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Items: 40

1.

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose.

Chin EL, Simmons G, Bouzid YY, Kan A, Burnett DJ, Tagkopoulos I, Lemay DG.

Nutrients. 2019 Dec 13;11(12). pii: E3045. doi: 10.3390/nu11123045.

2.

Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning.

Bradley R, Tagkopoulos I, Kim M, Kokkinos Y, Panagiotakos T, Kennedy J, De Meyer G, Watson P, Elliott J.

J Vet Intern Med. 2019 Nov;33(6):2644-2656. doi: 10.1111/jvim.15623. Epub 2019 Sep 26.

3.

Benzalkonium Chlorides: Uses, Regulatory Status, and Microbial Resistance.

Merchel Piovesan Pereira B, Tagkopoulos I.

Appl Environ Microbiol. 2019 Jun 17;85(13). pii: e00377-19. doi: 10.1128/AEM.00377-19. Print 2019 Jul 1. Review.

4.

Compendium of skin molecular signatures identifies key pathological features associated with fibrosis in systemic sclerosis.

Moon SJ, Bae JM, Park KS, Tagkopoulos I, Kim KJ.

Ann Rheum Dis. 2019 Jun;78(6):817-825. doi: 10.1136/annrheumdis-2018-214778. Epub 2019 Apr 5.

PMID:
30952646
5.

Compendium of synovial signatures identifies pathologic characteristics for predicting treatment response in rheumatoid arthritis patients.

Kim KJ, Kim M, Adamopoulos IE, Tagkopoulos I.

Clin Immunol. 2019 May;202:1-10. doi: 10.1016/j.clim.2019.03.002. Epub 2019 Mar 1.

PMID:
30831253
6.

Application of machine learning in rheumatic disease research.

Kim KJ, Tagkopoulos I.

Korean J Intern Med. 2019 Jul;34(4):708-722. doi: 10.3904/kjim.2018.349. Epub 2018 Dec 31. Review.

7.

Population collapse and adaptive rescue during long-term chemostat fermentation.

Rai N, Huynh L, Kim M, Tagkopoulos I.

Biotechnol Bioeng. 2019 Mar;116(3):693-703. doi: 10.1002/bit.26898. Epub 2019 Jan 16.

PMID:
30536368
8.

Genetic Neural Networks: an artificial neural network architecture for capturing gene expression relationships.

Eetemadi A, Tagkopoulos I.

Bioinformatics. 2019 Jul 1;35(13):2226-2234. doi: 10.1093/bioinformatics/bty945.

PMID:
30452523
9.

Predicting the evolution of Escherichia coli by a data-driven approach.

Wang X, Zorraquino V, Kim M, Tsoukalas A, Tagkopoulos I.

Nat Commun. 2018 Sep 3;9(1):3562. doi: 10.1038/s41467-018-05807-z.

10.

Data integration and predictive modeling methods for multi-omics datasets.

Kim M, Tagkopoulos I.

Mol Omics. 2018 Feb 12;14(1):8-25. doi: 10.1039/c7mo00051k. Review.

PMID:
29725673
11.

DeepPep: Deep proteome inference from peptide profiles.

Kim M, Eetemadi A, Tagkopoulos I.

PLoS Comput Biol. 2017 Sep 5;13(9):e1005661. doi: 10.1371/journal.pcbi.1005661. eCollection 2017 Sep.

12.

Elucidating Substrate Promiscuity within the FabI Enzyme Family.

Freund GS, O'Brien TE, Vinson L, Carlin DA, Yao A, Mak WS, Tagkopoulos I, Facciotti MT, Tantillo DJ, Siegel JB.

ACS Chem Biol. 2017 Sep 15;12(9):2465-2473. doi: 10.1021/acschembio.7b00400. Epub 2017 Aug 31.

PMID:
28820936
13.

Integrated omics analyses of retrograde signaling mutant delineate interrelated stress-response strata.

Bjornson M, Balcke GU, Xiao Y, de Souza A, Wang JZ, Zhabinskaya D, Tagkopoulos I, Tissier A, Dehesh K.

Plant J. 2017 Jul;91(1):70-84. doi: 10.1111/tpj.13547. Epub 2017 Apr 29.

