PMID- 29688306
OWN - NLM
STAT- MEDLINE
DCOM- 20191017
LR  - 20230130
IS  - 1367-4811 (Electronic)
IS  - 1367-4803 (Print)
IS  - 1367-4803 (Linking)
VI  - 34
IP  - 18
DP  - 2018 Sep 15
TI  - EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to improve prediction 
      accuracy.
PG  - 3151-3159
LID - 10.1093/bioinformatics/bty325 [doi]
AB  - MOTIVATION: Availability of large-scale genomic, epigenetic and proteomic data in 
      complex diseases makes it possible to objectively and comprehensively identify 
      the therapeutic targets that can lead to new therapies. The Connectivity Map has 
      been widely used to explore novel indications of existing drugs. However, the 
      prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic 
      remains low. Here we present a novel high-performance drug repositioning approach 
      that improves over the state-of-the-art methods. RESULTS: We first designed an 
      expression weighted cosine (EWCos) method to minimize the influence of the 
      uninformative expression changes and then developed an ensemble approach termed 
      ensemble of multiple drug repositioning approaches (EMUDRA) to integrate EWCos 
      and three existing state-of-the-art methods. EMUDRA significantly outperformed 
      individual drug repositioning methods when applied to simulated and independent 
      evaluation datasets. We predicted using EMUDRA and experimentally validated an 
      antibiotic rifabutin as an inhibitor of cell growth in triple negative breast 
      cancer. EMUDRA can identify drugs that more effectively target disease gene 
      signatures and will thus be a useful tool for identifying novel therapies for 
      complex diseases and predicting new indications for existing drugs. AVAILABILITY 
      AND IMPLEMENTATION: The EMUDRA R package is available at doi: 
      10.7303/syn11510888. SUPPLEMENTARY INFORMATION: Supplementary data are available 
      at Bioinformatics online.
FAU - Zhou, Xianxiao
AU  - Zhou X
AD  - Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount 
      Sinai, New York, NY, USA.
AD  - Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at 
      Mount Sinai, New York, NY, USA.
FAU - Wang, Minghui
AU  - Wang M
AD  - Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount 
      Sinai, New York, NY, USA.
AD  - Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at 
      Mount Sinai, New York, NY, USA.
FAU - Katsyv, Igor
AU  - Katsyv I
AD  - Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount 
      Sinai, New York, NY, USA.
AD  - Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at 
      Mount Sinai, New York, NY, USA.
AD  - Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New 
      York, NY, USA.
FAU - Irie, Hanna
AU  - Irie H
AD  - Division of Hematology and Medical Oncology, Department of Medicine, Icahn School 
      of Medicine at Mount Sinai, New York, NY, USA.
AD  - Department of Oncological Sciences, Tisch Cancer Institute, Icahn School of 
      Medicine at Mount Sinai, New York, NY, USA.
FAU - Zhang, Bin
AU  - Zhang B
AD  - Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount 
      Sinai, New York, NY, USA.
AD  - Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at 
      Mount Sinai, New York, NY, USA.
AD  - Department of Oncological Sciences, Tisch Cancer Institute, Icahn School of 
      Medicine at Mount Sinai, New York, NY, USA.
LA  - eng
GR  - RF1 AG057440/AG/NIA NIH HHS/United States
GR  - RF1 AG054014/AG/NIA NIH HHS/United States
GR  - U01 AG052411/AG/NIA NIH HHS/United States
GR  - U01 AG046170/AG/NIA NIH HHS/United States
GR  - R01 AG057907/AG/NIA NIH HHS/United States
GR  - U01 AI111598/AI/NIAID NIH HHS/United States
GR  - R01 CA163772/CA/NCI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PL  - England
TA  - Bioinformatics
JT  - Bioinformatics (Oxford, England)
JID - 9808944
SB  - IM
MH  - *Algorithms
MH  - *Drug Repositioning
MH  - Epigenomics
MH  - Genomics
MH  - Proteomics
PMC - PMC6138000
EDAT- 2018/04/25 06:00
MHDA- 2019/10/18 06:00
PMCR- 2019/04/24
CRDT- 2018/04/25 06:00
PHST- 2017/05/21 00:00 [received]
PHST- 2018/04/20 00:00 [accepted]
PHST- 2018/04/25 06:00 [pubmed]
PHST- 2019/10/18 06:00 [medline]
PHST- 2018/04/25 06:00 [entrez]
PHST- 2019/04/24 00:00 [pmc-release]
AID - 4983064 [pii]
AID - bty325 [pii]
AID - 10.1093/bioinformatics/bty325 [doi]
PST - ppublish
SO  - Bioinformatics. 2018 Sep 15;34(18):3151-3159. doi: 10.1093/bioinformatics/bty325.