iAFPs-EnC-GA: Identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach-Reference-Cited by-同舟云学术

iAFPs-EnC-GA: Identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach

Published:2022-03 Issue: Volume:222 Page:104516
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Ahmad Ashfaq,Akbar Shahid^ORCID,Tahir Muhammad,Hayat Maqsood,Ali Farman

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference77 articles.

1. Global and multi-national prevalence of fungal diseases—estimate precision;Bongomin;J. Fungi,2017

2. Tackling emerging fungal threats to animal health, food security and ecosystem resilience;Fisher;Royal Soc.,2016

3. Emerging threats in antifungal-resistant fungal pathogens;Sanglard;Front. Med.,2016

4. Antibiotic-resistant bacteria: a challenge for the food industry;Capita;Crit. Rev. Food Sci. Nutr.,2013

5. Antifungal peptides as therapeutic agents;Fernández de Ullivarri;Front. Cell. Infect. Microbiol.,2020

Cited by 35 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of cervical lymph nodes recurrence after radiotherapy for early nasopharyngeal carcinoma via unsupervised diagnostic feature learning and supervised ensemble classifier learning;Biomedical Signal Processing and Control;2024-05

2. Interpretable CRISPR/Cas9 off-target activities with mismatches and indels prediction using BERT;Computers in Biology and Medicine;2024-02

3. Generating bulk RNA-Seq gene expression data based on generative deep learning models and utilizing it for data augmentation;Computers in Biology and Medicine;2024-02

4. Isolation and identification of anti-colorectal cancer peptides from walnut proteins and associated in silico analysis;Journal of Functional Foods;2024-01

5. BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients;Scientific Reports;2023-12-18