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Items: 14

1.

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways.

Äijö T, Huang Y, Mannerström H, Chavez L, Tsagaratou A, Rao A, Lähdesmäki H.

Genome Biol. 2016 Mar 14;17(1):49. doi: 10.1186/s13059-016-0911-6.

2.

Comparative analysis of human and mouse transcriptomes of Th17 cell priming.

Tuomela S, Rautio S, Ahlfors H, Öling V, Salo V, Ullah U, Chen Z, Hämälistö S, Tripathi SK, Äijö T, Rasool O, Soueidan H, Wessels L, Stockinger B, Lähdesmäki H, Lahesmaa R.

Oncotarget. 2016 Mar 7. doi: 10.18632/oncotarget.7963. [Epub ahead of print]

3.

Control of Foxp3 stability through modulation of TET activity.

Yue X, Trifari S, Äijö T, Tsagaratou A, Pastor WA, Zepeda-Martínez JA, Lio CW, Li X, Huang Y, Vijayanand P, Lähdesmäki H, Rao A.

J Exp Med. 2016 Mar 7;213(3):377-97. doi: 10.1084/jem.20151438. Epub 2016 Feb 22.

PMID:
26903244
4.

The transcription factor NFAT promotes exhaustion of activated CD8⁺ T cells.

Martinez GJ, Pereira RM, Äijö T, Kim EY, Marangoni F, Pipkin ME, Togher S, Heissmeyer V, Zhang YC, Crotty S, Lamperti ED, Ansel KM, Mempel TR, Lähdesmäki H, Hogan PG, Rao A.

Immunity. 2015 Feb 17;42(2):265-78. doi: 10.1016/j.immuni.2015.01.006. Epub 2015 Feb 10.

5.

Dissecting the dynamic changes of 5-hydroxymethylcytosine in T-cell development and differentiation.

Tsagaratou A, Äijö T, Lio CW, Yue X, Huang Y, Jacobsen SE, Lähdesmäki H, Rao A.

Proc Natl Acad Sci U S A. 2014 Aug 12;111(32):E3306-15. doi: 10.1073/pnas.1412327111. Epub 2014 Jul 28.

6.

Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation.

Äijö T, Butty V, Chen Z, Salo V, Tripathi S, Burge CB, Lahesmaa R, Lähdesmäki H.

Bioinformatics. 2014 Jun 15;30(12):i113-20. doi: 10.1093/bioinformatics/btu274.

7.

MicroRNA-directed program of cytotoxic CD8+ T-cell differentiation.

Trifari S, Pipkin ME, Bandukwala HS, Äijö T, Bassein J, Chen R, Martinez GJ, Rao A.

Proc Natl Acad Sci U S A. 2013 Nov 12;110(46):18608-13. doi: 10.1073/pnas.1317191110. Epub 2013 Oct 25. Erratum in: Proc Natl Acad Sci U S A. 2014 Feb 4;111(5):2047.

8.

Modulation of TET2 expression and 5-methylcytosine oxidation by the CXXC domain protein IDAX.

Ko M, An J, Bandukwala HS, Chavez L, Aijö T, Pastor WA, Segal MF, Li H, Koh KP, Lähdesmäki H, Hogan PG, Aravind L, Rao A.

Nature. 2013 May 2;497(7447):122-6. doi: 10.1038/nature12052. Epub 2013 Apr 7.

9.

Sorad: a systems biology approach to predict and modulate dynamic signaling pathway response from phosphoproteome time-course measurements.

Äijö T, Granberg K, Lähdesmäki H.

Bioinformatics. 2013 May 15;29(10):1283-91. doi: 10.1093/bioinformatics/btt130. Epub 2013 Mar 16.

10.

An integrative computational systems biology approach identifies differentially regulated dynamic transcriptome signatures which drive the initiation of human T helper cell differentiation.

Aijö T, Edelman SM, Lönnberg T, Larjo A, Kallionpää H, Tuomela S, Engström E, Lahesmaa R, Lähdesmäki H.

BMC Genomics. 2012 Oct 30;13:572. doi: 10.1186/1471-2164-13-572.

11.

Heterogeneous nuclear ribonucleoprotein L-like (hnRNPLL) and elongation factor, RNA polymerase II, 2 (ELL2) are regulators of mRNA processing in plasma cells.

Benson MJ, Aijö T, Chang X, Gagnon J, Pape UJ, Anantharaman V, Aravind L, Pursiheimo JP, Oberdoerffer S, Liu XS, Lahesmaa R, Lähdesmäki H, Rao A.

Proc Natl Acad Sci U S A. 2012 Oct 2;109(40):16252-7. doi: 10.1073/pnas.1214414109. Epub 2012 Sep 18.

12.

Identification of early gene expression changes during human Th17 cell differentiation.

Tuomela S, Salo V, Tripathi SK, Chen Z, Laurila K, Gupta B, Äijö T, Oikari L, Stockinger B, Lähdesmäki H, Lahesmaa R.

Blood. 2012 Jun 7;119(23):e151-60. doi: 10.1182/blood-2012-01-407528. Epub 2012 Apr 27.

13.

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images.

Ruusuvuori P, Aijö T, Chowdhury S, Garmendia-Torres C, Selinummi J, Birbaumer M, Dudley AM, Pelkmans L, Yli-Harja O.

BMC Bioinformatics. 2010 May 13;11:248. doi: 10.1186/1471-2105-11-248.

14.

Learning gene regulatory networks from gene expression measurements using non-parametric molecular kinetics.

Aijö T, Lähdesmäki H.

Bioinformatics. 2009 Nov 15;25(22):2937-44. doi: 10.1093/bioinformatics/btp511. Epub 2009 Aug 25.

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