A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Using an Optimal Set of Features with a Machine Learning-Based Approach to Predict Effector Proteins for Legionella pneumophila
[article]
2018
bioRxiv
pre-print
Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several machine learning algorithms have been developed to predict effector proteins, potentially facilitating experimental verification. However, inconsistencies exist between their results. Previously we analysed the disparate sets of predictive features
doi:10.1101/383570
fatcat:zasr6w5fsvcwjllzaj7eeh6mxa