“Papers of School of Biological Sciences”


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  11. N. Rohani and C. Eslahchi,
Classifying Breast Cancer Molecular Subtypes using Deep Clustering Approach,
Frontiers in Genetics  (to appear) [abstract]

DOI: 10.21203/rs.2.19530/v1

   12. N. Rohani, F. Ahmadi Moughari and C. Eslahchi,
DisCoVering potential candidates of RNAi-based therapy for COVID-19 using computational methods,
PeerJ 10.7717/peerj.10505(2021),   [abstract]
DOI: 10.7717/peerj.10505

   13. 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

   14. 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]

   15. 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

   16. 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

   17. 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

   18. 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

   19. 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

   20. 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

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