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Items: 35

1.

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas.

Knijnenburg TA, Wang L, Zimmermann MT, Chambwe N, Gao GF, Cherniack AD, Fan H, Shen H, Way GP, Greene CS, Liu Y, Akbani R, Feng B, Donehower LA, Miller C, Shen Y, Karimi M, Chen H, Kim P, Jia P, Shinbrot E, Zhang S, Liu J, Hu H, Bailey MH, Yau C, Wolf D, Zhao Z, Weinstein JN, Li L, Ding L, Mills GB, Laird PW, Wheeler DA, Shmulevich I; Cancer Genome Atlas Research Network, Monnat RJ Jr, Xiao Y, Wang C.

Cell Rep. 2018 Apr 3;23(1):239-254.e6. doi: 10.1016/j.celrep.2018.03.076.

2.

Identifying novel transcription factors involved in the inflammatory response by using binding site motif scanning in genomic regions defined by histone acetylation.

Askovich PS, Ramsey SA, Diercks AH, Kennedy KA, Knijnenburg TA, Aderem A.

PLoS One. 2017 Sep 18;12(9):e0184850. doi: 10.1371/journal.pone.0184850. eCollection 2017.

3.

Extracting Intercellular Signaling Network of Cancer Tissues using Ligand-Receptor Expression Patterns from Whole-tumor and Single-cell Transcriptomes.

Zhou JX, Taramelli R, Pedrini E, Knijnenburg T, Huang S.

Sci Rep. 2017 Aug 18;7(1):8815. doi: 10.1038/s41598-017-09307-w.

4.

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression.

Poole W, Leinonen K, Shmulevich I, Knijnenburg TA, Bernard B.

PLoS Comput Biol. 2017 Feb 7;13(2):e1005347. doi: 10.1371/journal.pcbi.1005347. eCollection 2017 Feb. Erratum in: PLoS Comput Biol. 2017 Apr 6;13(4):e1005472.

5.

Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.

Knijnenburg TA, Klau GW, Iorio F, Garnett MJ, McDermott U, Shmulevich I, Wessels LF.

Sci Rep. 2016 Nov 23;6:36812. doi: 10.1038/srep36812.

6.

Loss of ARID1A Activates ANXA1, which Serves as a Predictive Biomarker for Trastuzumab Resistance.

Berns K, Sonnenblick A, Gennissen A, Brohée S, Hijmans EM, Evers B, Fumagalli D, Desmedt C, Loibl S, Denkert C, Neven P, Guo W, Zhang F, Knijnenburg TA, Bosse T, van der Heijden MS, Hindriksen S, Nijkamp W, Wessels LF, Joensuu H, Mills GB, Beijersbergen RL, Sotiriou C, Bernards R.

Clin Cancer Res. 2016 Nov 1;22(21):5238-5248. Epub 2016 May 12.

7.

Combining dependent P-values with an empirical adaptation of Brown's method.

Poole W, Gibbs DL, Shmulevich I, Bernard B, Knijnenburg TA.

Bioinformatics. 2016 Sep 1;32(17):i430-i436. doi: 10.1093/bioinformatics/btw438.

8.

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma.

Zheng S, Cherniack AD, Dewal N, Moffitt RA, Danilova L, Murray BA, Lerario AM, Else T, Knijnenburg TA, Ciriello G, Kim S, Assie G, Morozova O, Akbani R, Shih J, Hoadley KA, Choueiri TK, Waldmann J, Mete O, Robertson AG, Wu HT, Raphael BJ, Shao L, Meyerson M, Demeure MJ, Beuschlein F, Gill AJ, Sidhu SB, Almeida MQ, Fragoso MCBV, Cope LM, Kebebew E, Habra MA, Whitsett TG, Bussey KJ, Rainey WE, Asa SL, Bertherat J, Fassnacht M, Wheeler DA; Cancer Genome Atlas Research Network, Hammer GD, Giordano TJ, Verhaak RGW.

Cancer Cell. 2016 Aug 8;30(2):363. doi: 10.1016/j.ccell.2016.07.013. Epub 2016 Aug 8. No abstract available.

