“Papers of School of Biological Sciences”
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181. R. Jafari, M. Sadeghi and M. Mirzaie,
Investigating the importance of Delaunay-based definition of atomic interactions in scoring of proteinâprotein docking results,
J. Mol. Graphics and Modelling 16(2016), 108â??114â??â?? [abstract]
182. 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]
183. 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]
184. 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]
185. 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]
186. T. Baghfalaki, M. Ganjali and D. Berridge,
Missing Value Imputation for RNA-Sequencing Data Using Statistical Models: A Comparative Study,
J. Appl. Statist. (to appear) [abstract]
187. s. Noorian, M. Ganjali and E. Bahrami Samani,
A Bayesian test of homogeneity of association parameter using transition modelling of longitudinal mixed responses,
J. Appl. Statist. 43(2016), 1850-1863 [abstract]
188. M. Akbaripour-Elahabad and J. Zahiri,
rpiCOOL: A tool for In Silico RNA protein interaction detection using random forest,
Journal of Theoretical Biology 402(2016), 1-8 [abstract]
189. M. Bideli. , J. Gittins. and H. Pezeshk,
A Mixed Bayesian/Frequentist Approach to Sample Size Determination Problem for Clinical Trials,
Progress in Biological Sciences 6(2016), 1-9 [abstract]
190. R. Aghdam. , M. Alijanpour. , M. Azadi. , A. Ebrahimi. , C. Eslahchi. and A. Rezvan. ,
Inferring Gene Regulatory Networks by PCA-CMI Using Hill Climbing Algorithm Based on MIT Score and SORDER Method,
Int. J. Biomath. DOI: 10.1142/S1793524516500406(2016), 18 [abstract]
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