IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0069220.html
   My bibliography  Save this article

Reconstruction of Cellular Signal Transduction Networks Using Perturbation Assays and Linear Programming

Author

Listed:
  • Bettina Knapp
  • Lars Kaderali

Abstract

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4+ T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

Suggested Citation

  • Bettina Knapp & Lars Kaderali, 2013. "Reconstruction of Cellular Signal Transduction Networks Using Perturbation Assays and Linear Programming," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
  • Handle: RePEc:plo:pone00:0069220
    DOI: 10.1371/journal.pone.0069220
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0069220
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0069220&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0069220?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Patrick Müller & David Kuttenkeuler & Viola Gesellchen & Martin P. Zeidler & Michael Boutros, 2005. "Identification of JAK/STAT signalling components by genome-wide RNA interference," Nature, Nature, vol. 436(7052), pages 871-875, August.
    2. Adam Friedman & Norbert Perrimon, 2006. "A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling," Nature, Nature, vol. 444(7116), pages 230-234, November.
    3. Angelique W. Whitehurst & Brian O. Bodemann & Jessica Cardenas & Deborah Ferguson & Luc Girard & Michael Peyton & John D. Minna & Carolyn Michnoff & Weihua Hao & Michael G. Roth & Xian-Jin Xie & Micha, 2007. "Synthetic lethal screen identification of chemosensitizer loci in cancer cells," Nature, Nature, vol. 446(7137), pages 815-819, April.
    4. Manoj N. Krishnan & Aylwin Ng & Bindu Sukumaran & Felicia D. Gilfoy & Pradeep D. Uchil & Hameeda Sultana & Abraham L. Brass & Rachel Adametz & Melody Tsui & Feng Qian & Ruth R. Montgomery & Sima Lev &, 2008. "RNA interference screen for human genes associated with West Nile virus infection," Nature, Nature, vol. 455(7210), pages 242-245, September.
    5. Ralf Kittler & Gabriele Putz & Laurence Pelletier & Ina Poser & Anne-Kristin Heninger & David Drechsel & Steffi Fischer & Irena Konstantinova & Bianca Habermann & Hannes Grabner & Marie-Laure Yaspo & , 2004. "An endoribonuclease-prepared siRNA screen in human cells identifies genes essential for cell division," Nature, Nature, vol. 432(7020), pages 1036-1040, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. T M Murali & Matthew D Dyer & David Badger & Brett M Tyler & Michael G Katze, 2011. "Network-Based Prediction and Analysis of HIV Dependency Factors," PLOS Computational Biology, Public Library of Science, vol. 7(9), pages 1-15, September.
    2. Deborah Chasman & Brandi Gancarz & Linhui Hao & Michael Ferris & Paul Ahlquist & Mark Craven, 2014. "Inferring Host Gene Subnetworks Involved in Viral Replication," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-22, May.
    3. Casey S Greene & Olga G Troyanskaya, 2012. "Chapter 2: Data-Driven View of Disease Biology," PLOS Computational Biology, Public Library of Science, vol. 8(12), pages 1-8, December.
    4. Jing Tang & Leena Karhinen & Tao Xu & Agnieszka Szwajda & Bhagwan Yadav & Krister Wennerberg & Tero Aittokallio, 2013. "Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-16, September.
    5. Abigail W Bigham & Kati J Buckingham & Sofia Husain & Mary J Emond & Kathryn M Bofferding & Heidi Gildersleeve & Ann Rutherford & Natalia M Astakhova & Andrey A Perelygin & Michael P Busch & Kristy O , 2011. "Host Genetic Risk Factors for West Nile Virus Infection and Disease Progression," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-11, September.
    6. Victoria O. Shender & Ksenia S. Anufrieva & Polina V. Shnaider & Georgij P. Arapidi & Marat S. Pavlyukov & Olga M. Ivanova & Irina K. Malyants & Grigory A. Stepanov & Evgenii Zhuravlev & Rustam H. Zig, 2024. "Therapy-induced secretion of spliceosomal components mediates pro-survival crosstalk between ovarian cancer cells," Nature Communications, Nature, vol. 15(1), pages 1-26, December.
    7. Linhui Hao & Qiuling He & Zhishi Wang & Mark Craven & Michael A Newton & Paul Ahlquist, 2013. "Limited Agreement of Independent RNAi Screens for Virus-Required Host Genes Owes More to False-Negative than False-Positive Factors," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-20, September.
    8. Sahar Harati & Lee A D Cooper & Josue D Moran & Felipe O Giuste & Yuhong Du & Andrei A Ivanov & Margaret A Johns & Fadlo R Khuri & Haian Fu & Carlos S Moreno, 2017. "MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-18, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0069220. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.