9.

A Landscape of Pharmacogenomic Interactions in Cancer.

Iorio F, Knijnenburg TA, Vis DJ, Bignell GR, Menden MP, Schubert M, Aben N, Gonçalves E, Barthorpe S, Lightfoot H, Cokelaer T, Greninger P, van Dyk E, Chang H, de Silva H, Heyn H, Deng X, Egan RK, Liu Q, Mironenko T, Mitropoulos X, Richardson L, Wang J, Zhang T, Moran S, Sayols S, Soleimani M, Tamborero D, Lopez-Bigas N, Ross-Macdonald P, Esteller M, Gray NS, Haber DA, Stratton MR, Benes CH, Wessels LFA, Saez-Rodriguez J, McDermott U, Garnett MJ.

Cell. 2016 Jul 28;166(3):740-754. doi: 10.1016/j.cell.2016.06.017. Epub 2016 Jul 7.

10.

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma.

Zheng S, Cherniack AD, Dewal N, Moffitt RA, Danilova L, Murray BA, Lerario AM, Else T, Knijnenburg TA, Ciriello G, Kim S, Assie G, Morozova O, Akbani R, Shih J, Hoadley KA, Choueiri TK, Waldmann J, Mete O, Robertson AG, Wu HT, Raphael BJ, Shao L, Meyerson M, Demeure MJ, Beuschlein F, Gill AJ, Sidhu SB, Almeida MQ, Fragoso MCBV, Cope LM, Kebebew E, Habra MA, Whitsett TG, Bussey KJ, Rainey WE, Asa SL, Bertherat J, Fassnacht M, Wheeler DA; Cancer Genome Atlas Research Network, Hammer GD, Giordano TJ, Verhaak RGW.

Cancer Cell. 2016 May 9;29(5):723-736. doi: 10.1016/j.ccell.2016.04.002. Erratum in: Cancer Cell. 2016 Aug 8;30(2):363.

11.

Using Incomplete Trios to Boost Confidence in Family Based Association Studies.

Dhankani V, Gibbs DL, Knijnenburg T, Kramer R, Vockley J, Niederhuber J, Shmulevich I, Bernard B.

Front Genet. 2016 Mar 18;7:34. doi: 10.3389/fgene.2016.00034. eCollection 2016.

12.

CloudForest: A Scalable and Efficient Random Forest Implementation for Biological Data.

Bressler R, Kreisberg RB, Bernard B, Niederhuber JE, Vockley JG, Shmulevich I, Knijnenburg TA.

PLoS One. 2015 Dec 17;10(12):e0144820. doi: 10.1371/journal.pone.0144820. eCollection 2015.

13.

A multilevel pan-cancer map links gene mutations to cancer hallmarks.

Knijnenburg TA, Bismeijer T, Wessels LF, Shmulevich I.

Chin J Cancer. 2015 Sep 14;34(10):439-49. doi: 10.1186/s40880-015-0050-6.

14.

Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.

