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논문검색

Machine Learning Approaches for Anticancer Peptide Discovery : A Comprehensive Review

원문정보

Priya Dharshini

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초록

영어

Invasive species are organisms that are introduced into places outside of their natural distribution range. The global pet trade is facilitating the introduction of invasive species into new countries and areas. Among the introduced alien species, turtles are one of the most common animal groups whether lives in wetland ecosystems, such as wetlands or reservoirs. Like other countries around the world, exotic turtles is becoming a growing concern for the wetland ecosystem in South Korea. In this study, we report new reports of subspecies of Painted turtle (Chrysemys spp.): Chrysemys picta marginata, C. p. bellii and C. dorsalis, from the reservoirs in downtown Cheongju and Gwangju, South Korea. We used morphological features, such as the characteristics of the legs, plastron, and carapace, to identify the turtles. It is assumed that all turtles were artificially released into nature. Considering the increasing number of reports on the introduction of alien invasive turtles in Korean wetlands, we recommend the formulation of an immediate and systematic management plan for pet trades and organized continuous monitoring programs.

목차

Abstract
1. Introduction
2. Peptides as Promising Anticancer Agents
3. Data Sources and Datasets for Bioactive and Therapeutic Peptides
4. Existing Machine Learning approaches for the prediction of ACPs
5. Model refinement and Assessment of Model Performance
6. Web server development
7. Conclusion
References
Table
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저자정보

  • Priya Dharshini Computational Biology Laboratory, Department of Genetic Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur-603203, Tamil Nadu, India

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