These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

337 related articles for article (PubMed ID: 20195367)

  • 1. Optimal in silico target gene deletion through nonlinear programming for genetic engineering.
    Hong CC; Song M
    PLoS One; 2010 Feb; 5(2):e9331. PubMed ID: 20195367
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Evolutionary programming as a platform for in silico metabolic engineering.
    Patil KR; Rocha I; Förster J; Nielsen J
    BMC Bioinformatics; 2005 Dec; 6():308. PubMed ID: 16375763
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Growing seed genes from time series data and thresholded Boolean networks with perturbation.
    Higa CH; Andrade TP; Hashimoto RF
    IEEE/ACM Trans Comput Biol Bioinform; 2013; 10(1):37-49. PubMed ID: 23702542
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Reverse engineering genetic networks using nonlinear saturation kinetics.
    Kizhakkethil Youseph AS; Chetty M; Karmakar G
    Biosystems; 2019 Aug; 182():30-41. PubMed ID: 31185246
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Intervention in gene regulatory networks via a stationary mean-first-passage-time control policy.
    Vahedi G; Faryabi B; Chamberland JF; Datta A; Dougherty ER
    IEEE Trans Biomed Eng; 2008 Oct; 55(10):2319-31. PubMed ID: 18838357
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Finding optimal gene networks using biological constraints.
    Ott S; Miyano S
    Genome Inform; 2003; 14():124-33. PubMed ID: 15706527
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improving gene regulatory network inference using network topology information.
    Nair A; Chetty M; Wangikar PP
    Mol Biosyst; 2015 Sep; 11(9):2449-63. PubMed ID: 26126758
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Generating realistic in silico gene networks for performance assessment of reverse engineering methods.
    Marbach D; Schaffter T; Mattiussi C; Floreano D
    J Comput Biol; 2009 Feb; 16(2):229-39. PubMed ID: 19183003
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.
    Kentzoglanakis K; Poole M
    IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(2):358-71. PubMed ID: 21576756
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Chromosome structures: reduction of certain problems with unequal gene content and gene paralogs to integer linear programming.
    Lyubetsky V; Gershgorin R; Gorbunov K
    BMC Bioinformatics; 2017 Dec; 18(1):537. PubMed ID: 29212445
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses.
    Guillén-Gosálbez G; Sorribas A
    BMC Bioinformatics; 2009 Nov; 10():386. PubMed ID: 19930714
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Natural computation meta-heuristics for the in silico optimization of microbial strains.
    Rocha M; Maia P; Mendes R; Pinto JP; Ferreira EC; Nielsen J; Patil KR; Rocha I
    BMC Bioinformatics; 2008 Nov; 9():499. PubMed ID: 19038030
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.
    Lee WP; Hsiao YT; Hwang WC
    BMC Syst Biol; 2014 Jan; 8():5. PubMed ID: 24428926
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An integer optimization algorithm for robust identification of non-linear gene regulatory networks.
    Chemmangattuvalappil N; Task K; Banerjee I
    BMC Syst Biol; 2012 Sep; 6():119. PubMed ID: 22937832
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Quantitative inference of dynamic regulatory pathways via microarray data.
    Chang WC; Li CW; Chen BS
    BMC Bioinformatics; 2005 Mar; 6():44. PubMed ID: 15748298
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Combinatorial metabolic engineering using an orthogonal tri-functional CRISPR system.
    Lian J; HamediRad M; Hu S; Zhao H
    Nat Commun; 2017 Nov; 8(1):1688. PubMed ID: 29167442
    [TBL] [Abstract][Full Text] [Related]  

  • 17. In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae.
    Alves R; Sorribas A
    BMC Syst Biol; 2007 Jan; 1():10. PubMed ID: 17408500
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification of metabolic engineering targets through analysis of optimal and sub-optimal routes.
    Soons ZI; Ferreira EC; Patil KR; Rocha I
    PLoS One; 2013; 8(4):e61648. PubMed ID: 23626708
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Reverse engineering of gene networks with LASSO and nonlinear basis functions.
    Gustafsson M; Hörnquist M; Lundström J; Björkegren J; Tegnér J
    Ann N Y Acad Sci; 2009 Mar; 1158():265-75. PubMed ID: 19348648
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Genetic Interaction Motif Finding by expectation maximization--a novel statistical model for inferring gene modules from synthetic lethality.
    Qi Y; Ye P; Bader JS
    BMC Bioinformatics; 2005 Dec; 6():288. PubMed ID: 16332255
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.