Literature DB >> 21919609

Systems biology data analysis methodology in pharmacogenomics.

Andrei S Rodin1, Grigoriy Gogoshin, Eric Boerwinkle.   

Abstract

Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.

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Mesh:

Year:  2011        PMID: 21919609      PMCID: PMC3482399          DOI: 10.2217/pgs.11.76

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  68 in total

1.  Estimating genome-wide gene networks using nonparametric Bayesian network models on massively parallel computers.

Authors:  Yoshinori Tamada; Seiya Imoto; Hiromitsu Araki; Masao Nagasaki; Cristin Print; D Stephen Charnock-Jones; Satoru Miyano
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2011 May-Jun       Impact factor: 3.710

2.  Functional mapping of drug response with pharmacodynamic-pharmacokinetic principles.

Authors:  Kwangmi Ahn; Jiangtao Luo; Arthur Berg; David Keefe; Rongling Wu
Journal:  Trends Pharmacol Sci       Date:  2010-05-18       Impact factor: 14.819

3.  Identifying drug active pathways from gene networks estimated by gene expression data.

Authors:  Yoshinori Tamada; Seiya Imoto; Kousuke Tashiro; Satoru Kuhara; Satoru Miyano
Journal:  Genome Inform       Date:  2005

4.  Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles.

Authors:  Seiya Imoto; Yoshinori Tamada; Hiromitsu Araki; Kaori Yasuda; Cristin G Print; Stephen D Charnock-Jones; Deborah Sanders; Christopher J Savoie; Kousuke Tashiro; Satoru Kuhara; Satoru Miyano
Journal:  Pac Symp Biocomput       Date:  2006

5.  Unraveling dynamic activities of autocrine pathways that control drug-response transcriptome networks.

Authors:  Yoshinori Tamada; Hiromitsu Araki; Seiya Imoto; Masao Nagasaki; Atsushi Doi; Yukiko Nakanishi; Yuki Tomiyasu; Kaori Yasuda; Ben Dunmore; Deborah Sanders; Sally Humphreys; Cristin Print; D Stephen Charnock-Jones; Kousuke Tashiro; Satoru Kuhara; Satoru Miyano
Journal:  Pac Symp Biocomput       Date:  2009

6.  Metabolic networks are NP-hard to reconstruct.

Authors:  Zoran Nikoloski; Sergio Grimbs; Patrick May; Joachim Selbig
Journal:  J Theor Biol       Date:  2008-07-22       Impact factor: 2.691

Review 7.  Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.

Authors:  Marylyn D Ritchie
Journal:  Ann Hum Genet       Date:  2011-01       Impact factor: 1.670

Review 8.  Future of personalized medicine in oncology: a systems biology approach.

Authors:  Ana Maria Gonzalez-Angulo; Bryan T J Hennessy; Gordon B Mills
Journal:  J Clin Oncol       Date:  2010-04-20       Impact factor: 44.544

Review 9.  Genome-wide association studies in pharmacogenomics: successes and lessons.

Authors:  Alison A Motsinger-Reif; Eric Jorgenson; Mary V Relling; Deanna L Kroetz; Richard Weinshilboum; Nancy J Cox; Dan M Roden
Journal:  Pharmacogenet Genomics       Date:  2013-08       Impact factor: 2.089

10.  Predicting response to short-acting bronchodilator medication using Bayesian networks.

Authors:  Blanca E Himes; Ann Chen Wu; Qing Ling Duan; Barbara Klanderman; Augusto A Litonjua; Kelan Tantisira; Marco F Ramoni; Scott T Weiss
Journal:  Pharmacogenomics       Date:  2009-09       Impact factor: 2.533

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  8 in total

Review 1.  Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities.

Authors:  Shareefa Dalvie; Nastassja Koen; Nathaniel McGregor; Kevin O'Connell; Louise Warnich; Raj Ramesar; Caroline M Nievergelt; Dan J Stein
Journal:  OMICS       Date:  2016-09-16

Review 2.  Integrative systems biology approaches in asthma pharmacogenomics.

Authors:  Amber Dahlin; Kelan G Tantisira
Journal:  Pharmacogenomics       Date:  2012-09       Impact factor: 2.533

Review 3.  Using systems approaches to address challenges for clinical implementation of pharmacogenomics.

Authors:  Jason H Karnes; Sara Van Driest; Erica A Bowton; Peter E Weeke; Jonathan D Mosley; Josh F Peterson; Joshua C Denny; Dan M Roden
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-12-06

4.  Pharmacogenomic characterization of gemcitabine response--a framework for data integration to enable personalized medicine.

Authors:  Michael Harris; Krithika Bhuvaneshwar; Thanemozhi Natarajan; Laura Sheahan; Difei Wang; Mahlet G Tadesse; Ira Shoulson; Ross Filice; Kenneth Steadman; Michael J Pishvaian; Subha Madhavan; John Deeken
Journal:  Pharmacogenet Genomics       Date:  2014-02       Impact factor: 2.089

5.  Genome-wide multi-omics profiling of colorectal cancer identifies immune determinants strongly associated with relapse.

Authors:  Subha Madhavan; Yuriy Gusev; Thanemozhi G Natarajan; Lei Song; Krithika Bhuvaneshwar; Robinder Gauba; Abhishek Pandey; Bassem R Haddad; David Goerlitz; Amrita K Cheema; Hartmut Juhl; Bhaskar Kallakury; John L Marshall; Stephen W Byers; Louis M Weiner
Journal:  Front Genet       Date:  2013-11-20       Impact factor: 4.599

6.  Analysis of high-resolution 3D intrachromosomal interactions aided by Bayesian network modeling.

Authors:  Xizhe Zhang; Sergio Branciamore; Grigoriy Gogoshin; Andrei S Rodin; Arthur D Riggs
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-13       Impact factor: 11.205

7.  A pharmacogenetic risk score for the evaluation of major depression severity under treatment with antidepressants.

Authors:  Sofia H Kanders; Claudia Pisanu; Marcus Bandstein; Jörgen Jonsson; Enrique Castelao; Giorgio Pistis; Mehdi Gholam-Rezaee; Chin B Eap; Martin Preisig; Helgi B Schiöth; Jessica Mwinyi
Journal:  Drug Dev Res       Date:  2019-10-16       Impact factor: 4.360

Review 8.  The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era.

Authors:  Marylyn D Ritchie
Journal:  Hum Genet       Date:  2012-08-25       Impact factor: 4.132

  8 in total

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