Cancer Genome Atlas Research Network, Brat DJ, Verhaak RG, Aldape KD, Yung WK, Salama SR, Cooper LA, Rheinbay E, Miller CR, Vitucci M, Morozova O, Robertson AG, Noushmehr H, Laird PW, Cherniack AD, Akbani R, Huse JT, Ciriello G, Poisson LM, Barnholtz-Sloan JS, Berger MS, Brennan C, Colen RR, Colman H, Flanders AE, Giannini C, Grifford M, Iavarone A, Jain R, Joseph I, Kim J, Kasaian K, Mikkelsen T, Murray BA, O'Neill BP, Pachter L, Parsons DW, Sougnez C, Sulman EP, Vandenberg SR, Van Meir EG, von Deimling A, Zhang H, Crain D, Lau K, Mallery D, Morris S, Paulauskis J, Penny R, Shelton T, Sherman M, Yena P, Black A, Bowen J, Dicostanzo K, Gastier-Foster J, Leraas KM, Lichtenberg TM, Pierson CR, Ramirez NC, Taylor C, Weaver S, Wise L, Zmuda E, Davidsen T, Demchok JA, Eley G, Ferguson ML, Hutter CM, Mills Shaw KR, Ozenberger BA, Sheth M, Sofia HJ, Tarnuzzer R, Wang Z, Yang L, Zenklusen JC, Ayala B, Baboud J, Chudamani S, Jensen MA, Liu J, Pihl T, Raman R, Wan Y, Wu Y, Ally A, Auman JT, Balasundaram M, Balu S, Baylin SB, Beroukhim R, Bootwalla MS, Bowlby R, Bristow CA, Brooks D, Butterfield Y, Carlsen R, Carter S, Chin L, Chu A, Chuah E, Cibulskis K, Clarke A, Coetzee SG, Dhalla N, Fennell T, Fisher S, Gabriel S, Getz G, Gibbs R, Guin R, Hadjipanayis A, Hayes DN, Hinoue T, Hoadley K, Holt RA, Hoyle AP, Jefferys SR, Jones S, Jones CD, Kucherlapati R, Lai PH, Lander E, Lee S, Lichtenstein L, Ma Y, Maglinte DT, Mahadeshwar HS, Marra MA, Mayo M, Meng S, Meyerson ML, Mieczkowski PA, Moore RA, Mose LE, Mungall AJ, Pantazi A, Parfenov M, Park PJ, Parker JS, Perou CM, Protopopov A, Ren X, Roach J, Sabedot TS, Schein J, Schumacher SE, Seidman JG, Seth S, Shen H, Simons JV, Sipahimalani P, Soloway MG, Song X, Sun H, Tabak B, Tam A, Tan D, Tang J, Thiessen N, Triche T Jr, Van Den Berg DJ, Veluvolu U, Waring S, Weisenberger DJ, Wilkerson MD, Wong T, Wu J, Xi L, Xu AW, Yang L, Zack TI, Zhang J, Aksoy BA, Arachchi H, Benz C, Bernard B, Carlin D, Cho J, DiCara D, Frazer S, Fuller GN, Gao J, Gehlenborg N, Haussler D, Heiman DI, Iype L, Jacobsen A, Ju Z, Katzman S, Kim H, Knijnenburg T, Kreisberg RB, Lawrence MS, Lee W, Leinonen K, Lin P, Ling S, Liu W, Liu Y, Liu Y, Lu Y, Mills G, Ng S, Noble MS, Paull E, Rao A, Reynolds S, Saksena G, Sanborn Z, Sander C, Schultz N, Senbabaoglu Y, Shen R, Shmulevich I, Sinha R, Stuart J, Sumer SO, Sun Y, Tasman N, Taylor BS, Voet D, Weinhold N, Weinstein JN, Yang D, Yoshihara K, Zheng S, Zhang W, Zou L, Abel T, Sadeghi S, Cohen ML, Eschbacher J, Hattab EM, Raghunathan A, Schniederjan MJ, Aziz D, Barnett G, Barrett W, Bigner DD, Boice L, Brewer C, Calatozzolo C, Campos B, Carlotti CG Jr, Chan TA, Cuppini L, Curley E, Cuzzubbo S, Devine K, DiMeco F, Duell R, Elder JB, Fehrenbach A, Finocchiaro G, Friedman W, Fulop J, Gardner J, Hermes B, Herold-Mende C, Jungk C, Kendler A, Lehman NL, Lipp E, Liu O, Mandt R, McGraw M, Mclendon R, McPherson C, Neder L, Nguyen P, Noss A, Nunziata R, Ostrom QT, Palmer C, Perin A, Pollo B, Potapov A, Potapova O, Rathmell WK, Rotin D, Scarpace L, Schilero C, Senecal K, Shimmel K, Shurkhay V, Sifri S, Singh R, Sloan AE, Smolenski K, Staugaitis SM, Steele R, Thorne L, Tirapelli DP, Unterberg A, Vallurupalli M, Wang Y, Warnick R, Williams F, Wolinsky Y, Bell S, Rosenberg M, Stewart C, Huang F, Grimsby JL, Radenbaugh AJ, Zhang J.

