Cihan Oguz Email and Phone Number
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• Bioinformatician and genomic data scientist with solid computational biology and bioinformatics background and 14 years of experience in biomedical research. • Proficient in R, Python, and MATLAB programming and operating in UNIX cluster environments. • Strong written and verbal communication skills and ability to produce quality research in collaborative groups as demonstrated by 18 publications in journals including Nature, Nature Medicine, and Nature Immunology. • Adept at implementing systems biology approaches and integrating multi-level omic data into predictive machine learning models and networks of disease phenotypes.• 8 years of hand-on experience in genomic data processing and analysis of sequencing data sets derived from short and long reads that involve single cell RNA-Seq, genome/transcriptome assembly, spatial transcriptomics, and bulk/single cell immune repertoire.• Highly skilled in integrating evidence from multiple data modalities and identifying interactions between them (e.g., genotype-phenotype and genotype-gene expression) using machine learning.• Strong ability in generating novel hypotheses and insights from multi-omic data analysis as demonstrated by research output on cardiovascular disease phenotypes across multiple patient cohorts with clinical, genotypic, and transcriptomic data. • Experienced at presenting analysis results in a concise manner as demonstrated by presentations in 20+ genomics conferences and meetings at the Cold Spring Harbor Laboratory and the National Institutes of Health.
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Bioinformatics ScientistAxle Informatics Nov 2021 - PresentRockville, Maryland, UsI work with NIH investigators in research projects that involve genomic data processing and analysis of sequencing data sets derived from short and long reads that involve genome/transcriptome assembly, single cell RNA-Seq, spatial transcriptomics, and bulk/single cell immune repertoire.
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Bioinformatician And Genomic Data ScientistLeidos Nov 2018 - Nov 2021Reston, Virginia, UsStarting from raw sequencing data, I perform RNA-Seq analysis (bulk and single cell), alternative splicing analysis, and whole exome and whole genome sequencing analysis in projects related to immune system. I collaborate with investigators at the National Institute of Allergy and Infectious Diseases at NIH. -
Research FellowNational Human Genome Research Institute (Nhgri) Jun 2014 - Oct 2018Bethesda, Md, Us• Developed predictive random forest and neural network classification models and interaction networks of treatment resistant and controlled hypertension among African-Americans using clinical and RNA-Seq data. • Identified subphenotype-specific mRNA and miRNA predictors and perturbed pathways and generated experimentally testable predictions associated with hypertension.• Used clinical and exome sequencing data for building predictive models of advanced coronary artery calcium. Identified a predictive molecular network enriched in biological processes associated with vascular aging. Tested and replicated the predictive SNPs in independent Caucasian patient cohorts with multiple disease subphenotypes. -
Research ScientistVirginia Tech Mar 2011 - May 2014Blacksburg, Va, Us• Built a computational pipeline optimizing the 200 biological parameters of a mechanistic budding yeast cell cycle model integrating genotype, phenotype, and protein level data from 111 genetic strains. • Characterized the model’s feasible region, identified robust and fragile mutants and model parameters, and found relative protein abundances predictive of cell cycle network modules.• Implemented a single cell-based stochastic approach for modeling synchronization of budding yeast cells. Integrated expression pulses of various cyclins into this model and generated predictions that were verified by experimental data that was not used for model calibration. -
PostdocUcsf Jan 2008 - Dec 2010San Francisco, California, UsAlgorithm development for parameter estimation, robustness analysis, and validation of genetic network models based on high dimensional ODEs:- Created an algorithm that explores large model parameter spaces (e.g., more than 40 parameters, covering several orders of magnitude with each parameter) to automatically identify populations of parameter sets that can satisfy different kinds of experimental data simultaneously.- Incorporated relative abundances of proteins at steady state, dynamic data describing the evolution of mRNA/protein levels under different inputs such as temperature increase, and fold changes in protein levels with gene overexpressions from Western blots, QPCR and flow cytometry into high dimensional ODE models.Multiscale modeling of the bistable white-opaque switch in Candida Albicans:- Used the algorithm described above to build a deterministic model and constrained its parameters so that the model satisfies experimental constraints such as bistability, fold changes in protein levels with gene overexpressions, dynamic evolution of protein levels during switching between different cell states, and switching behavior under genetic perturbations (e.g., gene copy deletions).- Based on this deterministic model, built a predictive stochastic model that correctly captured the experimentally observed heritability consistently with a large ensemble of parameter sets. Identified the topological network features that are critical for the observed steady state and dynamic behavior of this genetic network. -
Graduate StudentGeorgia Institute Of Technology Aug 2002 - Dec 2007Atlanta, Georgia , UsThesis topic: Control-oriented modeling of atomic and molecular scale processes with application and experimental validation in film growth and polymer synthesis.Data dimensionality reduction based modeling and optimization of the epitaxial gallium arsenide deposition:- Created a kinetic Monte Carlo code for simulation of thin film growth. Formulated an algorithm inorder to identify a reduced order dynamic model of the deposition. This algorithm was based oncharacterizing the state space under different input sequences, followed by state space dimensionality reduction using principal component analysis and Self-Organizing Maps, and finally the identification of a Markovian model describing the transitions between different states with compact representations.- Optimized the film growth process using this reduced order model by identifying the optimal input sequence to reach the desired final state through dynamic programming.Structure development in hyperbranched polymers:- Created a kinetic Monte Carlo code for simulation of the polymerization process by extracting simulation parameters from experimental data.- Modeled the effects of reduced monomer reactivity, cyclization and endcapping reactions on thebranching of polymers. Investigated the effects of different polymer synthesis routes and variousmonomers on the structure development of hyperbranched polymers.Microstructure development in sputtered aluminum thin films:- Deposited aluminum thin films in cleanroom by sputtering process. Characterized the microstructure of these films with atomic force microscopy. -
StudentMetu Chemical Engineering Department 1998 - 2002
Cihan Oguz Skills
Cihan Oguz Education Details
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Georgia Institute Of TechnologyChemical And Biomolecular Engineering -
Orta Doğu Teknik Üniversitesi / Middle East Technical UniversityChemical Engineering
Frequently Asked Questions about Cihan Oguz
What company does Cihan Oguz work for?
Cihan Oguz works for Axle Informatics
What is Cihan Oguz's role at the current company?
Cihan Oguz's current role is Bioinformatics Scientist @ Axle Informatics/NIAID-NIH.
What is Cihan Oguz's email address?
Cihan Oguz's email address is c.****@****dos.com
What is Cihan Oguz's direct phone number?
Cihan Oguz's direct phone number is +140475*****
What schools did Cihan Oguz attend?
Cihan Oguz attended Georgia Institute Of Technology, Orta Doğu Teknik Üniversitesi / Middle East Technical University.
What skills is Cihan Oguz known for?
Cihan Oguz has skills like Systems Biology, Cardiovascular Disease, Matlab, Data Analysis, Bioinformatics, Statistics, Mathematical Modeling, Molecular Biology, Computational Biology, Machine Learning, Dimensionality Reduction, Latex.
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