Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 156

1.

Transcriptome and proteome quantification of a tumor model provides novel insights into post-transcriptional gene regulation.

Jüschke C, Dohnal I, Pichler P, Harzer H, Swart R, Ammerer G, Mechtler K, Knoblich JA.

Genome Biol. 2013 Nov 30;14(11):r133. doi: 10.1186/gb-2013-14-11-r133.

2.

Transcriptional signature of an adult brain tumor in Drosophila.

Loop T, Leemans R, Stiefel U, Hermida L, Egger B, Xie F, Primig M, Certa U, Fischbach KF, Reichert H, Hirth F.

BMC Genomics. 2004 Apr 16;5(1):24.

3.

Integrative proteomic and transcriptomic analyses reveal multiple post-transcriptional regulatory mechanisms of mouse spermatogenesis.

Gan H, Cai T, Lin X, Wu Y, Wang X, Yang F, Han C.

Mol Cell Proteomics. 2013 May;12(5):1144-57. doi: 10.1074/mcp.M112.020123. Epub 2013 Jan 16.

4.

Complementary iTRAQ proteomics and RNA-seq transcriptomics reveal multiple levels of regulation in response to nitrogen starvation in Synechocystis sp. PCC 6803.

Huang S, Chen L, Te R, Qiao J, Wang J, Zhang W.

Mol Biosyst. 2013 Oct;9(10):2565-74. doi: 10.1039/c3mb70188c.

PMID:
23942477
5.

Genome stability versus transcript diversity.

Magnuson B, Bedi K, Ljungman M.

DNA Repair (Amst). 2016 Aug;44:81-86. doi: 10.1016/j.dnarep.2016.05.010. Epub 2016 May 16. Review.

6.

Towards decrypting cryptobiosis--analyzing anhydrobiosis in the tardigrade Milnesium tardigradum using transcriptome sequencing.

Wang C, Grohme MA, Mali B, Schill RO, Frohme M.

PLoS One. 2014 Mar 20;9(3):e92663. doi: 10.1371/journal.pone.0092663. eCollection 2014.

7.

Integrative analyses reveal transcriptome-proteome correlation in biological pathways and secondary metabolism clusters in A. flavus in response to temperature.

Bai Y, Wang S, Zhong H, Yang Q, Zhang F, Zhuang Z, Yuan J, Nie X, Wang S.

Sci Rep. 2015 Sep 29;5:14582. doi: 10.1038/srep14582.

8.

Integrated proteomics identified novel activation of dynein IC2-GR-COX-1 signaling in neurofibromatosis type I (NF1) disease model cells.

Hirayama M, Kobayashi D, Mizuguchi S, Morikawa T, Nagayama M, Midorikawa U, Wilson MM, Nambu AN, Yoshizawa AC, Kawano S, Araki N.

Mol Cell Proteomics. 2013 May;12(5):1377-94. doi: 10.1074/mcp.M112.024802. Epub 2013 Jan 28.

9.

In the Driver's Seat: The Case for Transcriptional Regulation and Coupling as Relevant Determinants of the Circadian Transcriptome and Proteome in Eukaryotes.

Montenegro-Montero A, Larrondo LF.

J Biol Rhythms. 2016 Feb;31(1):37-47. doi: 10.1177/0748730415607321. Epub 2015 Oct 7.

PMID:
26446874
10.

Variation and genetic control of protein abundance in humans.

Wu L, Candille SI, Choi Y, Xie D, Jiang L, Li-Pook-Than J, Tang H, Snyder M.

Nature. 2013 Jul 4;499(7456):79-82. doi: 10.1038/nature12223. Epub 2013 May 15.

11.

iTRAQ-based quantitative proteome and phosphoprotein characterization reveals the central metabolism changes involved in wheat grain development.

Ma C, Zhou J, Chen G, Bian Y, Lv D, Li X, Wang Z, Yan Y.

BMC Genomics. 2014 Nov 27;15:1029. doi: 10.1186/1471-2164-15-1029.

12.

Regulation of transcriptome, translation, and proteome in response to environmental stress in fission yeast.

Lackner DH, Schmidt MW, Wu S, Wolf DA, Bähler J.

Genome Biol. 2012 Apr 18;13(4):R25. doi: 10.1186/gb-2012-13-4-r25.

13.

Strand-specific RNA-Seq reveals widespread and developmentally regulated transcription of natural antisense transcripts in Plasmodium falciparum.

Siegel TN, Hon CC, Zhang Q, Lopez-Rubio JJ, Scheidig-Benatar C, Martins RM, Sismeiro O, Coppée JY, Scherf A.

BMC Genomics. 2014 Feb 22;15:150. doi: 10.1186/1471-2164-15-150.

14.
15.

A novel method to prioritize RNAseq data for post-hoc analysis based on absolute changes in transcript abundance.

McNutt P, Gut I, Hubbard K, Beske P.

Stat Appl Genet Mol Biol. 2015 Jun;14(3):227-41. doi: 10.1515/sagmb-2014-0018.

PMID:
25781714
16.

Comparative transcriptome analysis of epithelial and fiber cells in newborn mouse lenses with RNA sequencing.

Hoang TV, Kumar PK, Sutharzan S, Tsonis PA, Liang C, Robinson ML.

Mol Vis. 2014 Nov 4;20:1491-517. eCollection 2014.

17.

MicroRNA transcriptome profiling of mice brains infected with Japanese encephalitis virus by RNA sequencing.

Li XF, Cao RB, Luo J, Fan JM, Wang JM, Zhang YP, Gu JY, Feng XL, Zhou B, Chen PY.

Infect Genet Evol. 2016 Apr;39:249-57. doi: 10.1016/j.meegid.2016.01.028. Epub 2016 Feb 2.

PMID:
26845346
18.

Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes.

Gunawardana Y, Niranjan M.

Bioinformatics. 2013 Dec 1;29(23):3060-6. doi: 10.1093/bioinformatics/btt537. Epub 2013 Sep 16.

PMID:
24045772
19.

Comparative Transcriptome and iTRAQ Proteome Analyses of Citrus Root Responses to Candidatus Liberibacter asiaticus Infection.

Zhong Y, Cheng CZ, Jiang NH, Jiang B, Zhang YY, Wu B, Hu ML, Zeng JW, Yan HX, Yi GJ, Zhong GY.

PLoS One. 2015 Jun 5;10(6):e0126973. doi: 10.1371/journal.pone.0126973. eCollection 2015.

20.

Analysis of the transcriptomes downstream of Eyeless and the Hedgehog, Decapentaplegic and Notch signaling pathways in Drosophila melanogaster.

Nfonsam LE, Cano C, Mudge J, Schilkey FD, Curtiss J.

PLoS One. 2012;7(8):e44583. doi: 10.1371/journal.pone.0044583. Epub 2012 Aug 31.

Supplemental Content

Support Center