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Generating the Logicome from Microarray Data

Charmi Panchal, Vladimir Rogojin, Generating the Logicome from Microarray Data. TUCS Technical Reports 1175, TUCS, 2017.


The advances in complex statistics and machine learning methods lead to the development
of powerfull classifiers that can be used to recognize cellular states, (such
as gene expression profiles) that are associated to a number of gene-scale expressed
diseases, for instance, cancer. However, the data-driven models built by means
of learning from datasets mostly represent ”black boxes” that cannot be easily
analysed and understood. On the other hand, a lot of modelling efforts in systems
biology are directed towards constructing highly detailed large models for the
closer connection to the real life picture. Meanwhile, for the better comprehension
of the phenomena, also, a complementary higher abstraction level modeling that
captures relations only between the key elements of the larger model, is needed.
Recently, there was suggested a method for translating large bio-molecular network
models into so-called logicome, a small boolean network reflecting activation
conditions between key nodes of the large network. In this article, we suggest a
method for building a data-driven logicome. I.e., the method for building a set
of small boolean expressions as classifiers for disjoint groups of samples from a
microarray dataset. We validate our method on the microarray dataset of Head and
neck/Oral squamous cell carcinoma, where our boolean classifiers presented a set
of gene activity/inactivity combinations that are characteristic for various cancer
sub-types and normal samples. Our findings correlate well with the literature.


Full publication in PDF-format

BibTeX entry:

  title = {Generating the Logicome from Microarray Data},
  author = {Panchal, Charmi and Rogojin, Vladimir},
  number = {1175},
  series = {TUCS Technical Reports},
  publisher = {TUCS},
  year = {2017},

Belongs to TUCS Research Unit(s): Computational Biomodeling Laboratory (Combio Lab)

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