N Engl J Med. 2015 Jun 25;372(26):2481-98. doi: 10.1056/NEJMoa1402121. Epub 2015 Jun 10.

15.

SMARCE1 suppresses EGFR expression and controls responses to MET and ALK inhibitors in lung cancer.

Papadakis AI, Sun C, Knijnenburg TA, Xue Y, Grernrum W, Hölzel M, Nijkamp W, Wessels LF, Beijersbergen RL, Bernards R, Huang S.

Cell Res. 2015 Apr;25(4):445-58. doi: 10.1038/cr.2015.16. Epub 2015 Feb 6.

16.

Deletion of the Saccharomyces cerevisiae ARO8 gene, encoding an aromatic amino acid transaminase, enhances phenylethanol production from glucose.

Romagnoli G, Knijnenburg TA, Liti G, Louis EJ, Pronk JT, Daran JM.

Yeast. 2015 Jan;32(1):29-45. doi: 10.1002/yea.3015. Epub 2014 May 13.

17.

Multiscale representation of genomic signals.

Knijnenburg TA, Ramsey SA, Berman BP, Kennedy KA, Smit AF, Wessels LF, Laird PW, Aderem A, Shmulevich I.

Nat Methods. 2014 Jun;11(6):689-94. doi: 10.1038/nmeth.2924. Epub 2014 Apr 13.

18.

Hallmarks of aromatase inhibitor drug resistance revealed by epigenetic profiling in breast cancer.

Jansen MP, Knijnenburg T, Reijm EA, Simon I, Kerkhoven R, Droog M, Velds A, van Laere S, Dirix L, Alexi X, Foekens JA, Wessels L, Linn SC, Berns EM, Zwart W.

Cancer Res. 2013 Nov 15;73(22):6632-41. doi: 10.1158/0008-5472.CAN-13-0704.

19.

Systematic measurement of transcription factor-DNA interactions by targeted mass spectrometry identifies candidate gene regulatory proteins.

Mirzaei H, Knijnenburg TA, Kim B, Robinson M, Picotti P, Carter GW, Li S, Dilworth DJ, Eng JK, Aitchison JD, Shmulevich I, Galitski T, Aebersold R, Ranish J.

Proc Natl Acad Sci U S A. 2013 Feb 26;110(9):3645-50. doi: 10.1073/pnas.1216918110. Epub 2013 Feb 6.

20.

MED12 controls the response to multiple cancer drugs through regulation of TGF-β receptor signaling.

Huang S, Hölzel M, Knijnenburg T, Schlicker A, Roepman P, McDermott U, Garnett M, Grernrum W, Sun C, Prahallad A, Groenendijk FH, Mittempergher L, Nijkamp W, Neefjes J, Salazar R, Ten Dijke P, Uramoto H, Tanaka F, Beijersbergen RL, Wessels LF, Bernards R.

Cell. 2012 Nov 21;151(5):937-50. doi: 10.1016/j.cell.2012.10.035.

21.

Fastbreak: a tool for analysis and visualization of structural variations in genomic data.

Bressler R, Lin J, Eakin A, Robinson T, Kreisberg R, Rovira H, Knijnenburg T, Boyle J, Shmulevich I.

EURASIP J Bioinform Syst Biol. 2012 Oct 9;2012(1):15. doi: 10.1186/1687-4153-2012-15.

22.

EPEPT: a web service for enhanced P-value estimation in permutation tests.

Knijnenburg TA, Lin J, Rovira H, Boyle J, Shmulevich I.

BMC Bioinformatics. 2011 Oct 24;12:411. doi: 10.1186/1471-2105-12-411.

23.

A regression model approach to enable cell morphology correction in high-throughput flow cytometry.

Knijnenburg TA, Roda O, Wan Y, Nolan GP, Aitchison JD, Shmulevich I.

Mol Syst Biol. 2011 Sep 27;7:531. doi: 10.1038/msb.2011.64.

24.

Genome-wide analysis of effectors of peroxisome biogenesis.

