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Items: 20

1.

Modeling gene-regulatory networks to describe cell fate transitions and predict master regulators.

Cholley PE, Moehlin J, Rohmer A, Zilliox V, Nicaise S, Gronemeyer H, Mendoza-Parra MA.

NPJ Syst Biol Appl. 2018 Aug 2;4:29. doi: 10.1038/s41540-018-0066-z. eCollection 2018.

2.

Development of biotin-retinoid conjugates as chemical probes for analysis of retinoid function.

Fujii S, Mori S, Kagechika H, Mendoza Parra MA, Gronemeyer H.

Bioorg Med Chem Lett. 2018 Aug 1;28(14):2442-2445. doi: 10.1016/j.bmcl.2018.06.011. Epub 2018 Jun 6.

PMID:
29908657
3.

Senescence-associated reprogramming promotes cancer stemness.

Milanovic M, Fan DNY, Belenki D, Däbritz JHM, Zhao Z, Yu Y, Dörr JR, Dimitrova L, Lenze D, Monteiro Barbosa IA, Mendoza-Parra MA, Kanashova T, Metzner M, Pardon K, Reimann M, Trumpp A, Dörken B, Zuber J, Gronemeyer H, Hummel M, Dittmar G, Lee S, Schmitt CA.

Nature. 2018 Jan 4;553(7686):96-100. doi: 10.1038/nature25167. Epub 2017 Dec 20.

PMID:
29258294
4.

Epimetheus - a multi-profile normalizer for epigenomic sequencing data.

Saleem MM, Mendoza-Parra MA, Cholley PE, Blum M, Gronemeyer H.

BMC Bioinformatics. 2017 May 12;18(1):259. doi: 10.1186/s12859-017-1655-3.

5.

Reconstructed cell fate-regulatory programs in stem cells reveal hierarchies and key factors of neurogenesis.

Mendoza-Parra MA, Malysheva V, Mohamed Saleem MA, Lieb M, Godel A, Gronemeyer H.

Genome Res. 2016 Nov;26(11):1505-1519. Epub 2016 Sep 20.

6.

Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

Mendoza-Parra MA, Saravaki V, Cholley PE, Blum M, Billoré B, Gronemeyer H.

Version 2. F1000Res. 2016 Jan 12 [revised 2016 Jan 1];5:54. doi: 10.12688/f1000research.7637.2. eCollection 2016.

7.

Reconstruction of gene regulatory networks reveals chromatin remodelers and key transcription factors in tumorigenesis.

Malysheva V, Mendoza-Parra MA, Saleem MA, Gronemeyer H.

Genome Med. 2016 May 19;8(1):57. doi: 10.1186/s13073-016-0310-3.

8.

LOGIQA: a database dedicated to long-range genome interactions quality assessment.

Mendoza-Parra MA, Blum M, Malysheva V, Cholley PE, Gronemeyer H.

BMC Genomics. 2016 May 16;17:355. doi: 10.1186/s12864-016-2642-1.

9.

NGS-QC Generator: A Quality Control System for ChIP-Seq and Related Deep Sequencing-Generated Datasets.

Mendoza-Parra MA, Saleem MA, Blum M, Cholley PE, Gronemeyer H.

Methods Mol Biol. 2016;1418:243-65. doi: 10.1007/978-1-4939-3578-9_13.

PMID:
27008019
10.

Assessing quality standards for ChIP-seq and related massive parallel sequencing-generated datasets: When rating goes beyond avoiding the crisis.

Mendoza-Parra MA, Gronemeyer H.

Genom Data. 2014 Aug 14;2:268-73. doi: 10.1016/j.gdata.2014.08.002. eCollection 2014 Dec.

11.

The inactive X chromosome is epigenetically unstable and transcriptionally labile in breast cancer.

Chaligné R, Popova T, Mendoza-Parra MA, Saleem MA, Gentien D, Ban K, Piolot T, Leroy O, Mariani O, Gronemeyer H, Vincent-Salomon A, Stern MH, Heard E.

Genome Res. 2015 Apr;25(4):488-503. doi: 10.1101/gr.185926.114. Epub 2015 Feb 4.

12.

Integrative genomics to dissect retinoid functions.

Mendoza-Parra MA, Gronemeyer H.

Subcell Biochem. 2014;70:181-202. doi: 10.1007/978-94-017-9050-5_9. Review.

PMID:
24962886
13.

Senescence-secreted factors activate Myc and sensitize pretransformed cells to TRAIL-induced apoptosis.

Vjetrovic J, Shankaranarayanan P, Mendoza-Parra MA, Gronemeyer H.

Aging Cell. 2014 Jun;13(3):487-96. doi: 10.1111/acel.12197. Epub 2014 Mar 4.

14.

Characterising ChIP-seq binding patterns by model-based peak shape deconvolution.

Mendoza-Parra MA, Nowicka M, Van Gool W, Gronemeyer H.

BMC Genomics. 2013 Nov 26;14:834. doi: 10.1186/1471-2164-14-834.

15.

A quality control system for profiles obtained by ChIP sequencing.

Mendoza-Parra MA, Van Gool W, Mohamed Saleem MA, Ceschin DG, Gronemeyer H.

Nucleic Acids Res. 2013 Nov;41(21):e196. doi: 10.1093/nar/gkt829. Epub 2013 Sep 14.

16.

Genome-wide studies of nuclear receptors in cell fate decisions.

Mendoza-Parra MA, Gronemeyer H.

Semin Cell Dev Biol. 2013 Dec;24(10-12):706-15. doi: 10.1016/j.semcdb.2013.07.001. Epub 2013 Aug 2. Review.

PMID:
23916718
17.

Single-tube linear DNA amplification for genome-wide studies using a few thousand cells.

Shankaranarayanan P, Mendoza-Parra MA, van Gool W, Trindade LM, Gronemeyer H.

Nat Protoc. 2012 Jan 26;7(2):328-38. doi: 10.1038/nprot.2011.447.

PMID:
22281868
18.

POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq profiles by non-linear normalization.

Mendoza-Parra MA, Sankar M, Walia M, Gronemeyer H.

Nucleic Acids Res. 2012 Feb;40(4):e30. doi: 10.1093/nar/gkr1205. Epub 2011 Dec 7.

19.

Dissecting the retinoid-induced differentiation of F9 embryonal stem cells by integrative genomics.

Mendoza-Parra MA, Walia M, Sankar M, Gronemeyer H.

Mol Syst Biol. 2011 Oct 11;7:538. doi: 10.1038/msb.2011.73.

20.

Single-tube linear DNA amplification (LinDA) for robust ChIP-seq.

Shankaranarayanan P, Mendoza-Parra MA, Walia M, Wang L, Li N, Trindade LM, Gronemeyer H.

Nat Methods. 2011 Jun 5;8(7):565-7. doi: 10.1038/nmeth.1626.

PMID:
21642965

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