Cihan Oguz
About Cihan Oguz
Cihan Oguz is a Bioinformatics Scientist with extensive experience in multi-omic data analysis and machine learning. He has contributed to 18 publications in high-impact journals and has presented research at over 20 genomics conferences.
Work at Axle Informatics
Cihan Oguz has been employed as a Bioinformatics Scientist at Axle Informatics since 2021. In this role, he focuses on integrating multi-level omic data into predictive machine learning models. His work contributes to understanding disease phenotypes, particularly in the context of cardiovascular diseases. The position is based in Bethesda, Maryland, where he continues to advance his research in bioinformatics.
Education and Expertise
Cihan Oguz holds a Doctor of Philosophy (Ph.D.) in Chemical and Biomolecular Engineering from Georgia Institute of Technology, where he studied from 2002 to 2007. Prior to that, he earned a Bachelor's degree in Chemical Engineering from Orta Doğu Teknik Üniversitesi (Middle East Technical University) from 1998 to 2002. His educational background provides a strong foundation for his expertise in bioinformatics, particularly in multi-omic data analysis.
Background
Cihan Oguz has a diverse professional background in bioinformatics and research. He began his career as a student at the METU Chemical Engineering Department from 1998 to 2002. He then pursued graduate studies at Georgia Institute of Technology from 2002 to 2007. Following his Ph.D., he worked at various institutions, including UCSF as a Postdoc from 2008 to 2010, and Virginia Tech as a Research Scientist from 2011 to 2014. He also served as a Research Fellow at the National Human Genome Research Institute from 2014 to 2018.
Publications and Presentations
Cihan Oguz has contributed to 18 publications in high-impact journals, including Nature, Nature Medicine, and Nature Immunology. He has also presented his research findings at over 20 genomics conferences and meetings. Notable venues include the Cold Spring Harbor Laboratory and the National Institutes of Health, where he shared insights on multi-omic data analysis and its implications for disease research.
Research Skills and Specializations
Cihan Oguz specializes in analyzing sequencing data sets, including single cell RNA-Seq, spatial transcriptomics, and immune repertoire analysis. He has a strong ability to generate novel hypotheses from multi-omic data, particularly related to cardiovascular disease phenotypes. His expertise extends to integrating these data into predictive machine learning models, enhancing the understanding of complex disease networks.