BMI Faculty by Research Area


Biomedical Informatics Research Areas

Predictive Modeling and Personalized Medicine

Pattern recognition on clinical data has enabled the development of predictive models for diagnosis and prognosis of human disease. However, the predictive power of these models can be enhanced with genetic data that are increasingly being generated via high throughput technologies, and more recently via whole genome sequencing. Integrating clinical and molecular data to build, evaluate, and implement accurate prediction models for personalized medicine is a new exciting field of research for biomedical informatics specialists. The impact of personalized medicine in patient outcomes is only beginning to be understood, and this burgeoning area of research and development requires skills in computer science, statistics, and life sciences.

Olivier Harismendy

Assistant Professor, Biomedical Informatics

  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Predictive Modeling and Personalized Medicine
  • Bioinformatics Applications in Human Disease

Research Focus: My laboratory develops genome-wide assays and analysis for personalized cancer care. Particular focus includes genetics of cancer susceptibility and drug response, secure computing and data sharing.

oharismendy@ucsd.edu
858-246-0248
Website
Profile

Chun-Nan Hsu

Associate Professor of Medicine, Biomedical Informatics

  • Predictive Modeling and Personalized Medicine
  • Data Models and Knowledge Representation
  • Biomedical Natural Language Processing

Research Focus: Information extraction from biomedical literature and clinical notes by machine learning

chunnan@ucsd.edu
(858) 822-2690
Profile

Xiaoqian Jiang

Assistant Professor, Biomedical Informatics

  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics

Research Focus: Healthcare privacy, predictive models

x1jiang@ucsd.edu
(858) 534-6391
Profile

Lucila Ohno-Machado

Professor, Biomedical Informatics

  • Epigenomics and Gene Expression Control
  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics

Research Focus: Biomedical Informatics, predictive modeling, biomedical data analytics

machado@ucsd.edu
(858) 822-4931
Profile

Gene Yeo

Professor, Cellular and Molecular Medicine

  • Quantitative Foundations of Computational Biology
  • Comparative and Population Genomics
  • Proteomics and Metabolomics
  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Dynamical Systems, Stochastic Processes, and Biological Circuits
  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics
  • Bioinformatics Applications in Human Disease

Research Focus: We develop computational, molecular, biochemical and cellular approaches to understanding and treating human diseases such as neurodegeneration and autism.

geneyeo@ucsd.edu
(858) 534-9321
Website
Profile

Privacy Technology, Data Sharing, and Big Data Analytics

Whole genome sequences from humans are increasingly being collected for clinical care. Dealing with personal health information requires full compliance with current regulations designed to protect the individual privacy. Technologies to preserve privacy in disclosed data allow broader, safer sharing of health information for research and healthcare quality improvement. The rapid collection of data from electronic health records has promoted greater awareness of the need to combine technology and privacy solutions for data sharing. Building accurate predictive models that utilize these data will only be possible if these data can be shared in a privacy-protecting manner, hence the field of privacy technology has been experiencing enormous growth in the past few years, represented by a range of innovations in both theory and applications.

Charles Elkan

Professor, Computer Science and Engineering

  • Quantitative Foundations of Computational Biology
  • Genetic and Molecular Networks
  • Privacy Technology, Data Sharing, and Big Data Analytics
  • Biomedical Natural Language Processing

Research Focus: Artificial Intelligence

celkan@ucsd.edu
(858) 534-8897
Website
Profile

Yoav Freund

Professor, Computer Science and Engineering

  • Quantitative Foundations of Computational Biology
  • Epigenomics and Gene Expression Control
  • Privacy Technology, Data Sharing, and Big Data Analytics

Research Focus: Machine learning, computational statistics

yfreund@ucsd.edu
Website
Profile

Xiaoqian Jiang

Assistant Professor, Biomedical Informatics

  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics

Research Focus: Healthcare privacy, predictive models

x1jiang@ucsd.edu
(858) 534-6391
Profile

Lucila Ohno-Machado

Professor, Biomedical Informatics

  • Epigenomics and Gene Expression Control
  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics

Research Focus: Biomedical Informatics, predictive modeling, biomedical data analytics

machado@ucsd.edu
(858) 822-4931
Profile

Gene Yeo

Professor, Cellular and Molecular Medicine

  • Quantitative Foundations of Computational Biology
  • Comparative and Population Genomics
  • Proteomics and Metabolomics
  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Dynamical Systems, Stochastic Processes, and Biological Circuits
  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics
  • Bioinformatics Applications in Human Disease

Research Focus: We develop computational, molecular, biochemical and cellular approaches to understanding and treating human diseases such as neurodegeneration and autism.

geneyeo@ucsd.edu
(858) 534-9321
Website
Profile

Data Models and Knowledge Representation

Because research is multi-institutional and lots of data are required to recognize meaningful patterns, it is important to harmonize data collected at different institutions through the use of appropriate data models. Developing automated ontology mapping tools and structuring data and knowledge in a computable format are important pillars of biomedical computing. Although strategies have been developing for several years, before the advent of big healthcare data the need for and efficacy of innovative approaches were not fully appreciated by the biomedical scientific community. Research on data models and representation frameworks has permitted the combination of data from several sources for analytics that support a variety of applications, including decision support systems.

