Bioinformatics and Systems Biology

Bioinformatics and Systems Biology investigate computational models and build software tools and systems to answer important questions in bio/medical/health domains based on large scale data generated by high-throughput technologies. As an interdisciplinary field, Bioinformatics combines computer science, statistics, genetics and genomics, cellular and molecular biology to analyze and interpret biological and health data. 

Our research interests include studies of genetic variations for better understanding of genetic basis of diseases and for personalized medicine, biomarker discovery for disease diagnosis and prognosis, AI-based prediction models for computational drug discovery, computational network analysis of biological systems, joint analysis of genetic and molecular data with medical record data, and genetic privacy. 

Faculty who conduct research in Bioinformatics and Systems Biology

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Erman Ayday

Assistant Professor, Computer and Data Sciences Department

Privacy enhancing technologies, data security and applied cryptographyy

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Mehmet Koyuturk

Professor, Computer and Data Sciences Department

Develops algorithms for transforming "big" biological data into systems biology knowledge

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Jing Li

Leonard Case Jr. Professor of Engineering
Professor, Computer and Data Sciences Department

Develops computational approaches and software tools for genomics, bioinformatics and systems biology, and creates computational solutions for big data analytics

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Shuai Xu

Assistant Professor, Computer and Data Sciences Department

My research interest lies in theoretical computer science, with a focus on designing efficient algorithms and Fourier analysis of Boolean functions. I am also interested in developing quantitative portfolios for hedge funds by adhering to mathematical and statistical methods.

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Fanny Ye

Theodore L. and Dana J. Associate Professor in Computer Science and Engineering
Associate Professor, Computer and Data Sciences Department

Research areas mainly include cybersecurity, data mining, machine learning, and health intelligence.