IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v35y2001i3p351-372.html
   My bibliography  Save this article

Polarity-free automatic classification of chromosomes

Author

Listed:
  • Ritter, Gunter
  • Pesch, Christoph

Abstract

No abstract is available for this item.

Suggested Citation

  • Ritter, Gunter & Pesch, Christoph, 2001. "Polarity-free automatic classification of chromosomes," Computational Statistics & Data Analysis, Elsevier, vol. 35(3), pages 351-372, January.
    • Handle: RePEc:eee:csdana:v:35:y:2001:i:3:p:351-372
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(00)00022-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. L. Balinski, 1985. "Signature Methods for the Assignment Problem," Operations Research, INFORMS, vol. 33(3), pages 527-536, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ritter, Gunter & Gallegos, María Teresa, 2002. "Bayesian Object Identification: Variants," Journal of Multivariate Analysis, Elsevier, vol. 81(2), pages 301-334, May.
    2. Teresa Gallegos, María & Ritter, Gunter, 2006. "Parameter estimation under ambiguity and contamination with the spurious model," Journal of Multivariate Analysis, Elsevier, vol. 97(5), pages 1221-1250, May.

    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. Pritibhushan Sinha, 2009. "Assignment problems with changeover cost," Annals of Operations Research, Springer, vol. 172(1), pages 447-457, November.
    2. Chen, Liang & Tokuda, Naoyuki, 2001. "A faster data assignment algorithm for maximum likelihood-based multitarget motion tracking with bearings-only measurements," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 57(1), pages 109-120.
    3. Qin, Xiaolin & Tang, Juan & Feng, Yong & Bachmann, Bernhard & Fritzson, Peter, 2016. "Efficient index reduction algorithm for large scale systems of differential algebraic equations," Applied Mathematics and Computation, Elsevier, vol. 277(C), pages 10-22.
    4. Fanrui Xie & Tao Wu & Canrong Zhang, 2019. "A Branch-and-Price Algorithm for the Integrated Berth Allocation and Quay Crane Assignment Problem," Transportation Science, INFORMS, vol. 53(5), pages 1427-1454, September.
    5. Andrei Nikolaev & Anna Kozlova, 2021. "Hamiltonian decomposition and verifying vertex adjacency in 1-skeleton of the traveling salesperson polytope by variable neighborhood search," Journal of Combinatorial Optimization, Springer, vol. 42(2), pages 212-230, August.
    6. Jingqun Li & R. Tharmarasa & Daly Brown & Thia Kirubarajan & Krishna R. Pattipati, 2019. "A novel convex dual approach to three-dimensional assignment problem: theoretical analysis," Computational Optimization and Applications, Springer, vol. 74(2), pages 481-516, November.
    7. Andrei V. Nikolaev & Egor V. Klimov, 2024. "Finding a second Hamiltonian decomposition of a 4-regular multigraph by integer linear programming," Journal of Combinatorial Optimization, Springer, vol. 47(5), pages 1-31, July.
    8. Manfred Padberg & Dimitris Alevras, 1994. "Order‐preserving assignments," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(3), pages 395-421, April.
    9. Orlin, James B., 1953-. & Ahuja, Ravindra K., 1956-., 1988. "New scaling algorithms for the assignment and minimum cycle mean problems," Working papers 2019-88., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    10. Ivan Belik & Kurt Jornsten, 2018. "Critical objective function values in linear sum assignment problems," Journal of Combinatorial Optimization, Springer, vol. 35(3), pages 842-852, April.
    11. Konstantinos Paparrizos & Nikolaos Samaras & Angelo Sifaleras, 2015. "Exterior point simplex-type algorithms for linear and network optimization problems," Annals of Operations Research, Springer, vol. 229(1), pages 607-633, June.
    12. Michael Z. Spivey & Warren B. Powell, 2004. "The Dynamic Assignment Problem," Transportation Science, INFORMS, vol. 38(4), pages 399-419, November.
    13. Jingqun Li & Thia Kirubarajan & R. Tharmarasa & Daly Brown & Krishna R. Pattipati, 2021. "A dual approach to multi-dimensional assignment problems," Journal of Global Optimization, Springer, vol. 81(3), pages 691-716, November.

    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:eee:csdana:v:35:y:2001:i:3:p:351-372. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.