Literature DB >> 17683991

Towards knowledge-based gene expression data mining.

Riccardo Bellazzi1, Blaz Zupan.   

Abstract

The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at complementing microarray analysis with data and knowledge from diverse available sources. In this review, we report on the plethora of gene expression data mining techniques and focus on their evolution toward knowledge-based data analysis approaches. In particular, we discuss recent developments in gene expression-based analysis methods used in association and classification studies, phenotyping and reverse engineering of gene networks.

Mesh:

Substances:

Year:  2007        PMID: 17683991     DOI: 10.1016/j.jbi.2007.06.005

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  14 in total

1.  Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).

Authors:  Ronald C Kessler; Christopher H Warner; Christopher Ivany; Maria V Petukhova; Sherri Rose; Evelyn J Bromet; Millard Brown; Tianxi Cai; Lisa J Colpe; Kenneth L Cox; Carol S Fullerton; Stephen E Gilman; Michael J Gruber; Steven G Heeringa; Lisa Lewandowski-Romps; Junlong Li; Amy M Millikan-Bell; James A Naifeh; Matthew K Nock; Anthony J Rosellini; Nancy A Sampson; Michael Schoenbaum; Murray B Stein; Simon Wessely; Alan M Zaslavsky; Robert J Ursano
Journal:  JAMA Psychiatry       Date:  2015-01       Impact factor: 21.596

2.  Data analysis and data mining: current issues in biomedical informatics.

Authors:  R Bellazzi; M Diomidous; I N Sarkar; K Takabayashi; A Ziegler; A T McCray
Journal:  Methods Inf Med       Date:  2011       Impact factor: 2.176

3.  Computing gene expression data with a knowledge-based gene clustering approach.

Authors:  Bruce A Rosa; Sookyung Oh; Beronda L Montgomery; Jin Chen; Wensheng Qin
Journal:  Int J Biochem Mol Biol       Date:  2010-06-15

4.  Data mining technologies for blood glucose and diabetes management.

Authors:  Riccardo Bellazzi; Ameen Abu-Hanna
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

5.  Seeing the forest for the trees: using the Gene Ontology to restructure hierarchical clustering.

Authors:  Dikla Dotan-Cohen; Simon Kasif; Avraham A Melkman
Journal:  Bioinformatics       Date:  2009-06-03       Impact factor: 6.937

6.  Improving the efficiency of biomarker identification using biological knowledge.

Authors:  John H Phan; Qiqin Yin-Goen; Andrew N Young; May D Wang
Journal:  Pac Symp Biocomput       Date:  2009

7.  An unsupervised machine learning method for discovering patient clusters based on genetic signatures.

Authors:  Christian Lopez; Scott Tucker; Tarik Salameh; Conrad Tucker
Journal:  J Biomed Inform       Date:  2018-07-29       Impact factor: 6.317

8.  Exploring the transcription factor activity in high-throughput gene expression data using RLQ analysis.

Authors:  Florent Baty; Jochen Rüdiger; Nicola Miglino; Lukas Kern; Peter Borger; Martin Brutsche
Journal:  BMC Bioinformatics       Date:  2013-06-06       Impact factor: 3.169

9.  Biomedical discovery acceleration, with applications to craniofacial development.

Authors:  Sonia M Leach; Hannah Tipney; Weiguo Feng; William A Baumgartner; Priyanka Kasliwal; Ronald P Schuyler; Trevor Williams; Richard A Spritz; Lawrence Hunter
Journal:  PLoS Comput Biol       Date:  2009-03-27       Impact factor: 4.475

10.  geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

Authors:  Daniel Glez-Peña; Fernando Díaz; Jesús M Hernández; Juan M Corchado; Florentino Fdez-Riverola
Journal:  BMC Bioinformatics       Date:  2009-06-18       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.