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By adopting a probabilistic modeling framework compatible with the family of models represented by dynamic Bayesian networks and probabilistic Boolean networks, this paper proposes a network inference algorithm to recover not only the direct gene connectivity but also the regulating orientations.<\/jats:p>\n               <jats:p>Results: Based on the minimum description length principle, a novel network inference algorithm is proposed that greatly shrinks the search space for graphical solutions and achieves a good trade-off between modeling complexity and data fitting. Simulation results show that the algorithm achieves good performance in the case of synthetic networks. Compared with existing state-of-the-art results in the literature, the proposed algorithm exceptionally excels in efficiency, accuracy, robustness and scalability. Given a time-series dataset for Drosophila melanogaster, the paper proposes a genetic regulatory network involved in Drosophila's muscle development.<\/jats:p>\n               <jats:p>Availability: Available from the authors upon request.<\/jats:p>\n               <jats:p>Contact: \u00a0wtzhao@ece.tamu.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl364","type":"journal-article","created":{"date-parts":[[2006,7,16]],"date-time":"2006-07-16T01:50:42Z","timestamp":1153014642000},"page":"2129-2135","source":"Crossref","is-referenced-by-count":114,"title":["Inferring gene regulatory networks from time series data using the minimum description length principle"],"prefix":"10.1093","volume":"22","author":[{"given":"Wentao","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Texas A&M University 1 \u00a0 1 \u00a0 \u00a0 College Station, TX 77843-3128, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erchin","family":"Serpedin","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Texas A&M University 1 \u00a0 1 \u00a0 \u00a0 College Station, TX 77843-3128, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward R.","family":"Dougherty","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Texas A&M University 1 \u00a0 1 \u00a0 \u00a0 College Station, TX 77843-3128, USA"},{"name":"Translational Genomics Research Institute, 400 North Fifth Street 2 \u00a0 2 \u00a0 \u00a0 Suite 1600, Phoenix, AZ 85004, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2006,7,15]]},"reference":[{"key":"2023012409132711200_b1","doi-asserted-by":"crossref","first-page":"2270","DOI":"10.1126\/science.1072152","article-title":"Gene expression during the life cycle of Drosophila melanogaster","volume":"297","author":"Arbeitman","year":"2002","journal-title":"Science"},{"key":"2023012409132711200_b2","first-page":"17","article-title":"Nonparametric entropy estimation: an overview","volume":"6","author":"Beirlant","year":"1997","journal-title":"Int. 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