Format
Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 20 of 21

1.

Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data.

Razzaq M, Paulevé L, Siegel A, Saez-Rodriguez J, Bourdon J, Guziolowski C.

PLoS Comput Biol. 2018 Oct 29;14(10):e1006538. doi: 10.1371/journal.pcbi.1006538. eCollection 2018 Oct.

2.

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection.

Fourati S, Talla A, Mahmoudian M, Burkhart JG, Klén R, Henao R, Yu T, Aydın Z, Yeung KY, Ahsen ME, Almugbel R, Jahandideh S, Liang X, Nordling TEM, Shiga M, Stanescu A, Vogel R; Respiratory Viral DREAM Challenge Consortium, Pandey G, Chiu C, McClain MT, Woods CW, Ginsburg GS, Elo LL, Tsalik EL, Mangravite LM, Sieberts SK.

Nat Commun. 2018 Oct 24;9(1):4418. doi: 10.1038/s41467-018-06735-8.

3.

Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification.

Chebouba L, Boughaci D, Guziolowski C.

J Med Syst. 2018 Jun 4;42(7):129. doi: 10.1007/s10916-018-0972-z.

PMID:
29869179
4.

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

Miannay B, Minvielle S, Magrangeas F, Guziolowski C.

BMC Syst Biol. 2018 Mar 21;12(Suppl 3):32. doi: 10.1186/s12918-018-0551-4.

5.

Discriminate the response of Acute Myeloid Leukemia patients to treatment by using proteomics data and Answer Set Programming.

Chebouba L, Miannay B, Boughaci D, Guziolowski C.

BMC Bioinformatics. 2018 Mar 8;19(Suppl 2):59. doi: 10.1186/s12859-018-2034-4.

6.

Therapeutic target discovery using Boolean network attractors: improvements of kali.

Poret A, Guziolowski C.

R Soc Open Sci. 2018 Feb 14;5(2):171852. doi: 10.1098/rsos.171852. eCollection 2018 Feb.

7.

Logic programming reveals alteration of key transcription factors in multiple myeloma.

Miannay B, Minvielle S, Roux O, Drouin P, Avet-Loiseau H, Guérin-Charbonnel C, Gouraud W, Attal M, Facon T, Munshi NC, Moreau P, Campion L, Magrangeas F, Guziolowski C.

Sci Rep. 2017 Aug 23;7(1):9257. doi: 10.1038/s41598-017-09378-9.

8.

Identification of bifurcation transitions in biological regulatory networks using Answer-Set Programming.

Fitime LF, Roux O, Guziolowski C, Paulevé L.

Algorithms Mol Biol. 2017 Jul 20;12:19. doi: 10.1186/s13015-017-0110-3. eCollection 2017.

9.

caspo: a toolbox for automated reasoning on the response of logical signaling networks families.

Videla S, Saez-Rodriguez J, Guziolowski C, Siegel A.

Bioinformatics. 2017 Mar 15;33(6):947-950. doi: 10.1093/bioinformatics/btw738.

10.

Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming.

Ostrowski M, Paulevé L, Schaub T, Siegel A, Guziolowski C.

Biosystems. 2016 Nov;149:139-153. doi: 10.1016/j.biosystems.2016.07.009. Epub 2016 Jul 30.

PMID:
27484338
11.

Deciphering transcriptional regulations coordinating the response to environmental changes.

Acuña V, Aravena A, Guziolowski C, Eveillard D, Siegel A, Maass A.

BMC Bioinformatics. 2016 Jan 16;17:35. doi: 10.1186/s12859-016-0885-0.

12.

Directed random walks and constraint programming reveal active pathways in hepatocyte growth factor signaling.

Kittas A, Delobelle A, Schmitt S, Breuhahn K, Guziolowski C, Grabe N.

FEBS J. 2016 Jan;283(2):350-60. doi: 10.1111/febs.13580. Epub 2015 Nov 26.

13.

Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies.

Thiele S, Cerone L, Saez-Rodriguez J, Siegel A, Guziołowski C, Klamt S.

BMC Bioinformatics. 2015 Oct 28;16:345. doi: 10.1186/s12859-015-0733-7.

14.

Designing Experiments to Discriminate Families of Logic Models.

Videla S, Konokotina I, Alexopoulos LG, Saez-Rodriguez J, Schaub T, Siegel A, Guziolowski C.

Front Bioeng Biotechnol. 2015 Sep 4;3:131. doi: 10.3389/fbioe.2015.00131. eCollection 2015.

15.

Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.

Guziolowski C, Videla S, Eduati F, Thiele S, Cokelaer T, Siegel A, Saez-Rodriguez J.

Bioinformatics. 2013 Sep 15;29(18):2320-6. doi: 10.1093/bioinformatics/btt393. Epub 2013 Jul 12. Erratum in: Bioinformatics. 2014 Jul 1;30(13):1942.

16.

Automatic generation of causal networks linking growth factor stimuli to functional cell state changes.

Guziolowski C, Kittas A, Dittmann F, Grabe N.

FEBS J. 2012 Sep;279(18):3462-74. doi: 10.1111/j.1742-4658.2012.08616.x. Epub 2012 May 22.

17.

Designing logical rules to model the response of biomolecular networks with complex interactions: an application to cancer modeling.

Guziolowski C, Blachon S, Baumuratova T, Stoll G, Radulescu O, Siegel A.

IEEE/ACM Trans Comput Biol Bioinform. 2011 Sep-Oct;8(5):1223-34. doi: 10.1109/TCBB.2010.71.

PMID:
20733239
18.

BioQuali Cytoscape plugin: analysing the global consistency of regulatory networks.

Guziolowski C, Bourdé A, Moreews F, Siegel A.

BMC Genomics. 2009 May 26;10:244. doi: 10.1186/1471-2164-10-244.

19.

Inferring the role of transcription factors in regulatory networks.

Veber P, Guziolowski C, Le Borgne M, Radulescu O, Siegel A.

BMC Bioinformatics. 2008 May 6;9:228. doi: 10.1186/1471-2105-9-228.

20.

Mapping sequences by parts.

Didier G, Guziolowski C.

Algorithms Mol Biol. 2007 Sep 19;2:11.

Supplemental Content

Loading ...
Support Center