Anticancer Peptides Classification Using Long-Short-Term Memory With Novel Feature Representation
TL;DR
This study uses Long-Short-Term Memory with a novel feature representation to classify anticancer peptides, addressing challenges in their identification and synthesis for cancer treatment.
Anticancer Peptides Classification Using Long-Short-Term Memory With Novel Feature Representation
Nazer Al Tahifah; Muhammad Sohail Ibrahim; Erum Rehman; Naveed Ahmed; Abdul Wahab; Shujaat Khan
https://doi.org/10.1109/ACCESS.2024.3523068
Volume 13
Cancer treatment is a challenging endeavor because of the intricacy, heterogeneity, and diversity of cancer causes. Comprehensive therapeutic approaches are crucial for cancer treatment. Anticancer peptides (ACPs) present a potentially effective therapeutic option. However, the extensive identification and synthesis of these peptides present a persistent difficulty that calls for the creation of e...