-cell communication, regulatory circuits, and networks controlling normal lung maturation and the pathogenesis of diseases using integrative single-cell omics approaches. She is also devoting her efforts to develop web-based lung cell atlas (LGEA) and LAM Cell Atlas to facilitate the maximal access and usage of the ever-growing omics data resources for the lung research community.
Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Assistant Professor, Department of Pediatrics, University of Cincinnati
Hee Woong Lim, PhD, studies fundamental mechanisms of gene transcriptional regulations in various contexts, such as metabolism, development, pathogenesis, and pharmacogenomics. He focuses on enhancer regulations to delineate their intrinsic heterogeneity of architectures and functions using a high-resolution landscape of transcription factor binding and enhancer RNA (eRNA). His lab actively utilizes multi-omics high-throughput data including GRO-seq, RNA-seq, ChIP-seq, ChIP-exo, CUT&RUN, csRNA-seq, and multiple types of single-cell omics data.
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Department ofBiostatistics, Health Informatics & Data Sciences
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