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) …
Antimicrobial peptides derived from insects offer a novel therapeutic option to combat biofilm: A review
Biofilms form a complex layer with defined structures, that attach on biotic or abiotic surfaces,
are tough to eradicate and tend to cause some resistance against most antibiotics. Several …
are tough to eradicate and tend to cause some resistance against most antibiotics. Several …
A bioinformatic study of antimicrobial peptides identified in the Black Soldier Fly (BSF) Hermetia illucens (Diptera: Stratiomyidae)
Antimicrobial peptides (AMPs) play a key role in the innate immunity, the first line of defense
against bacteria, fungi, and viruses. AMPs are small molecules, ranging from 10 to 100 …
against bacteria, fungi, and viruses. AMPs are small molecules, ranging from 10 to 100 …
AntiCP 2.0: an updated model for predicting anticancer peptides
Increasing use of therapeutic peptides for treating cancer has received considerable
attention of the scientific community in the recent years. The present study describes the in …
attention of the scientific community in the recent years. The present study describes the in …
mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation
Motivation Cardiovascular disease is the primary cause of death globally accounting for
approximately 17.7 million deaths per year. One of the stakes linked with cardiovascular …
approximately 17.7 million deaths per year. One of the stakes linked with cardiovascular …
iAFPs-EnC-GA: identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach
Fungal infections have become a serious health concern for human beings worldwide.
Fungal infections usually occur when the invading fungus appear on a particular part of the …
Fungal infections usually occur when the invading fungus appear on a particular part of the …
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 …
iBCE-EL: a new ensemble learning framework for improved linear B-cell epitope prediction
Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine
development, antibody production, and disease prevention and diagnosis. Due to the …
development, antibody production, and disease prevention and diagnosis. Due to the …
Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19
Abstract Interleukin 6 (IL-6) is a pro-inflammatory cytokine that stimulates acute phase
responses, hematopoiesis and specific immune reactions. Recently, it was found that the IL …
responses, hematopoiesis and specific immune reactions. Recently, it was found that the IL …