14.

The Genetic and Transcriptional Basis of Short and Long Term Adaptation across Multiple Stresses in Escherichia coli.

Zorraquino V, Kim M, Rai N, Tagkopoulos I.

Mol Biol Evol. 2017 Mar 1;34(3):707-717. doi: 10.1093/molbev/msw269.

PMID:
28007978
15.

Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli.

Kim M, Rai N, Zorraquino V, Tagkopoulos I.

Nat Commun. 2016 Oct 7;7:13090. doi: 10.1038/ncomms13090.

16.

A Parts Database with Consensus Parameter Estimation for Synthetic Circuit Design.

Huynh L, Tagkopoulos I.

ACS Synth Biol. 2016 Dec 16;5(12):1412-1420. Epub 2016 Jul 25.

PMID:
27454439
17.

Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants.

Carlin DA, Caster RW, Wang X, Betzenderfer SA, Chen CX, Duong VM, Ryklansky CV, Alpekin A, Beaumont N, Kapoor H, Kim N, Mohabbot H, Pang B, Teel R, Whithaus L, Tagkopoulos I, Siegel JB.

PLoS One. 2016 Jan 27;11(1):e0147596. doi: 10.1371/journal.pone.0147596. eCollection 2016.

18.

RiboTALE: A modular, inducible system for accurate gene expression control.

Rai N, Ferreiro A, Neckelmann A, Soon A, Yao A, Siegel J, Facciotti MT, Tagkopoulos I.

Sci Rep. 2015 May 29;5:10658. doi: 10.1038/srep10658.

19.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

Huynh L, Tagkopoulos I.

ACS Synth Biol. 2015 Aug 21;4(8):890-7. doi: 10.1021/sb500339k. Epub 2015 Apr 28.

PMID:
25916918
20.

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

Kim M, Zorraquino V, Tagkopoulos I.

PLoS Comput Biol. 2015 Mar 16;11(3):e1004127. doi: 10.1371/journal.pcbi.1004127. eCollection 2015 Mar. Erratum in: PLoS Comput Biol. 2015 Nov;11(11):e1004617.

21.

From data to optimal decision making: a data-driven, probabilistic machine learning approach to decision support for patients with sepsis.

Tsoukalas A, Albertson T, Tagkopoulos I.

JMIR Med Inform. 2015 Feb 24;3(1):e11. doi: 10.2196/medinform.3445.

22.

An Arabidopsis gene regulatory network for secondary cell wall synthesis.

Taylor-Teeples M, Lin L, de Lucas M, Turco G, Toal TW, Gaudinier A, Young NF, Trabucco GM, Veling MT, Lamothe R, Handakumbura PP, Xiong G, Wang C, Corwin J, Tsoukalas A, Zhang L, Ware D, Pauly M, Kliebenstein DJ, Dehesh K, Tagkopoulos I, Breton G, Pruneda-Paz JL, Ahnert SE, Kay SA, Hazen SP, Brady SM.

Nature. 2015 Jan 29;517(7536):571-5. doi: 10.1038/nature14099. Epub 2014 Dec 24.

23.

A systems biology analysis of brain microvascular endothelial cell lipotoxicity.

Aung HH, Tsoukalas A, Rutledge JC, Tagkopoulos I.

BMC Syst Biol. 2014 Jul 4;8:80. doi: 10.1186/1752-0509-8-80.

24.

An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli.

Carrera J, Estrela R, Luo J, Rai N, Tsoukalas A, Tagkopoulos I.

Mol Syst Biol. 2014 Jul 1;10:735. doi: 10.15252/msb.20145108.

25.

Optimal part and module selection for synthetic gene circuit design automation.

Huynh L, Tagkopoulos I.

ACS Synth Biol. 2014 Aug 15;3(8):556-64. doi: 10.1021/sb400139h. Epub 2014 Feb 27.

PMID:
24933033
26.

From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system.

Gultepe E, Green JP, Nguyen H, Adams J, Albertson T, Tagkopoulos I.

J Am Med Inform Assoc. 2014 Mar-Apr;21(2):315-25. doi: 10.1136/amiajnl-2013-001815. Epub 2013 Aug 19.

