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)

Bio

I am a computational biologist with comprehensive expertise in bioinformatics, genomics, and structural biology. Serving as a Principal Investigator (PI) or co-PI for several federally funded research projects, my laboratory is dedicated to exploring nucleosomal DNA and nucleosome-protein interactions. In addition, I possess a keen interest in pioneering Artificial Intelligence models to tackle critical issues in the fields of medicine and systems biology. For more information, please visit my personal website

585-475-4115

Personal Links
Areas of Expertise

Select Scholarship

Journal Paper
Olatunji, Isaac and Feng Cui. "Multimodal AI for prediction of distant metastasis in carcinoma patients." Frontiers in Bioinformatics 3. (2023): 1131021. Web.
Subramanya, Sridevi K., et al. "Deep learning for histopathological segmentation of smooth muscle in the urinary bladder." BMC Medical Informatics and Decision Making 23. (2023): 122. Web.
Rynkiewicz, Patrick, et al. "Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains." Journal of Biomolecular Structure and Dynamics 40. 21 (2022): 10978-10996. Web.
Kc, Kishan, et al. "Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks." IEEE/ACM Transaction on Computational Biology and Bioinformatics 19. 2 (2022): 676-687. Web.
Gupta, Aditya, Andrew J. Rosato, and Feng Cui. "Vaccine candidate designed against carcinoembryonic antigen-related cell adhesion molecules using immunoinformatics tools." Journal of Biomolecular Structure and Dynamics 39. 16 (2021): 6084–6098. Web.
Freewoman, Julia M, Rajiv Snape, and Feng Cui. "Temporal gene regulation by p53 is associated with the rotational setting of its binding sites in nucleosomes." Cell Cycle 20. 8 (2021): 792-807. Web.
Kc, Kishan, et al. "Machine learning predicts nucleosome binding modes of transcription factors." BMC Bioinformatics 22. (2021): 166. Web.
Yin, Peng-Nien, et al. "Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches." BMC Medical Informatics and Decision Making 20. 1 (2020): 162. Web.
Zhang, Jimmy F., et al. "BioVR: a platform for virtual reality assisted biological data integration and visualization." BMC Bioinformatics 20. (2019): 78. Web.
KC, Kishan, et al. "GNE: a deep learning framework for gene network inference by aggregating biological information." BMC Systems Biology 13. (2019): 38. Web.
Wright, Gregory M and Feng Cui. "The nucleosome position-encoding WW/SS sequence pattern is depleted in mammalian genes relative to other eukaryotes." Nucleic Acids Research 47. 15 (2019): 7942–7954. Print.
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.
Published Conference Proceedings
Kc, Kishan, et al. "Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction." Proceedings of the 2020 25th International Conference on Pattern Recognition (ICPR), 10-15 Jan. 2021, Milan, Italy. Ed. Rita Cucchiara, Alberto Del Bimbo, and Stan Sclaroff. Milan, Italy: n.p., 2021. Web.
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.

Currently Teaching

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-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-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-327
3 Credits
This course addresses the fundamental concepts of bioinformatics, focusing on computational analysis of nucleic acids and proteins. Utilization of computational programs for analysis of individual and multiple sequences for functional and evolutionary information will be discussed. The computational laboratory will highlight the applications available for analysis of molecular sequences.
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-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-689
1 - 4 Credits
This is a graduate course on a topic that is not part of the formal curriculum. This course is structured as an ordinary course and has specific prerequisites, contact hours, and examination procedures.
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-791
0 Credits
Continuation of Thesis
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.

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