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Journal Abstract Search

386 related items for PubMed ID: 17925357

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  • 2. Supervised inference of gene-regulatory networks.
    To CC, Vohradsky J.
    BMC Bioinformatics; 2008 Jan 04; 9():2. PubMed ID: 18177495
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  • 7. Learning kernels from biological networks by maximizing entropy.
    Tsuda K, Noble WS.
    Bioinformatics; 2004 Aug 04; 20 Suppl 1():i326-33. PubMed ID: 15262816
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  • 8. Using product kernels to predict protein interactions.
    Martin S, Brown WM, Faulon JL.
    Adv Biochem Eng Biotechnol; 2008 Aug 04; 110():215-45. PubMed ID: 17922100
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  • 9. Reverse engineering of dynamic networks.
    Stigler B, Jarrah A, Stillman M, Laubenbacher R.
    Ann N Y Acad Sci; 2007 Dec 04; 1115():168-77. PubMed ID: 17925347
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  • 11. Data requirements of reverse-engineering algorithms.
    Just W.
    Ann N Y Acad Sci; 2007 Dec 04; 1115():142-53. PubMed ID: 17925350
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  • 12. Fitting a geometric graph to a protein-protein interaction network.
    Higham DJ, Rasajski M, Przulj N.
    Bioinformatics; 2008 Apr 15; 24(8):1093-9. PubMed ID: 18344248
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  • 16. Extracting falsifiable predictions from sloppy models.
    Gutenkunst RN, Casey FP, Waterfall JJ, Myers CR, Sethna JP.
    Ann N Y Acad Sci; 2007 Dec 15; 1115():203-11. PubMed ID: 17925353
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  • 17. Dialogue on reverse-engineering assessment and methods: the DREAM of high-throughput pathway inference.
    Stolovitzky G, Monroe D, Califano A.
    Ann N Y Acad Sci; 2007 Dec 15; 1115():1-22. PubMed ID: 17925349
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  • 18. Selective integration of multiple biological data for supervised network inference.
    Kato T, Tsuda K, Asai K.
    Bioinformatics; 2005 May 15; 21(10):2488-95. PubMed ID: 15728114
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  • 19. Reverse engineering gene regulatory networks.
    Hartemink AJ.
    Nat Biotechnol; 2005 May 15; 23(5):554-5. PubMed ID: 15877071
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