PIMD: An Integrative Approach for Drug Repositioning Using Multiple Characterization Fusion

[1]  Van V. Brantner,et al.  Estimating the cost of new drug development: is it really 802 million dollars? , 2006, Health affairs.

[2]  Xiaobo Zhou,et al.  Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces , 2010, BMC Systems Biology.

[3]  David S. Wishart,et al.  DrugBank 4.0: shedding new light on drug metabolism , 2013, Nucleic Acids Res..

[4]  J. Mersey.  Long-term experience with terazosin for treatment of mild to moderate hypertension. , 1986, The American journal of medicine.

[5]  Christoph Steinbeck,et al.  BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontology , 2015, BMC Bioinformatics.

[6]  Louiqa Raschid,et al.  Ieee/acm Transactions on Computational Biology and Bioinformatics 1 Network-based Drug-target Interaction Prediction with Probabilistic Soft Logic , 2022 .

[7]  Yoshihiro Yamanishi,et al.  Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework , 2010, Bioinform..

[8]  Pankaj Agarwal,et al.  Systematic Drug Repositioning Based on Clinical Side-Effects , 2011, PloS one.

[9]  Xiang Zhang,et al.  Drug repositioning by integrating target information through a heterogeneous network model , 2014, Bioinform..

[10]  A. Ohta,et al.  Methylxanthines, inflammation, and cancer: fundamental mechanisms. , 2011, Handbook of experimental pharmacology.

[11]  Yuhao Wang,et al.  Predicting drug-target interactions using restricted Boltzmann machines , 2013, Bioinform..

[12]  Robert B. Russell,et al.  SuperTarget and Matador: resources for exploring drug-target relationships , 2007, Nucleic Acids Res..

[13]  Charles C. Persinger,et al.  How to improve R&D productivity: the pharmaceutical industry's grand challenge , 2010, Nature Reviews Drug Discovery.

[14]  Gang Fu,et al.  PubChem Substance and Compound databases , 2015, Nucleic Acids Res..

[15]  Yongcui Wang,et al.  Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data , 2013, PloS one.

[16]  J. Cerhan,et al.  Intake of coffee, caffeine and other methylxanthines and risk of Type I vs Type II endometrial cancer , 2013, British Journal of Cancer.

[17]  H. Itskovitz.  Alpha 1-blockade for the treatment of hypertension: a megastudy of terazosin in 2214 clinical practice settings. , 1994, Clinical therapeutics.

[18]  R. W. Hansen,et al.  The price of innovation: new estimates of drug development costs. , 2003, Journal of health economics.

[19]  Avi Ma'ayan,et al.  Drug-induced adverse events prediction with the LINCS L1000 data , 2016, Bioinform..

[20]  Jian-Yu Shi,et al.  Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering. , 2015, Methods.

[21]  Chee Keong Kwoh,et al.  Drug-target interaction prediction by learning from local information and neighbors , 2013, Bioinform..

[22]  S. Wakelin.  Systemic Drug Treatment in Dermatology : A Handbook , 2002 .

[23]  A Ward,et al.  Pentoxifylline , 1987, Drugs.

[24]  B Marshall,et al.  Gene Ontology Consortium: The Gene Ontology (GO) database and informatics resource , 2004, Nucleic Acids Res..

[25]  Shi-Hua Zhang,et al.  DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank , 2016, Bioinform..

[26]  Ping Zhang,et al.  Towards Drug Repositioning: A Unified Computational Framework for Integrating Multiple Aspects of Drug Similarity and Disease Similarity , 2014, AMIA.

[27]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[28]  D. di Bernardo,et al.  Identification of small molecules enhancing autophagic function from drug network analysis. , 2010, Autophagy.

[29]  J. O'dell,et al.  Treatment of rheumatoid arthritis with methotrexate alone, sulfasalazine and hydroxychloroquine, or a combination of all three medications. , 1996, The New England journal of medicine.

[30]  P. Hannonen,et al.  Sulfasalazine in early rheumatoid arthritis. A 48-week double-blind, prospective, placebo-controlled study. , 1993, Arthritis and rheumatism.

[31]  P. Lieberman.  Histamine, antihistamines, and the central nervous system. , 2009, Allergy and asthma proceedings.

[32]  T. Tsujii.  Comparison of prazosin, terazosin and tamsulosin in the treatment of symptomatic benign prostatic hyperplasia: A short‐term open, randomized multicenter study , 2000, International journal of urology : official journal of the Japanese Urological Association.

[33]  Yan Zhao,et al.  Drug repositioning: a machine-learning approach through data integration , 2013, Journal of Cheminformatics.

[34]  P. Zabel,et al.  Differences in the anti‐inflammatory effects of theophylline and pentoxifylline: important for the development of asthma therapy? , 1998, Allergy.

[35]  Xin Gao,et al.  An integrated structure- and system-based framework to identify new targets of metabolites and known drugs , 2015, Bioinform..

[36]  Yoshihiro Yamanishi,et al.  Supervised prediction of drug–target interactions using bipartite local models , 2009, Bioinform..

[37]  María Martín,et al.  UniProt: A hub for protein information , 2015 .

[38]  A. Hopkins.  Network pharmacology: the next paradigm in drug discovery. , 2008, Nature chemical biology.

