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Items: 1 to 20 of 94

1.

Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification.

Kouskoumvekaki I, Yang Z, Jónsdóttir SO, Olsson L, Panagiotou G.

BMC Bioinformatics. 2008 Jan 28;9:59. doi: 10.1186/1471-2105-9-59.

2.

Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans.

David H, Hofmann G, Oliveira AP, Jarmer H, Nielsen J.

Genome Biol. 2006;7(11):R108.

3.

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.

Zhang X, Lu X, Shi Q, Xu XQ, Leung HC, Harris LN, Iglehart JD, Miron A, Liu JS, Wong WH.

BMC Bioinformatics. 2006 Apr 10;7:197.

5.

The old 3-oxoadipate pathway revisited: new insights in the catabolism of aromatics in the saprophytic fungus Aspergillus nidulans.

Martins TM, Hartmann DO, Planchon S, Martins I, Renaut J, Silva Pereira C.

Fungal Genet Biol. 2015 Jan;74:32-44. doi: 10.1016/j.fgb.2014.11.002. Epub 2014 Dec 3.

PMID:
25479309
6.

MarVis: a tool for clustering and visualization of metabolic biomarkers.

Kaever A, Lingner T, Feussner K, Göbel C, Feussner I, Meinicke P.

BMC Bioinformatics. 2009 Mar 20;10:92. doi: 10.1186/1471-2105-10-92.

7.

Uncovering transcriptional regulation of glycerol metabolism in Aspergilli through genome-wide gene expression data analysis.

Salazar M, Vongsangnak W, Panagiotou G, Andersen MR, Nielsen J.

Mol Genet Genomics. 2009 Dec;282(6):571-86. doi: 10.1007/s00438-009-0486-y. Epub 2009 Sep 26.

PMID:
19784673
8.

Analysis of Aspergillus nidulans metabolism at the genome-scale.

David H, Ozçelik IS, Hofmann G, Nielsen J.

BMC Genomics. 2008 Apr 11;9:163. doi: 10.1186/1471-2164-9-163.

9.

Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data.

Boutros PC, Okey AB.

Brief Bioinform. 2005 Dec;6(4):331-43. Review.

PMID:
16420732
10.
11.

Intimate bacterial-fungal interaction triggers biosynthesis of archetypal polyketides in Aspergillus nidulans.

Schroeckh V, Scherlach K, Nützmann HW, Shelest E, Schmidt-Heck W, Schuemann J, Martin K, Hertweck C, Brakhage AA.

Proc Natl Acad Sci U S A. 2009 Aug 25;106(34):14558-63. doi: 10.1073/pnas.0901870106. Epub 2009 Aug 6.

12.

Identification and characterization of a novel diterpene gene cluster in Aspergillus nidulans.

Bromann K, Toivari M, Viljanen K, Vuoristo A, Ruohonen L, Nakari-Setälä T.

PLoS One. 2012;7(4):e35450. doi: 10.1371/journal.pone.0035450. Epub 2012 Apr 10.

13.

Reliable classification of two-class cancer data using evolutionary algorithms.

Deb K, Raji Reddy A.

Biosystems. 2003 Nov;72(1-2):111-29.

PMID:
14642662
14.

Studies of the production of fungal polyketides in Aspergillus nidulans by using systems biology tools.

Panagiotou G, Andersen MR, Grotkjaer T, Regueira TB, Nielsen J, Olsson L.

Appl Environ Microbiol. 2009 Apr;75(7):2212-20. doi: 10.1128/AEM.01461-08. Epub 2009 Jan 23.

15.

Clustering of gene expression data: performance and similarity analysis.

Yin L, Huang CH, Ni J.

BMC Bioinformatics. 2006 Dec 12;7 Suppl 4:S19.

16.

Qualitative ubiquitome unveils the potential significances of protein lysine ubiquitination in hyphal growth of Aspergillus nidulans.

Chu XL, Feng MG, Ying SH.

Curr Genet. 2016 Feb;62(1):191-201. doi: 10.1007/s00294-015-0517-7. Epub 2015 Sep 2.

PMID:
26328806
17.

Differential expression of silent polyketide biosynthesis gene clusters in chemostat cultures of Aspergillus nidulans.

Sarkar A, Funk AN, Scherlach K, Horn F, Schroeckh V, Chankhamjon P, Westermann M, Roth M, Brakhage AA, Hertweck C, Horn U.

J Biotechnol. 2012 Jul 31;160(1-2):64-71. doi: 10.1016/j.jbiotec.2012.01.015. Epub 2012 Jan 26.

PMID:
22306112
18.

Engineering of an "unnatural" natural product by swapping polyketide synthase domains in Aspergillus nidulans.

Liu T, Chiang YM, Somoza AD, Oakley BR, Wang CC.

J Am Chem Soc. 2011 Aug 31;133(34):13314-6. doi: 10.1021/ja205780g. Epub 2011 Aug 10.

19.

Time-resolved metabolomics reveals metabolic modulation in rice foliage.

Sato S, Arita M, Soga T, Nishioka T, Tomita M.

BMC Syst Biol. 2008 Jun 18;2:51. doi: 10.1186/1752-0509-2-51.

20.

A novel approach for clustering proteomics data using Bayesian fast Fourier transform.

Bensmail H, Golek J, Moody MM, Semmes JO, Haoudi A.

Bioinformatics. 2005 May 15;21(10):2210-24. Epub 2005 Mar 15.

PMID:
15769836

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