27.

Promoter element arising from the fusion of standard BioBrick parts.

Yao AI, Fenton TA, Owsley K, Seitzer P, Larsen DJ, Sit H, Lau J, Nair A, Tantiongloc J, Tagkopoulos I, Facciotti MT.

ACS Synth Biol. 2013 Feb 15;2(2):111-20. doi: 10.1021/sb300114d. Epub 2013 Jan 11. Erratum in: ACS Synth Biol. 2013 Jun 21;2(6):351.

PMID:
23656374
28.

SBROME: a scalable optimization and module matching framework for automated biosystems design.

Huynh L, Tsoukalas A, Köppe M, Tagkopoulos I.

ACS Synth Biol. 2013 May 17;2(5):263-73. doi: 10.1021/sb300095m. Epub 2013 Mar 11.

PMID:
23654271
29.

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Pavlogiannis A, Mozhayskiy V, Tagkopoulos I.

BMC Bioinformatics. 2013 Apr 24;14:137. doi: 10.1186/1471-2105-14-137.

30.

Evolutionary potential, cross-stress behavior and the genetic basis of acquired stress resistance in Escherichia coli.

Dragosits M, Mozhayskiy V, Quinones-Soto S, Park J, Tagkopoulos I.

Mol Syst Biol. 2013;9:643. doi: 10.1038/msb.2012.76.

31.

Microbial evolution in vivo and in silico: methods and applications.

Mozhayskiy V, Tagkopoulos I.

Integr Biol (Camb). 2013 Feb;5(2):262-77. doi: 10.1039/c2ib20095c. Review.

PMID:
23096365
32.

Microbial factories under control: auto-regulatory control through engineered stress-induced feedback.

Tagkopoulos I.

Bioengineered. 2013 Jan-Feb;4(1):5-8. doi: 10.4161/bioe.21935. Epub 2012 Aug 24.

33.

Transcriptional network analysis identifies BACH1 as a master regulator of breast cancer bone metastasis.

Liang Y, Wu H, Lei R, Chong RA, Wei Y, Lu X, Tagkopoulos I, Kung SY, Yang Q, Hu G, Kang Y.

J Biol Chem. 2012 Sep 28;287(40):33533-44. Epub 2012 Aug 8.

34.

Horizontal gene transfer dynamics and distribution of fitness effects during microbial in silico evolution.

Mozhayskiy V, Tagkopoulos I.

BMC Bioinformatics. 2012 Jun 25;13 Suppl 10:S13. doi: 10.1186/1471-2105-13-S10-S13.

35.

Guided evolution of in silico microbial populations in complex environments accelerates evolutionary rates through a step-wise adaptation.

Mozhayskiy V, Tagkopoulos I.

BMC Bioinformatics. 2012 Jun 25;13 Suppl 10:S10. doi: 10.1186/1471-2105-13-S10-S10.

36.

Automatic design of synthetic gene circuits through mixed integer non-linear programming.

Huynh L, Kececioglu J, Köppe M, Tagkopoulos I.

PLoS One. 2012;7(4):e35529. doi: 10.1371/journal.pone.0035529. Epub 2012 Apr 20.

37.

A synthetic biology approach to self-regulatory recombinant protein production in Escherichia coli.

Dragosits M, Nicklas D, Tagkopoulos I.

J Biol Eng. 2012 Mar 30;6(1):2. doi: 10.1186/1754-1611-6-2.

38.

Predictive behavior within microbial genetic networks.

Tagkopoulos I, Liu YC, Tavazoie S.

Science. 2008 Jun 6;320(5881):1313-7. doi: 10.1126/science.1154456. Epub 2008 May 8.

39.

Symmetric and asymmetric multi-modality biclustering analysis for microarray data matrix.

Kung SY, Mak MW, Tagkopoulos I.

J Bioinform Comput Biol. 2006 Apr;4(2):275-98.

PMID:
16819784
40.

Multi-metric and multi-substructure biclustering analysis for gene expression data.

Kung SY, Mak MW, Tagkopoulos I.

Proc IEEE Comput Syst Bioinform Conf. 2005:123-34.

PMID:
16447970

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