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Towards drug repositioning: a unified computational framework for integrating multiple aspects of drug similarity and disease similarity

Ping Zhang, Fei Wang, Jianying Hu
2014 AMIA Annual Symposium Proceedings  
In this paper, we propose a unified computational framework, called DDR, to predict novel drug-disease associations.  ...  It utilizes multiple drug similarity networks, multiple disease similarity networks, and known drug-disease associations to explore potential new associations among drugs and diseases with no known links  ...  In this paper, we propose a unified computational framework for drug repositioning hypothesis generation, by integrating multiple Drug information sources and multiple Disease information sources to facilitate  ... 
pmid:25954437 pmcid:PMC4419869 fatcat:5hfmoxxopnfvjbnbl5lwbgg2gu

Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding

M. Iskar, G. Zeller, P. Blattmann, M. Campillos, M. Kuhn, K. H. Kaminska, H. Runz, A.-C. Gavin, R. Pepperkok, V. van Noort, P. Bork
2014 Molecular Systems Biology  
homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of a-adrenergic receptor  ...  Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system.  ...  Acknowledgements We thank John P Overington, Sevi Durdu, Christina Besir, Elisabeth Georgii, Christian Tischer and members of the Bork group for helpful discussions.  ... 
doi:10.1038/msb.2013.20 pmid:23632384 pmcid:PMC3658274 fatcat:vc4w7uowlrffndysrbvwrl5jta

A survey of current trends in computational drug repositioning

Jiao Li, Si Zheng, Bin Chen, Atul J. Butte, S. Joshua Swamidass, Zhiyong Lu
2015 Briefings in Bioinformatics  
In this review, we show recent advancements in the critical areas of computational drug repositioning from multiple aspects.  ...  Computational drug repositioning or repurposing is a promising and efficient tool for discovering new uses from existing drugs and holds the great potential for precision medicine in the age of big data  ...  Acknowledgment The authors would like to thank Dr Pankaj Agarwal for his helpful discussion.  ... 
doi:10.1093/bib/bbv020 pmid:25832646 pmcid:PMC4719067 fatcat:aogwknlldvhtxfct5wwmorqtk4

Towards reproducible computational drug discovery

Nalini Schaduangrat, Samuel Lampa, Saw Simeon, Matthew Paul Gleeson, Ola Spjuth, Chanin Nantasenamat
2020 Journal of Cheminformatics  
It is therefore inevitable that the field of computational drug design would adopt an open approach towards the collection, curation and sharing of data/code.  ...  The reproducibility of experiments has been a long standing impediment for further scientific progress.  ...  Sirarat Sarntivijai from the European Bioinformatics Institute and Dr. Likit Preeyanon from the Department of Community Medical Technology for fruitful discussions.  ... 
doi:10.1186/s13321-020-0408-x pmid:33430992 fatcat:bvdcvjhi4jhlnifpc25t6cjthq

A data-driven methodology towards evaluating the potential of drug repurposing hypotheses

Lucía Prieto Santamaría, Esther Ugarte Carro, Marina Díaz Uzquiano, Ernestina Menasalvas Ruiz, Yuliana Pérez Gallardo, Alejandro Rodríguez-González
2021 Computational and Structural Biotechnology Journal  
Computational drug repurposing methods make use of modern heterogeneous biomedical data to identify and prioritize new indications for old drugs.  ...  In the current paper, we present a new complete methodology to evaluate new potentially repurposable drugs based on disease-gene and disease-phenotype associations, identifying significant differences  ...  Acknowledgements The work is a result of the project "DISNET (Creation and analysis of disease networks for drug repurposing from heterogeneous data sources applied to rare diseases)", that is being developed  ... 
doi:10.1016/j.csbj.2021.08.003 pmid:34471499 pmcid:PMC8387760 fatcat:6qlx5g6wz5gblc6ouvxykxjge4

A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions

Tamer N. Jarada, Jon G. Rokne, Reda Alhajj
2020 Journal of Cheminformatics  
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases.  ...  Since drug repositioning relies on data for existing drugs and diseases the enormous growth of publicly available large-scale biological, biomedical, and electronic health-related data along with the high-performance  ...  [116] introduced a unified computational framework for integrating numerous biological and biomedical sources in order to infer novel drugdrug similarities as well as disease-disease similarities.  ... 
doi:10.1186/s13321-020-00450-7 pmid:33431024 fatcat:yymhfsis4vgibo4surxzcrvp5m

The assessment of efficient representation of drug features using deep learning for drug repositioning

Mahroo Moridi, Marzieh Ghadirinia, Ali Sharifi-Zarchi, Fatemeh Zare-Mirakabad
2019 BMC Bioinformatics  
In this study, we present a non-linear method for drug repositioning. We extract four drug features and two disease features to find the semantic relations between drugs and diseases.  ...  This strategy is mostly used in cases with a limited number of candidate pairs of drugs and diseases. In other words, they are not scalable to a large number of drugs and diseases.  ...  [19] proposed a network-based approach using a unified framework for integrating multiple aspects of drug similarity and disease similarity.  ... 
doi:10.1186/s12859-019-3165-y pmid:31726977 pmcid:PMC6854697 fatcat:ttxnoqfvkndophro6gpog5pwre

Applications of Genome-Wide Screening and Systems Biology Approaches in Drug Repositioning

Elyas Mohammadi, Rui Benfeitas, Hasan Turkez, Jan Boren, Jens Nielsen, Mathias Uhlen, Adil Mardinoglu
2020 Cancers  
Drug repositioning presents a suitable approach for overcoming these issues by re-evaluating biological targets and modes of action of approved drugs.  ...  and uncovers unanticipated modes of action for available drugs.  ...  Pipeline of drug repositioning for a specific cancer or other disease.  ... 
doi:10.3390/cancers12092694 pmid:32967266 pmcid:PMC7563533 fatcat:s65x2effwbeuzelrfvmmvruco4

Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm

Huimin Luo, Jianxin Wang, Min Li, Junwei Luo, Xiaoqing Peng, Fang-Xiang Wu, Yi Pan
2016 Bioinformatics  
Many computational strategies for drug repositioning have been proposed, which are based on similarities among drugs and diseases.  ...  Motivation: Drug repositioning, which aims to identify new indications for existing drugs, offers a promising alternative to reduce the total time and cost of traditional drug development.  ...  Funding: This work is supported in part by the National Natural Science Foundation of China under Grant No. 61232001, No.61370024, No. 61428209, and the Program for New Century Excellent Talents in University  ... 
doi:10.1093/bioinformatics/btw228 pmid:27153662 fatcat:43dkh2ahpbbiteb5qo5bauxeku

Drug Repositioning by Merging Active Subnetworks Validated in Cancer and COVID-19 [article]

Marta Lucchetta, MARCO Pellegrini
2021 medRxiv   pre-print
We describe DrugMerge as a methodology for preclinical computational drug repositioning based on merging multiple drug rankings obtained with an ensemble of Disease Active Subnetwork construction algorithms  ...  Computational Drug Repositioning aims at ranking and selecting existing drugs for use in novel diseases or existing diseases for which these drugs were not originally designed.  ...  M.P. and M.L. interpreted the results and wrote the manuscript. All authors reviewed the manuscript.  ... 
doi:10.1101/2021.05.13.21257140 fatcat:jxhdr76oszgkfh5tn6zlzvbnwi

Drug Repositioning for Noonan and LEOPARD Syndromes by Integrating Transcriptomics With a Structure-Based Approach

Liyuan Zhu, Ruth Roberts, Ruili Huang, Jinghua Zhao, Menghang Xia, Brian Delavan, Mike Mikailov, Weida Tong, Zhichao Liu
2020 Frontiers in Pharmacology  
In this study, we implemented a hybrid computational drug repositioning framework by integrating transcriptomic and structure-based approaches to explore potential treatment options for NS and LS.  ...  Altogether, this hybrid computational drug repositioning approach has highlighted a number of drug candidates for NS and LS and could be applied to identifying drug candidates for other diseases as well  ...  In this study, we implemented a hybrid computational drug repositioning framework by integrating transcriptomic and structure-based approaches to explore potential treatment options for NS and LS.  ... 
doi:10.3389/fphar.2020.00927 pmid:32676024 pmcid:PMC7333460 fatcat:hqsyzbhejbe53mrkft4owwldbm

Identification of drug candidates and repurposing opportunities through compound–target interaction networks

Anna Cichonska, Juho Rousu, Tero Aittokallio
2015 Expert Opinion on Drug Discovery  
Janica Wakkinen and Dr. Simon Anders for many useful discussions about different types of experimental assays and computational models.  ...  acid sequences, and Gene Ontology classes to compute multiple drug--drug and target--target similarity measures integrated in the logistic regression-based SITAR (Similarity-based Inference of drug-TARgets  ...  However, Wang et al. introduced a network-based method that integrates these two tasks into a unified framework, termed Triple Layer Heterogeneous Graph Based Inference (TL_HGBI) [45] .  ... 
doi:10.1517/17460441.2015.1096926 pmid:26429153 fatcat:vtz37pji6jcnlmcuw6k3v7t3kq

Drug Discovery in a Multidimensional World: Systems, Patterns, and Networks

Joel T. Dudley, Eric Schadt, Marina Sirota, Atul J. Butte, Euan Ashley
2010 Journal of Cardiovascular Translational Research  
Recent advances in molecular profiling technologies and development of sophisticated computational approaches for analyzing these data are providing new, systems-oriented approaches towards drug discovery  ...  We also highlight several applications of these system-oriented approaches across various aspects of drug discovery, including target discovery, drug repositioning and drug toxicity.  ...  AJB is supported by funding from the National Library of Medicine (R01 LM009719).  ... 
doi:10.1007/s12265-010-9214-6 pmid:20677029 fatcat:4xlqxxttnvfvri5hkqkarqdjvy

Translational Bioinformatics Approaches to Drug Development

Ben Readhead, Joel Dudley
2013 Advances in Wound Care  
These include methods for data driven disease classification, drug repositioning, identification of disease biomarkers, and the creation of disease network models, each with significant impacts on drug  ...  A variety of powerful informatics methods for organizing and leveraging the vast wealth of available molecular measurements available for a broad range of disease contexts have recently emerged.  ...  Multiple approaches have been used in drug repositioning efforts, ranging from blind screening of libraries of drug compounds against model systems, to data-driven computational approaches that integrate  ... 
doi:10.1089/wound.2012.0422 pmid:24527359 pmcid:PMC3817001 fatcat:tnicjcbmzndg5c7lczl2fso434

Network-based machine learning and graph theory algorithms for precision oncology

Wei Zhang, Jeremy Chien, Jeongsik Yong, Rui Kuang
2017 npj Precision Oncology  
, candidate targets and repositioned drugs for personalized treatment.  ...  We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning  ...  The dbGaP accession number to the specific version of the TCGA dataset is phs000178.v9.p8. This research work is supported by a grant from the National Science Foundations, USA (NSF III 1149697).  ... 
doi:10.1038/s41698-017-0029-7 pmid:29872707 pmcid:PMC5871915 fatcat:yqeb4ntx7rgy3g5yep53u57wgq
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