Chun-Nan Hsu

Associate Professor of Medicine, Biomedical Informatics

  • Predictive Modeling and Personalized Medicine
  • Data Models and Knowledge Representation
  • Biomedical Natural Language Processing

Research Focus: Information extraction from biomedical literature and clinical notes by machine learning

chunnan@ucsd.edu
(858) 822-2690
Profile

Hyeon-eui Kim

Assistant Adjunct Professor, Biomedical Informatics

  • Data Models and Knowledge Representation

Research Focus: Impact of information technology on patient care. Clinical decision support systems. Consumer health informatics.

hyk038@ucsd.edu
(858) 822-4368
Profile

Decision Support Systems

Clinicians and biomedical researchers are often overwhelmed with information and may have difficulties in translating information into actions that have a direct or indirect effect on biomedical knowledge and human health. The design and implementation of effective decision support systems to assist biomedical researchers and/or clinicians perform their tasks in a well informed manner has the potential to change the biomedical research is conducted and way medicine is practiced. Deep understanding of computational challenges for specific applications areas is required for the assembly of multi-disciplinary teams that can build effective decision support systems.

Robert El-Kareh

Assistant Professor, School of Medicine

  • Decision Support Systems

Research Focus: Biomedical Informatics

relkareh@ucsd.edu
(858) 822-7776
Profile

Biomedical Natural Language Processing

The wide adoption of electronic health records (EHR) is important for proper collection data that can be used in further computation. However, most of the EHR information is still presented in narrative form. Systems that can understand the language in these documents and structure the data for computation are critical for data analysis and predictive modeling that serve as bases for decision support systems. Natural language processing techniques derived for non-biomedical text do not always work in biomedical text. For this reason, specialized biomedical natural language processing is necessary and constitutes an important area of research and development in biomedical informatics.

Charles Elkan

Professor, Computer Science and Engineering

  • Quantitative Foundations of Computational Biology
  • Genetic and Molecular Networks
  • Privacy Technology, Data Sharing, and Big Data Analytics
  • Biomedical Natural Language Processing

Research Focus: Artificial Intelligence

celkan@ucsd.edu
(858) 534-8897
Website
Profile

Chun-Nan Hsu

Associate Professor of Medicine, Biomedical Informatics

  • Predictive Modeling and Personalized Medicine
  • Data Models and Knowledge Representation
  • Biomedical Natural Language Processing

Research Focus: Information extraction from biomedical literature and clinical notes by machine learning

chunnan@ucsd.edu
(858) 822-2690
Profile

Bioinformatics Applications in Human Disease

Human disease is a result of genetic and environmental factors. New bioinformatics algorithms can be applied on a combination of genetic, clinical, and environmental factors to help understand disease processes and build predictive models for diagnosis and/or prognosis. Given the heterogeneity of data that are involved, specialized training is necessary to allow innovation in the integration, analysis, and sharing of human subject data related to health and disease.

Christopher Glass

Professor, Cellular and Molecular Medicine

  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Bioinformatics Applications in Human Disease

Research Focus: Enhancer Selection and Functions, Macrophage Subtypes, Genetic Variation, Enhancer Transcription

ckg@ucsd.edu
(858) 534-6011
Website
Profile

Olivier Harismendy

Assistant Professor, Biomedical Informatics

  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Predictive Modeling and Personalized Medicine
  • Bioinformatics Applications in Human Disease

Research Focus: My laboratory develops genome-wide assays and analysis for personalized cancer care. Particular focus includes genetics of cancer susceptibility and drug response, secure computing and data sharing.

oharismendy@ucsd.edu
858-246-0248
Website
Profile

Lilia Iakoucheva

Associate Professor, Psychiatry

  • Genetic and Molecular Networks
  • Bioinformatics Applications in Human Disease

Research Focus: Autism, genetics, gene expression, protein interactions, systems biology, networks, psychiatric diseases, whole genome sequencing

lilyak@ucsd.edu
(858) 822-1878
Website
Profile

Dorothy Sears

Associate Professor, School of Medicine

  • Proteomics and Metabolomics
  • Epigenomics and Gene Expression Control
  • Bioinformatics Applications in Human Disease

Research Focus: Mechanisms and biomarkers of nsulin resistance, type 2 diabetes, obesity, breast cancer, PPARgamma, inflammation

dsears@ucsd.edu
(858) 534-8898
Profile

Gene Yeo

Professor, Cellular and Molecular Medicine

  • Quantitative Foundations of Computational Biology
  • Comparative and Population Genomics
  • Proteomics and Metabolomics
  • Epigenomics and Gene Expression Control
  • Genetic and Molecular Networks
  • Dynamical Systems, Stochastic Processes, and Biological Circuits
  • Predictive Modeling and Personalized Medicine
  • Privacy Technology, Data Sharing, and Big Data Analytics
  • Bioinformatics Applications in Human Disease

Research Focus: We develop computational, molecular, biochemical and cellular approaches to understanding and treating human diseases such as neurodegeneration and autism.

geneyeo@ucsd.edu
(858) 534-9321
Website
Profile

Other BMI Research Areas

Jina Huh

Assistant Professor, Biomedical Informatics

Research Focus: Human-computer interaction, consumer-health informatics, mobile health

jinahuh@ucsd.edu
(858) 246-2562
Website
Profile