Saleem RA, Long-O'Donnell R, Dilworth DJ, Armstrong AM, Jamakhandi AP, Wan Y, Knijnenburg TA, Niemistö A, Boyle J, Rachubinski RA, Shmulevich I, Aitchison JD.

PLoS One. 2010 Aug 4;5(8):e11953. doi: 10.1371/journal.pone.0011953.

25.

Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites.

Ramsey SA, Knijnenburg TA, Kennedy KA, Zak DE, Gilchrist M, Gold ES, Johnson CD, Lampano AE, Litvak V, Navarro G, Stolyar T, Aderem A, Shmulevich I.

Bioinformatics. 2010 Sep 1;26(17):2071-5. doi: 10.1093/bioinformatics/btq405. Epub 2010 Jul 27.

26.

Fewer permutations, more accurate P-values.

Knijnenburg TA, Wessels LF, Reinders MJ, Shmulevich I.

Bioinformatics. 2009 Jun 15;25(12):i161-8. doi: 10.1093/bioinformatics/btp211.

27.

Combinatorial effects of environmental parameters on transcriptional regulation in Saccharomyces cerevisiae: a quantitative analysis of a compendium of chemostat-based transcriptome data.

Knijnenburg TA, Daran JM, van den Broek MA, Daran-Lapujade PA, de Winde JH, Pronk JT, Reinders MJ, Wessels LF.

BMC Genomics. 2009 Jan 27;10:53. doi: 10.1186/1471-2164-10-53.

28.

Creating gene set activity profiles with time-series expression data.

Knijnenburg TA, Wessels LF, Reinders MJ.

Int J Bioinform Res Appl. 2008;4(3):306-23.

PMID:
18640906
29.

Combinatorial influence of environmental parameters on transcription factor activity.

Knijnenburg TA, Wessels LF, Reinders MJ.

Bioinformatics. 2008 Jul 1;24(13):i172-81. doi: 10.1093/bioinformatics/btn155.

30.

Quantitative proteomics and transcriptomics of anaerobic and aerobic yeast cultures reveals post-transcriptional regulation of key cellular processes.

de Groot MJ, Daran-Lapujade P, van Breukelen B, Knijnenburg TA, de Hulster EA, Reinders MJ, Pronk JT, Heck AJ, Slijper M.

Microbiology. 2007 Nov;153(Pt 11):3864-78.

PMID:
17975095
31.

Physiological and transcriptional responses of Saccharomyces cerevisiae to zinc limitation in chemostat cultures.

De Nicola R, Hazelwood LA, De Hulster EA, Walsh MC, Knijnenburg TA, Reinders MJ, Walker GM, Pronk JT, Daran JM, Daran-Lapujade P.

Appl Environ Microbiol. 2007 Dec;73(23):7680-92. Epub 2007 Oct 12.

32.

Integration of known transcription factor binding site information and gene expression data to advance from co-expression to co-regulation.

Clements M, van Someren EP, Knijnenburg TA, Reinders MJ.

Genomics Proteomics Bioinformatics. 2007 May;5(2):86-101.

33.

Generic and specific transcriptional responses to different weak organic acids in anaerobic chemostat cultures of Saccharomyces cerevisiae.

Abbott DA, Knijnenburg TA, de Poorter LM, Reinders MJ, Pronk JT, van Maris AJ.

FEMS Yeast Res. 2007 Sep;7(6):819-33. Epub 2007 Apr 30.

34.

Exploiting combinatorial cultivation conditions to infer transcriptional regulation.

Knijnenburg TA, de Winde JH, Daran JM, Daran-Lapujade P, Pronk JT, Reinders MJ, Wessels LF.

BMC Genomics. 2007 Jan 22;8:25.

35.

When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation.

Kresnowati MT, van Winden WA, Almering MJ, ten Pierick A, Ras C, Knijnenburg TA, Daran-Lapujade P, Pronk JT, Heijnen JJ, Daran JM.

Mol Syst Biol. 2006;2:49. Epub 2006 Sep 12.

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