Literature DB >> 21414478

Boosting signal-to-noise in complex biology: prior knowledge is power.

Trey Ideker1, Janusz Dutkowski, Leroy Hood.   

Abstract

A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21414478      PMCID: PMC3102020          DOI: 10.1016/j.cell.2011.03.007

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  20 in total

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Authors:  Kasper Lage; E Olof Karlberg; Zenia M Størling; Páll I Olason; Anders G Pedersen; Olga Rigina; Anders M Hinsby; Zeynep Tümer; Flemming Pociot; Niels Tommerup; Yves Moreau; Søren Brunak
Journal:  Nat Biotechnol       Date:  2007-03       Impact factor: 54.908

2.  A predictive model for transcriptional control of physiology in a free living cell.

Authors:  Richard Bonneau; Marc T Facciotti; David J Reiss; Amy K Schmid; Min Pan; Amardeep Kaur; Vesteinn Thorsson; Paul Shannon; Michael H Johnson; J Christopher Bare; William Longabaugh; Madhavi Vuthoori; Kenia Whitehead; Aviv Madar; Lena Suzuki; Tetsuya Mori; Dong-Eun Chang; Jocelyne Diruggiero; Carl H Johnson; Leroy Hood; Nitin S Baliga
Journal:  Cell       Date:  2007-12-28       Impact factor: 41.582

3.  Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks.

Authors:  Jun Zhu; Bin Zhang; Erin N Smith; Becky Drees; Rachel B Brem; Leonid Kruglyak; Roger E Bumgarner; Eric E Schadt
Journal:  Nat Genet       Date:  2008-06-15       Impact factor: 38.330

Review 4.  Sequencing technologies - the next generation.

Authors:  Michael L Metzker
Journal:  Nat Rev Genet       Date:  2009-12-08       Impact factor: 53.242

5.  A global protein kinase and phosphatase interaction network in yeast.

Authors:  Ashton Breitkreutz; Hyungwon Choi; Jeffrey R Sharom; Lorrie Boucher; Victor Neduva; Brett Larsen; Zhen-Yuan Lin; Bobby-Joe Breitkreutz; Chris Stark; Guomin Liu; Jessica Ahn; Danielle Dewar-Darch; Teresa Reguly; Xiaojing Tang; Ricardo Almeida; Zhaohui Steve Qin; Tony Pawson; Anne-Claude Gingras; Alexey I Nesvizhskii; Mike Tyers
Journal:  Science       Date:  2010-05-21       Impact factor: 47.728

6.  Common SNPs explain a large proportion of the heritability for human height.

Authors:  Jian Yang; Beben Benyamin; Brian P McEvoy; Scott Gordon; Anjali K Henders; Dale R Nyholt; Pamela A Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

7.  Analysis of genetic inheritance in a family quartet by whole-genome sequencing.

Authors:  Jared C Roach; Gustavo Glusman; Arian F A Smit; Chad D Huff; Robert Hubley; Paul T Shannon; Lee Rowen; Krishna P Pant; Nathan Goodman; Michael Bamshad; Jay Shendure; Radoje Drmanac; Lynn B Jorde; Leroy Hood; David J Galas
Journal:  Science       Date:  2010-03-10       Impact factor: 47.728

8.  A probabilistic functional network of yeast genes.

Authors:  Insuk Lee; Shailesh V Date; Alex T Adai; Edward M Marcotte
Journal:  Science       Date:  2004-11-26       Impact factor: 47.728

9.  Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations.

Authors:  Jun Zhu; Matthew C Wiener; Chunsheng Zhang; Arthur Fridman; Eric Minch; Pek Y Lum; Jeffrey R Sachs; Eric E Schadt
Journal:  PLoS Comput Biol       Date:  2007-02-27       Impact factor: 4.475

10.  eQED: an efficient method for interpreting eQTL associations using protein networks.

Authors:  Silpa Suthram; Andreas Beyer; Richard M Karp; Yonina Eldar; Trey Ideker
Journal:  Mol Syst Biol       Date:  2008-03-04       Impact factor: 11.429

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  73 in total

Review 1.  Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine.

Authors:  Q Tian; N D Price; L Hood
Journal:  J Intern Med       Date:  2012-02       Impact factor: 8.989

2.  New technologies for 21st century plant science.

Authors:  David W Ehrhardt; Wolf B Frommer
Journal:  Plant Cell       Date:  2012-02-24       Impact factor: 11.277

Review 3.  Metabolic systems biology: a brief primer.

Authors:  Lindsay M Edwards
Journal:  J Physiol       Date:  2017-02-21       Impact factor: 5.182

4.  Toxicogenomic module associations with pathogenesis: a network-based approach to understanding drug toxicity.

Authors:  J J Sutherland; Y W Webster; J A Willy; G H Searfoss; K M Goldstein; A R Irizarry; D G Hall; J L Stevens
Journal:  Pharmacogenomics J       Date:  2017-04-25       Impact factor: 3.550

Review 5.  Promise of personalized omics to precision medicine.

Authors:  Rui Chen; Michael Snyder
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2012-11-26

Review 6.  Systems biology: personalized medicine for the future?

Authors:  Rui Chen; Michael Snyder
Journal:  Curr Opin Pharmacol       Date:  2012-07-31       Impact factor: 5.547

7.  Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion.

Authors:  Aliccia Bollig-Fischer; Luca Marchetti; Cristina Mitrea; Jiusheng Wu; Adéle Kruger; Vincenzo Manca; Sorin Drăghici
Journal:  Bioinformatics       Date:  2014-07-15       Impact factor: 6.937

8.  Network-based pathway enrichment analysis with incomplete network information.

Authors:  Jing Ma; Ali Shojaie; George Michailidis
Journal:  Bioinformatics       Date:  2016-06-29       Impact factor: 6.937

Review 9.  Network analysis of GWAS data.

Authors:  Mark D M Leiserson; Jonathan V Eldridge; Sohini Ramachandran; Benjamin J Raphael
Journal:  Curr Opin Genet Dev       Date:  2013-11-26       Impact factor: 5.578

10.  Genome-wide association study using cellular traits identifies a new regulator of root development in Arabidopsis.

Authors:  Mónica Meijón; Santosh B Satbhai; Takashi Tsuchimatsu; Wolfgang Busch
Journal:  Nat Genet       Date:  2013-11-10       Impact factor: 38.330

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