Commit 0a43830c authored by Laurent Heirendt's avatar Laurent Heirendt
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Merge branch 'add-9p51-ch19' into 'master'

add 9p51-ch19

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......@@ -16,6 +16,7 @@ This website is under version control on the [LCSB Gitlab](https://gitlab.lcsb.u
<ul>
<li><a href="{{ '/frozen/8wvb-mt36' | relative_url }}">SMASCH: multi-appointment scheduling system for longitudinal clinical research studies</a></li>
<li><a href="{{ '/frozen/9p51-ch19' | relative_url }}">ChemPert: mapping between chemical perturbation and transcriptional response for noncancer cells</a></li>
<li><a href="{{ '/frozen/hr67-ba06' | relative_url }}">Age at onset as stratifier in idiopathic Parkinson's disease – effect of ageing and polygenic risk score on clinical phenotypes</a></li>
</ul>
......@@ -56,8 +57,8 @@ This website is under version control on the [LCSB Gitlab](https://gitlab.lcsb.u
<ul>
<li><a href="{{ '/frozen/lcsb-20191008-01' | relative_url }}">Reproducible generation of human midbrain organoids for in vitro modeling of Parkinson's disease</a></li>
<li><a href="{{ '/frozen/lcsb-20191309-02' | relative_url }}">Machine learning-assisted neurotoxicity prediction in human midbrain organoids</a></li>
<li><a href="{{ '/frozen/lcsb-2019130913-01' | relative_url }}">Synapse alterations precede neuronal damage and storage pathology in a human cerebral organoid model of CLN3-juvenile neuronal ceroid lipofuscinosis</a></li>
<li><a href="{{ '/frozen/lcsb-20191309-02' | relative_url }}">Machine learning-assisted neurotoxicity prediction in human midbrain organoids</a></li>
<li><a href="{{ '/frozen/lcsb-20190507-01' | relative_url }}">Mitochondrial morphology provides a mechanism for energy buffering at synapses</a></li>
<li><a href="{{ '/frozen/lcsb-20190326-01' | relative_url }}">Single-cell transcriptomics reveals multiple neuronal cell types in human midbrain-specific organoids</a></li>
<li><a href="{{ '/frozen/lcsb-20192701-01' | relative_url }}">Modeling Parkinson's disease in midbrain-like organoids</a></li>
......
---
layout: default
date: 2022-05-12
order: -1
title: "ChemPert: mapping between chemical perturbation and transcriptional response for noncancer cells"
permalink: /frozen/9p51-ch19
published: true
---
{% rtitle {{ page.title }} %}
Menglin Zheng, Satoshi Okawa, Miren Bravo, Fei Chen, María-Luz Martínez Chantar, Antonio del Sol
Prior knowledge of perturbation data can significantly assist in inferring the relationship between chemical perturbations and their specific transcriptional response. However, current databases mostly contain cancer cell lines, which are unsuitable for the aforementioned inference in non-cancer cells. Here we present ChemPert (https://chempert.uni.lu/), a database consisting of 82270 transcriptional signatures across 167 non-cancer cell types, enabling more accurate predictions of perturbation responses and drugs compared to cancer databases in non-cancer cells. In particular, ChemPert correctly predicted drug effects for treating non-alcoholic steatohepatitis and novel drugs for osteoarthritis. Overall, ChemPert provides a valuable resource for drug discovery in non-cancer diseases.
{% endrtitle %}
{% rblock Code %}
The source code cand be found on [Gitlab](https://gitlab.lcsb.uni.lu/CBG/chempert)
{% endrblock %}
{% rblock Data %}
The Supplementary Information can also be found [here](https://webdav-r3lab.uni.lu/public/data/9p51-ch19/).
{% endrblock %}
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