Student Presentations

CSI 5180 - Machine Learning for Bioinformatics

Student Presentation

Students	Paper	DOI
Ziyang Mao & Kaixi Xu (slides)	Malusare et al. (2024)	10.1093/bioadv/vbae117
Steven Wilson	Gupta et al. (2024)	10.1186/s13040-024-00399-5
Nicole Sabourin	Nam et al. (2018)	10.1093/bioinformatics/bty882
Rang Zhang	Nandi, Subramanian, and Sarkar (2017)	10.1039/C7MB00234C

References

Gupta, Richa, Mansi Bhandari, Anhad Grover, Taher Al-shehari, Mohammed Kadrie, Taha Alfakih, and Hussain Alsalman. 2024. “Predictive modeling of ALS progression: an XGBoost approach using clinical features.” BioData Mining 17 (1): 54. https://doi.org/10.1186/s13040-024-00399-5.

Malusare, Aditya, Harish Kothandaraman, Dipesh Tamboli, Nadia A Lanman, and Vaneet Aggarwal. 2024. “Understanding the natural language of DNA using encoder–decoder foundation models with byte-level precision.” Bioinformatics Advances 4 (1): vbae117. https://doi.org/10.1093/bioadv/vbae117.

Nam, Yonghyun, Jong Ho Jhee, Junhee Cho, Ji-Hyun Lee, and Hyunjung Shin. 2018. “Disease gene identification based on generic and disease-specific genome networks.” Bioinformatics 35 (11): 1923–30. https://doi.org/10.1093/bioinformatics/bty882.

Nandi, Sutanu, Abhishek Subramanian, and Ram Rup Sarkar. 2017. “An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.” Molecular BioSystems 13 (8): 1584–96. https://doi.org/10.1039/c7mb00234c.