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Open MoA : revealing the mechanism of action (MoA) based on network topology and hierarchy

Liao, Xinmeng (author)
KTH,Proteinvetenskap,Science for Life Laboratory, SciLifeLab
Ozcan, Mehmet (author)
KTH,Science for Life Laboratory, SciLifeLab,Proteinvetenskap,Department of Medical Biochemistry, Faculty of Medicine, Zonguldak Bulent Ecevit University, 67630 Zonguldak, Turkey
Shi, Mengnan (author)
KTH,Science for Life Laboratory, SciLifeLab,Systembiologi
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Kim, Woonghee (author)
KTH,Systembiologi,Science for Life Laboratory, SciLifeLab
Jin, Han (author)
KTH,Science for Life Laboratory, SciLifeLab,Systembiologi
Li, Xiangyu (author)
Guangzhou National Laboratory, Guangzhou, Guangdong Province 510005, China
Turkez, Hasan (author)
Department of Medical Biology, Faculty of Medicine, Atatürk University, Erzurum 25240, Turkey
Achour, Adnane (author)
Karolinska Institutet
Uhlén, Mathias (author)
KTH,Science for Life Laboratory, SciLifeLab,Systembiologi
Mardinoglu, Adil (author)
KTH,Science for Life Laboratory, SciLifeLab,Systembiologi,Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London SE1 9RT, United Kingdom
Zhang, Cheng (author)
KTH,Science for Life Laboratory, SciLifeLab,Systembiologi
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 (creator_code:org_t)
Oxford University Press (OUP), 2023
2023
English.
In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 39:11
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • MOTIVATION: Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA). RESULTS: We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/XinmengLiao/Open_MoA.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

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