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IPM
30
YEARS OLD

“Papers of School of Biological Sciences”

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  81. H. Ebadi, M. Saeedian, M. Ausloos and Gholam Reza Jafari,
Effect of memory in non-Markovian Boolean networks illustrated with a case study: A cell cycling process,
116(2016), 30004 - https://doi.org/10.1209/0295-5075/116/30004  [abstract]

   82. R. Aghdam, P. Khosravi and E. Saberi Ansari,
Comparative Analysis of Gene Regulatory Networks Concepts in Normal and Cancer Groups,
Bioinformatics and Biocomputational Research (2016), 1  [abstract]

   83. H. Ebadi, M. Saeedian, M. Ausloos and G.H. Jafari,
Effect of memory in non-Markovian Boolean networks illustrated with a case study: A cell cycling process,
EPL 116(2016), https://doi.org/10.1209/0295-5075/116/30004  [abstract]

   84. N. Ansari-Pour, Z. Razaghi Moghadam, F. Barneh and M. Jafari,
Testis-Specific Y-Centric Protein–Protein Interaction Network Provides Clues to the Etiology of Severe Spermatogenic Failure,
Journal of proteome research 15(2016), 1011-1022  [abstract]

   85. A. Malekpour, H. Pezeshk and M. Sadeghi,
PSE-HMM: genome-wide CNV detection from NGS data using an HMM with Position-Specific Emission probabilities,
BMC Bioinformatics https://doi.org/10.1186/s12859-016-1296-y(2016), 1-30  [abstract]

   86. R. Jafari, M. Sadeghi and M. Mirzaie,
Investigating the importance of Delaunay-based definition of atomic interactions in scoring of protein–protein docking results,
J. Mol. Graphics and Modelling 16(2016), 108�??114�??�??  [abstract]

   87. S. A. Malekpour, H. Pezeshk and M. Sadeghi,
MGP-HMM: detecting genome-wide CNVs using an HMM for modeling mate pair insertion sizes and read counts,
Mathematical Biosciences (2016), 53-62  [abstract]

   88. V. Rezaei Tabar and H. Pezeshk,
Generalized Profile Hidden Markov Model (PHMM) based on the Dependency between sequences,
Progress in Biological Sciences 6(2016), 117-127 10.22059/PBS.2016.590014  [abstract]

   89. V. Rezaei Tabar, F. Eskandari and S. Salimi,
A novel node ordering method using L1-regularized Markov Blanket and modified likelihood reduction factor for the K2 algorithm,
pattern recognition letter  (to appear) [abstract]

   90. M. H. REYHANI and H. Poormohammadi,
RPNCH: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets based on Height Function,
Indian Journal of Science and Technology  (to appear) [abstract]

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