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) …
Strengths and limitations of in silico tools to assess physicochemical properties, bioactivity, and bioavailability of food-derived peptides
F Rivero-Pino, MC Millan-Linares… - Trends in Food Science …, 2023 - Elsevier
Background Bioactive peptides obtained from different food sources have been proved to
exert several bioactivities, such as antioxidant, antihypertensive, antimicrobial, or anti …
exert several bioactivities, such as antioxidant, antihypertensive, antimicrobial, or anti …
Whey protein hydrolysates as a source of bioactive peptides for functional foods–Biotechnological facilitation of industrial scale-up
A Dullius, MI Goettert, CFV de Souza - Journal of Functional Foods, 2018 - Elsevier
Whey proteins, which possess the highest nutritional quality of all food proteins, are an
optimal source of functional food ingredients. Enzymatic hydrolysis of whey proteins …
optimal source of functional food ingredients. Enzymatic hydrolysis of whey proteins …
Recurrent neural network model for constructive peptide design
We present a generative long short-term memory (LSTM) recurrent neural network (RNN) for
combinatorial de novo peptide design. RNN models capture patterns in sequential data and …
combinatorial de novo peptide design. RNN models capture patterns in sequential data and …
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides
Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a
crucial role in a myriad of biological processes and cellular functions. AMP-related studies …
crucial role in a myriad of biological processes and cellular functions. AMP-related studies …
Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data
Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target
not only microorganisms but also viruses and cancer cells. Due to their lower selection for …
not only microorganisms but also viruses and cancer cells. Due to their lower selection for …
mACPpred: a support vector machine-based meta-predictor for identification of anticancer peptides
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer
cells. The accurate prediction of ACPs from given peptide sequences remains as an open …
cells. The accurate prediction of ACPs from given peptide sequences remains as an open …
Computational methods and tools in antimicrobial peptide research
PGA Aronica, LM Reid, N Desai, J Li… - Journal of Chemical …, 2021 - ACS Publications
The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that
has increased the number of diseases and infections that risk going untreated. There is an …
has increased the number of diseases and infections that risk going untreated. There is an …
Machine-learning-based prediction of cell-penetrating peptides and their uptake efficiency with improved accuracy
Cell-penetrating peptides (CPPs) can enter cells as a variety of biologically active
conjugates and have various biomedical applications. To offset the cost and effort of …
conjugates and have various biomedical applications. To offset the cost and effort of …
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 …