Feng Cui Headshot

Feng Cui

Associate Professor
Thomas H. Gosnell School of Life Sciences
College of Science
Graduate Director of Bioinformatics

585-475-4115
Office Location

Feng Cui

Associate Professor
Thomas H. Gosnell School of Life Sciences
College of Science
Graduate Director of Bioinformatics

Education

MS, Truman State University; Ph.D., Iowa State University; MD, Hunan Medical University (China)

585-475-4115

Areas of Expertise
p53
chromatin organization
Machine Learning
biological data visualization

Currently Teaching

BIOL-694
3 Credits
This course will explore two facets of protein molecules: their separation and their structure. The structure component will build upon information from earlier bioinformatics courses. Protein separation techniques will be addressed in lectures with descriptions of 2D gel electrophoresis and chromatography. Algorithms of protein secondary structure prediction will be implemented. Experimental techniques for tertiary structure determination such as NMR will be covered. The course will also include the analysis of inter-molecular interactions, such as ligand/receptor pairing, by employing software that permits modeling of molecular docking experiments.
BIOL-495
1 - 4 Credits
This course is a faculty-directed student project or research involving laboratory or field work, computer modeling, or theoretical calculations that could be considered of an original nature. The level of study is appropriate for students in their final two years of study.
BIOL-594
3 Credits
This course will explore two facets of protein molecules: separation and structure. The separation component will address common protein separation techniques such as 2D gel electrophoresis and chromatography. The structure component will follow the levels of protein structures, focusing on both experimental and computational methods to determine protein structures. Methods for determining primary structures such as Edman degradation method, Sanger method and mass spectrometry will be taught in lectures. Algorithms of predicting secondary structures will be introduced and implemented. Tertiary structure determination techniques such as NMR will be covered, with an emphasis on proton NMR, 13C NMR and multi-dimensional NMR. Homology modeling will be used to predict protein tertiary structures.
BIOL-798
1 - 4 Credits
This course is a faculty-directed, graduate level tutorial of appropriate topics that are not part of the formal curriculum.
BIOL-498
1 - 4 Credits
This course is a faculty-directed tutorial of appropriate topics that are not part of the formal curriculum. The level of study is appropriate for student in their final two years of study.
BIOL-301
1 - 4 Credits
This course allows students to assist in a class or laboratory for which they have previously earned credit. The student will assist the instructor in the operation of the course. Assistance by the student may include fielding questions, helping in workshops, and assisting in review sessions. In the case of labs, students may also be asked to help with supervising safety practices, waste manifestation, and instrumentation.
BIOL-791
0 Credits
Continuation of Thesis
BIOL-298
1 - 4 Credits
This course is a faculty-directed tutorial of appropriate topics that are not part of the formal curriculum. The level of study is appropriate for student in their first three years of study.
BIOL-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
BIOL-295
1 - 4 Credits
This course is a faculty-directed student project or research involving laboratory work, computer modeling, or theoretical calculations that could be considered of an original nature. The level of study is appropriate for students in their first three years of study.
BIOL-330
3 Credits
Bioinformatics introduces students to the analysis of biological sequences: DNA, mRNA, and protein. Emphasis is placed on classical bioinformatics analyses such as gene prediction, sequence alignment, and phylogenetics. The methods are applicable to both human and model organism studies in medical, biotechnological, and classical biology research.

Select Scholarship

Published Conference Proceedings
Li, Rui, et al. "Sparse Covariance Modeling in High Dimensions with Gaussian Processes." Proceedings of the Neural Information Processing Systems 2018. Ed. S. Bengio, et al. Montreal, Canada: n.p., 2018. Web.
Bao, Feifei, et al. "P53 Binding Sites in Normal and Cancer Cells are Characterized by Distinct Chromatin Context." Proceedings of the AACR Annual Meeting 2018. Ed. Chi Van Dang. Chicago, IL: n.p., 2018. Print.
Journal Paper
F., Bao, et al. "P53 Binding Sites in Normal and Cancer Cells are Characterized by Distinct Chromatin Context." Cell Cycle 16. 21 (2017): 2073-2085. Print.
Cole, Hope A., et al. "Novel Nucleosomal Particles Containing Core Histones and Linker DNA but no Histone H1." Nucleic Acids Research 44. 2 (2016): 573-581. Print.
Ocampo, Josefina, et al. "The Proto-chromatosome: A Fundamental Subunit of Chromatin?" Nucleus 7. 4 (2016): 382-387. Print.
LoVerso, Peter R and Feng Cui. "A Computational Pipeline for Cross-Species Analysis of RNA-seq Data Using R and Bioconductor." Bioinformatics and Biology Insights 9. (2015): 165-174. Print.
LoVerso, Peter R, Christopher M Wachter, and Feng Cui. "Cross-species Transcriptomic Comparison of In Vitro and In Vivo Mammalian Neural Cells." Bioinformatics and Biology Insights 9. (2015): 153-164. Print.
Norouzi, Davood, et al. "Topological diversity of chromatin fibers: Interplay between nucleosome repeat length, DNA linking number and the level of transcription." AIMS Biophysics 2. 4 (2015): 613-629. Print.
Cui, Feng and Victor B. Zhurkin. "Rotational Positioning of Nucleosomes Facilitates Selective Binding of p53 to Response Elements Associated with Cell Cycle Arrest." Nucleic Acids Research 42. 2 (2014): 836-847. Print.
Cui, Feng, et al. "Prediction of Nucleosome Rotational Positioning in Yeast and Human Genomes Based on Sequence-dependent DNA Anisotropy." BMC Bioinformatics 15. (2014): 313. Print.
Alharbi, Bader A., et al. "nuMap: A Web Platform for Accurate Prediction of Nucleosome Positioning." Genomics Proteomics and Bioinformatics 12. 5 (2014): 249-253. Print.
Cui, F, et al. "Transcriptional Activation of Yeast Genes Disrupts Intragenic Nucleosome Phasing." Nucleic Acids Research 40. 21 (2012): 10753-10764. Print.
Macvanin, M, et al. "Noncoding RNAs Binding to the Nucleoid Protein HU in Escherichia Coli." Journal of Bacteriology 194. 22 (2012): 6046-6055. Print.