Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings
University of Electronic Science and Technology of China · Huzhou University · +6 more institutions
Abstract
Snake venom contains many toxic proteins that can destroy the circulatory system or nervous system of prey. Studies have found that these snake venom proteins have the potential to treat cardiovascular and nervous system diseases. Therefore, the study of snake venom protein is conducive to the development of related drugs. The research technologies based on traditional biochemistry can accurately identify these proteins, but the experimental cost is high and the time is long. Artificial intelligence technology provides a new means and strategy for large-scale screening of snake venom proteins from the perspective of computing. In this paper, we developed a sequence-based computational method to recognize snake…
Citation impact
- FWCI
- 61.84
- Percentile
- 100%
- References
- 36
Authors
9- HZHasan Zulfiqar
University of Electronic Science and Technology of China, Huzhou University
- ZGZhiling Guo
- RMRamala Masood Ahmad
University of Faisalabad, University of Agriculture Faisalabad
- ZAZahoor Ahmed
University of Electronic Science and Technology of China, Huzhou University
- PCPeiling Cai
Chengdu University
Topics & keywords
- Computer science
- Artificial intelligence
- Snake venom
- Robustness (evolution)
- Deep learning
- Support vector machine
- Machine learning
- Feature vector