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Peptides

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Unveiling antimicrobial peptide-generating human proteases using PROTEASIX.

Journal of proteomics
UNLABELLED: Extracting information from peptidomics data is a major current challenge, as endogenous peptides can result from the activity of multiple enzymes. Proteolytic enzymes can display overlapping or complementary specificity. The activity spe...

HemoPred: a web server for predicting the hemolytic activity of peptides.

Future medicinal chemistry
AIM: Toxicity arising from hemolytic activity of peptides hinders its further progress as drug candidates.

MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm.

BMC bioinformatics
BACKGROUND: This work presents a machine learning strategy to increase sensitivity in tandem mass spectrometry (MS/MS) data analysis for peptide/protein identification. MS/MS yields thousands of spectra in a single run which are then interpreted by s...

Mapping membrane activity in undiscovered peptide sequence space using machine learning.

Proceedings of the National Academy of Sciences of the United States of America
There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature o...

ASAP: a machine learning framework for local protein properties.

Database : the journal of biological databases and curation
Determining residue-level protein properties, such as sites of post-translational modifications (PTMs), is vital to understanding protein function. Experimental methods are costly and time-consuming, while traditional rule-based computational methods...

Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra.

Journal of proteome research
A central problem in mass spectrometry analysis involves identifying, for each observed tandem mass spectrum, the corresponding generating peptide. We present a dynamic Bayesian network (DBN) toolkit that addresses this problem by using a machine lea...

Pan-Specific Prediction of Peptide-MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity.

Journal of immunology (Baltimore, Md. : 1950)
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. ...

An Artificial Neural Network Based Analysis of Factors Controlling Particle Size in a Virgin Coconut Oil-Based Nanoemulsion System Containing Copper Peptide.

PloS one
A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. F...

Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...

Machine learning approaches for discrimination of Extracellular Matrix proteins using hybrid feature space.

Journal of theoretical biology
Extracellular Matrix (ECM) proteins are the vital type of proteins that are secreted by resident cells. ECM proteins perform several significant functions including adhesion, differentiation, cell migration and proliferation. In addition, ECM protein...