Antibiotic Lethality Is Impacted by Nutrient Availabilities: New Insights from Machine Learning

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In this issue of Cell, Yang, Wright et al. describe a machine learning approach that that can provide mechanistic insight from chemical screens. They use this approach to uncover how the nutritional availability for Escherichia coli impacts lethality toward three widely used antibiotics.
Original languageEnglish
JournalCELL
Volume177
Issue number6
Pages (from-to)1373-1374
ISSN0092-8674
DOIs
Publication statusPublished - 2019

Cite this

@article{cb8a189037e748edb6cd7f4d506eea2d,
title = "Antibiotic Lethality Is Impacted by Nutrient Availabilities: New Insights from Machine Learning",
abstract = "In this issue of Cell, Yang, Wright et al. describe a machine learning approach that that can provide mechanistic insight from chemical screens. They use this approach to uncover how the nutritional availability for Escherichia coli impacts lethality toward three widely used antibiotics.",
author = "Jens Nielsen",
year = "2019",
doi = "10.1016/j.cell.2019.05.015",
language = "English",
volume = "177",
pages = "1373--1374",
journal = "Cell",
issn = "0092-8674",
publisher = "Cell Press",
number = "6",

}

Antibiotic Lethality Is Impacted by Nutrient Availabilities: New Insights from Machine Learning. / Nielsen, Jens.

In: CELL, Vol. 177, No. 6, 2019, p. 1373-1374.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Antibiotic Lethality Is Impacted by Nutrient Availabilities: New Insights from Machine Learning

AU - Nielsen, Jens

PY - 2019

Y1 - 2019

N2 - In this issue of Cell, Yang, Wright et al. describe a machine learning approach that that can provide mechanistic insight from chemical screens. They use this approach to uncover how the nutritional availability for Escherichia coli impacts lethality toward three widely used antibiotics.

AB - In this issue of Cell, Yang, Wright et al. describe a machine learning approach that that can provide mechanistic insight from chemical screens. They use this approach to uncover how the nutritional availability for Escherichia coli impacts lethality toward three widely used antibiotics.

U2 - 10.1016/j.cell.2019.05.015

DO - 10.1016/j.cell.2019.05.015

M3 - Journal article

VL - 177

SP - 1373

EP - 1374

JO - Cell

JF - Cell

SN - 0092-8674

IS - 6

ER -