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61.	S. H. Mahmoodi, R. Aghdam and C. Eslahchi, An order independent algorithm for inferring gene regulatory network using quantile value for conditional independence tests, Scientific Reports 11(2021), 1-15 [abstract] DOI: https://doi.org/10.1038/s41598-021-87074-5

62.	A. Emdadi and C. Eslahchi, Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model, BMC Bioinformatics (2021), 1-22 [abstract]

63.	F. Mohseni-Salehi, F. Zare-Mirakabad, M. Sadeghi and S. Ghafouri-Fard, A Stochastic Model of DNA Double-Strand Breaks Repair Throughout the Cell Cycle, Bulletin of Mathematical Biology 82(2021), 1-36 [abstract] DOI: https://doi.org/10.1007/s11538-019-00692-z

64.	S. salmanian, H. Pezeshk and M. Sadeghi, Inter protein residue covariation information unravels physically interacting protein dimers, BMC Bioinformatics 21(2020), 1-21 https://doi.org/10.1186/s12859-020-03930-7 [abstract] DOI: https://doi.org/10.1186/s12859-020-03930-7

65.	M. Ghamghami, N. Ghahreman, P. Irannejad and H. Pezeshk, A parametric empirical Bayes (PEB) approach for estimating maize progress percentage at field scale, Agricultural and Forest Meteorology 281(2020), https://doi.org/10.1016/j.agrformet.2019.107829 [abstract] DOI: https://doi.org/10.1016/j.agrformet.2019.107829

66.	H. Poormohammadi and M. Sardari Zarchi, Netcombin: An algorithm for constructing optimal phylogenetic network from rooted triplets, Plos One 15(2020), https://doi.org/10.1371/journal.pone.0227842 [abstract] DOI: https://doi.org/10.1371/journal.pone.0227842

67.	A. Emdadi and Ch. Eslahchi, DSPLMF: A Method for Cancer Drug Sensitivity Prediction Using a Novel Regularization Approach in Logistic Matrix Factorization, Frontiers in Genetics 11(2020), 75 [abstract] DOI: https://doi.org/10.3389/fgene.2020.00075

68.	F. Ahmadi Moughari and Ch. Eslahchi, ADRML: anticancer drug response prediction using manifold learning, Scientific Reports 10(2020), 1-18 [abstract] DOI: https://doi.org/10.1038/s41598-020-71257-7

69.	S. A. Malekpour, A. R. Alizad-Rahvar and M. Sadeghi, LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks, BMC Bioinformatics 21(2020), 1-21 [abstract] DOI: https://doi.org/10.1186/s12859-020-03651-x

70.	LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks, BMC Bioinformatics 21(2020), 1-21 [abstract] DOI: https://doi.org/10.1186/s12859-020-03651-x

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