[39]  J. Montastruc,et al.  A comparative study of QT prolongation with serotonin reuptake inhibitors , 2017, Psychopharmacology.

[40]  The Uniprot Consortium,et al.  UniProt: a hub for protein information , 2014, Nucleic Acids Res..

[41]  Elena Marchiori,et al.  Gaussian interaction profile kernels for predicting drug-target interaction , 2011, Bioinform..

[42]  A. Barabasi,et al.  Drug—target network , 2007, Nature Biotechnology.

[43]  A. Wróbel,et al.  Lignans and norlignans inhibit multidrug resistance protein 1 (MRP1/ABCC1)-mediated transport. , 2010, Anticancer research.

[44]  Hao Ding,et al.  Collaborative matrix factorization with multiple similarities for predicting drug-target interactions , 2013, KDD.

[45]  Yoshihiro Yamanishi,et al.  DINIES: drug–target interaction network inference engine based on supervised analysis , 2014, Nucleic Acids Res..

[46]  Zoran Obradovic,et al.  Computational Drug Repositioning by Ranking and Integrating Multiple Data Sources , 2013, ECML/PKDD.

[47]  Tao Jiang,et al.  NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions , 2018, bioRxiv.

[48]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Katarzyna H. Kaminska,et al.  Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding , 2013, Molecular systems biology.

[50]  M. Boguski,et al.  Repurposing with a Difference , 2009, Science.

[51]  Tao Jiang,et al.  ChemmineR: a compound mining framework for R , 2008, Bioinform..

[52]  Hui Liu,et al.  Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks , 2016, BMC Bioinformatics.

[53]  E. Chi,et al.  Safety, Tolerability, and Effect of Food on the Pharmacokinetics of Iloperidone (HP 873), a Potential Atypical Antipsychotic , 1995, Journal of clinical pharmacology.

[54]  Song He,et al.  Discovery of novel therapeutic properties of drugs from transcriptional responses based on multi-label classification , 2017, Scientific Reports.

[55]  Minoru Kanehisa,et al.  KEGG: new perspectives on genomes, pathways, diseases and drugs , 2016, Nucleic Acids Res..

[56]  Ming Wen,et al.  Deep-Learning-Based Drug-Target Interaction Prediction. , 2017, Journal of proteome research.

[57]  Guy N. Brock,et al.  clValid , an R package for cluster validation , 2008 .

[58]  S. Dudoit,et al.  A prediction-based resampling method for estimating the number of clusters in a dataset , 2002, Genome Biology.

[59]  Peer Bork,et al.  The SIDER database of drugs and side effects , 2015, Nucleic Acids Res..

[60]  K. Borden,et al.  Ribavirin as an anti-cancer therapy: acute myeloid leukemia and beyond? , 2010, Leukemia & lymphoma.

[61]  Itskovitz Hd.  Alpha 1-blockade for the treatment of hypertension: a megastudy of terazosin in 2214 clinical practice settings. , 1994 .

[62]  Joanna L. Sharman,et al.  The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands , 2013, Nucleic Acids Res..

[63]  V. Torri,et al.  Cyproterone acetate in the therapy of prostate carcinoma. , 2005, Archivio italiano di urologia, andrologia : organo ufficiale [di] Societa italiana di ecografia urologica e nefrologica.

[64]  E. Pucci,et al.  Treatment of androgen excess in females: yesterday, today and tomorrow. , 1997, Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology.

[65]  Jian Peng,et al.  A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information , 2017, Nature Communications.

[66]  Xin Huang,et al.  ICM: a web server for integrated clustering of multi-dimensional biomedical data , 2016, Nucleic Acids Res..

[67]  Christoph Steinbeck,et al.  The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013 , 2012, Nucleic Acids Res..

[68]  P. Bork,et al.  Drug Target Identification Using Side-Effect Similarity , 2008, Science.

[69]  Guangchuang Yu,et al.  clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.

[70]  A. Booth,et al.  Pentoxifylline for intermittent claudication. , 2012, The Cochrane database of systematic reviews.

[71]  Ivan G. Costa,et al.  A multiple kernel learning algorithm for drug-target interaction prediction , 2016, BMC Bioinformatics.

[72]  E. Marchiori,et al.  Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile , 2013, PloS one.

[73]  Zhuowen Tu,et al.  Similarity network fusion for aggregating data types on a genomic scale , 2014, Nature Methods.

[74]  Chris Morley,et al.  Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit , 2008, Chemistry Central journal.

[75]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[76]  Anbupalam Thalamuthu,et al.  Gene expression Evaluation and comparison of gene clustering methods in microarray analysis , 2006 .

[77]  Michael J. Keiser,et al.  Relating protein pharmacology by ligand chemistry , 2007, Nature Biotechnology.

[78]  José Luís Oliveira,et al.  Computational Discovery of Putative Leads for Drug Repositioning through Drug-Target Interaction Prediction , 2016, PLoS Comput. Biol..

[79]  SSRIs and QT interval prolongation management. A review , 2017, European Psychiatry.

[80]  Michael J. Keiser,et al.  Predicting new molecular targets for known drugs , 2009, Nature.

[81]  Rong Chen,et al.  Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning , 2017, Briefings Bioinform..