Nathan Gravel

According to our database, Nathan Gravel authored at least 5 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Using explainable machine learning to uncover the kinase-substrate interaction landscape.

Zhongliang Zhou, Wayland Yeung, Saber Soleymani, Nathan Gravel, Mariah Salcedo, Sheng Li, Natarajan Kannan

Bioinform., 2024

2023

Phosformer: an explainable transformer model for protein kinase-specific phosphorylation predictions.

Zhongliang Zhou, Wayland Yeung, Nathan Gravel, Mariah Salcedo, Saber Soleymani, Sheng Li, Natarajan Kannan

Bioinform., February, 2023

Tree visualizations of protein sequence embedding space enable improved functional clustering of diverse protein superfamilies.

Wayland Yeung, Zhongliang Zhou, Liju Mathew, Nathan Gravel, Rahil Taujale, Brady O'boyle, Mariah Salcedo, Aarya Venkat, William Lanzilotta, Sheng Li, Natarajan Kannan

Briefings Bioinform., January, 2023

XAI meets Biology: A Comprehensive Review of Explainable AI in Bioinformatics Applications.

Zhongliang Zhou, Mengxuan Hu, Mariah Salcedo, Nathan Gravel, Wayland Yeung, Aarya Venkat, Dongliang Guo, Jielu Zhang, Natarajan Kannan, Sheng Li

CoRR, 2023

2021

KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases.

Liang-Chin Huang, Rahil Taujale, Nathan Gravel, Aarya Venkat, Wayland Yeung, Dominic P. Byrne, Patrick A. Eyers, Natarajan Kannan

BMC Bioinform., 2021