DeepAI AI Chat
Log In Sign Up

Classifying Antimicrobial and Multifunctional Peptides with Bayesian Network Models

04/17/2018
by   Rainier Barrett, et al.
0

Bayesian network models are finding success in characterizing enzyme-catalyzed reactions, slow conformational changes, predicting enzyme inhibition, and genomics. In this work, we apply them to statistical modeling of peptides by simultaneously identifying amino acid sequence motifs and using a motif-based model to clarify the role motifs may play in antimicrobial activity. We construct models of increasing sophistication, demonstrating how chemical knowledge of a peptide system may be embedded without requiring new derivation of model fitting equations after changing model structure. These models are used to construct classifiers with good performance (94 Matthews correlation coefficient of 0.87) at predicting antimicrobial activity in peptides, while at the same time being built of interpretable parameters. We demonstrate use of these models to identify peptides that are potentially both antimicrobial and antifouling, and show that the background distribution of amino acids could play a greater role in activity than sequence motifs do. This provides an advancement in the type of peptide activity modeling that can be done and the ease in which models can be constructed.

READ FULL TEXT

page 1

page 2

page 3

page 4

02/22/2018

Sparse Bayesian dynamic network models, with genomics applications

Network models have become an important topic in modern statistics, and ...
10/28/2022

SG-VAD: Stochastic Gates Based Speech Activity Detection

We propose a novel voice activity detection (VAD) model in a low-resourc...
01/29/2020

Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion

Activity coefficients, which are a measure of the non-ideality of liquid...
10/19/2012

Modeling with Copulas and Vines in Estimation of Distribution Algorithms

The aim of this work is studying the use of copulas and vines in the opt...
07/27/2020

Modeling the Influence of Visual Density on Cluster Perception in Scatterplots Using Topology

Scatterplots are used for a variety of visual analytics tasks, including...
04/28/2022

Who will stay? Using Deep Learning to predict engagement of citizen scientists

Citizen science and machine learning should be considered for monitoring...
01/21/2021

Toxicity Detection in Drug Candidates using Simplified Molecular-Input Line-Entry System

The need for analysis of toxicity in new drug candidates and the require...