Log on / register
Feedback
|
Support
|
My details
home
|
journals A-Z
|
subject areas
|
advanced search
|
authors
|
reviewers
|
libraries
|
about
|
my BioMed Central
Gene selection and classification of microarray data using random forest.
Díaz-Uriarte R, Alvarez de Andrés S
BMC Bioinformatics
2006,
7
:3
[
Full text
]
[
PubMed
]
[
Related articles
]
[
Cited on BioMed Central
]
printer friendly
20 per page
50 per page
200 per page
500 per page
selected items
abstract
no abstract
any time period
7 Days
14 Days
30 Days
60 Days
90 Days
180 Days
1 Year
all 17 results
this page
selected items
to
Endnote (no abstracts)
Endnote + abstracts
Ref. Manager (no abstracts)
Ref. Manager + abstracts
RefWorks (no abstracts)
RefWorks + abstracts
BibTeX (no abstracts)
BibTeX + abstracts
ProCite (no abstracts)
ProCite + abstracts
[
Help
]
PubMed Central articles that cite the above article:
1.
Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals.
Enot DP, Beckmann M, Overy D, Draper J
Proc Natl Acad Sci U S A
2006 Oct 3,
103
:14865-70
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
2.
RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition features.
Jiang P, Wu H, Wei J, Sang F, Sun X, Lu Z
Nucleic Acids Res
2007 Jul,
35
:W47-51
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
3.
Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders.
Mutch DM, Temanni MR, Henegar C, Combes F, Pelloux V, Holst C, Sørensen TI, Astrup A, Martinez JA, Saris WH, Viguerie N, Langin D, Zucker JD, Clément K
PLoS One
2007,
2
:e1344
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
4.
Classification algorithms for phenotype prediction in genomics and proteomics.
Ressom HW, Varghese RS, Zhang Z, Xuan J, Clarke R
Front Biosci
2008,
13
:691-708
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
5.
Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data.
Hassane DC, Guzman ML, Corbett C, Li X, Abboud R, Young F, Liesveld JL, Carroll M, Jordan CT
Blood
2008 Jun 15,
111
:5654-62
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
6.
Comparing the characteristics of gene expression profiles derived by univariate and multivariate classification methods.
Zucknick M, Richardson S, Stronach EA
Stat Appl Genet Mol Biol
2008,
7
:Article7
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
7.
Accurate and robust gene selection for disease classification using a simple statistic.
Mutsubayashi H, Aso S, Nagashima T, Okada Y
Bioinformation
2008,
3
:68-71
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
8.
Knowledge-based gene expression classification via matrix factorization.
Schachtner R, Lutter D, Knollmüller P, Tomé AM, Theis FJ, Schmitz G, Stetter M, Vilda PG, Lang EW
Bioinformatics
2008 Aug 1,
24
:1688-97
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
9.
Are random forests better than support vector machines for microarray-based cancer classification?
Statnikov A, Aliferis CF
AMIA Annu Symp Proc
2007,
:686-90
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
10.
A hybrid approach for biomarker discovery from microarray gene expression data for cancer classification.
Peng Y, Li W, Liu Y
Cancer Inform
2007,
2
:301-11
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
11.
Asterias: A Parallelized Web-based Suite for the Analysis of Expression and aCGH Data.
Alibés A, Morrissey ER, Cañada A, Rueda OM, Casado D, Yankilevich P, Díaz-Uriarte R
Cancer Inform
2007,
3
:1-9
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
12.
CSF multianalyte profile distinguishes Alzheimer and Parkinson diseases.
Zhang J, Sokal I, Peskind ER, Quinn JF, Jankovic J, Kenney C, Chung KA, Millard SP, Nutt JG, Montine TJ
Am J Clin Pathol
2008 Apr,
129
:526-9
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
13.
Identification of yeast transcriptional regulation networks using multivariate random forests.
Xiao Y, Segal MR
PLoS Comput Biol
2009 Jun,
5
:e1000414
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
14.
How long will my mouse live? Machine learning approaches for prediction of mouse life span.
Swindell WR, Harper JM, Miller RA
J Gerontol A Biol Sci Med Sci
2008 Sep,
63
:895-906
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
15.
Genome-wide mRNA expression analysis of hepatic adaptation to high-fat diets reveals switch from an inflammatory to steatotic transcriptional program.
Radonjic M, de Haan JR, van Erk MJ, van Dijk KW, van den Berg SA, de Groot PJ, Müller M, van Ommen B
PLoS One
2009,
4
:e6646
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
16.
Prediction of high-responding peptides for targeted protein assays by mass spectrometry.
Fusaro VA, Mani DR, Mesirov JP, Carr SA
Nat Biotechnol
2009 Feb,
27
:190-8
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
17.
Patient-centered yes/no prognosis using learning machines.
König IR, Malley JD, Pajevic S, Weimar C, Diener HC, Ziegler A
Int J Data Min Bioinform
2008,
2
:289-341
[
PubMed Central
]
[
PubMed
]
[
Related articles
]
This article is also cited by
22 articles
in BioMed Central
You can also
check ISI Web of Science
for additional citations (subscription required)
printer friendly
20 per page
50 per page
200 per page
500 per page
selected items
abstract
no abstract
any time period
7 Days
14 Days
30 Days
60 Days
90 Days
180 Days
1 Year
all 17 results
this page
selected items
to
Endnote (no abstracts)
Endnote + abstracts
Ref. Manager (no abstracts)
Ref. Manager + abstracts
RefWorks (no abstracts)
RefWorks + abstracts
BibTeX (no abstracts)
BibTeX + abstracts
ProCite (no abstracts)
ProCite + abstracts
[
Help
]
Terms and Conditions
Privacy statement
Information for advertisers
Jobs at BMC
Contact us
© 1999-2009 BioMed Central Ltd unless otherwise stated. Part of
Springer Science+Business Media
.