BTNET :   Boosted tree based gene regulatory network inference algorithm using time-course measurement data

BTNET is a gene regulatory network inference algorithm using time course measurement data. BTNET infers a gene regulatory network by computing regulatory interaction scores between genes in the measurment data using boosted tree algorithms.
BTNET-Adaboost uses adaptive boosting and BTNET-Graboost uses gradient boosting for comptuing the regulatory interaction scores.

To download the source code of BTNET and all the time-course datasets used in this study, click on the below links.

  • Source code
  • Time-course datasets

  • References

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    Sungjoon Park:
    Jung Min Kim:
    Ik-Soon Jang:
    Jaewoo Kang: