Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
S Basith, B Manavalan, T Hwan Shin… - Medicinal research …, 2020 - Wiley Online Library
Discovery and development of biopeptides are time‐consuming, laborious, and dependent
on various factors. Data‐driven computational methods, especially machine learning (ML) …
on various factors. Data‐driven computational methods, especially machine learning (ML) …
Antioxidant and antimicrobial peptides derived from food proteins
G López-García, O Dublan-García, D Arizmendi-Cotero… - Molecules, 2022 - mdpi.com
Recently, the demand for food proteins in the market has increased due to a rise in
degenerative illnesses that are associated with the excessive production of free radicals and …
degenerative illnesses that are associated with the excessive production of free radicals and …
DRAMP 3.0: an enhanced comprehensive data repository of antimicrobial peptides
G Shi, X Kang, F Dong, Y Liu, N Zhu, Y Hu… - Nucleic acids …, 2022 - academic.oup.com
Stapled antimicrobial peptides are an emerging class of artificial cyclic peptide molecules
which have antimicrobial activity and potent structure stability. We previously published the …
which have antimicrobial activity and potent structure stability. We previously published the …
dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data
The last 18 months, or more, have seen a profound shift in our global experience, with many
of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life …
of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life …
iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model
Tuberculosis (TB) is a worldwide illness caused by the bacteria Mycobacterium tuberculosis.
Owing to the high prevalence of multidrug-resistant tuberculosis, numerous traditional …
Owing to the high prevalence of multidrug-resistant tuberculosis, numerous traditional …
Machine learning prediction of antimicrobial peptides
Antibiotic resistance constitutes a global threat and could lead to a future pandemic. One
strategy is to develop a new generation of antimicrobials. Naturally occurring antimicrobial …
strategy is to develop a new generation of antimicrobials. Naturally occurring antimicrobial …
iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities
Antimicrobial peptides (AMPs) are short peptides that play crucial roles in diverse biological
processes and have various functional activities against target organisms. Due to the abuse …
processes and have various functional activities against target organisms. Due to the abuse …
pAtbP-EnC: identifying anti-tubercular peptides using multi-feature representation and genetic algorithm based deep ensemble model
Mycobacterium tuberculosis, a highly perilous pathogen in humans, serves as the causative
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
In silico Approaches for the Design and Optimization of Interfering Peptides Against Protein–Protein Interactions
Large contact surfaces of protein–protein interactions (PPIs) remain to be an ongoing issue
in the discovery and design of small molecule modulators. Peptides are intrinsically capable …
in the discovery and design of small molecule modulators. Peptides are intrinsically capable …
[HTML][HTML] AtbPpred: a robust sequence-based prediction of anti-tubercular peptides using extremely randomized trees
Mycobacterium tuberculosis is one of the most dangerous pathogens in humans. It acts as
an etiological agent of tuberculosis (TB), infecting almost one-third of the world's population …
an etiological agent of tuberculosis (TB), infecting almost one-third of the world's population …