“Papers of School of Biological Sciences”

 

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  11. S. Vafadar, M. Shahdoust, A. Kalirad, P. Zakeri and M. Sadeghi,
Competitive exclusion during co-infection as a strategy to prevent the spread of a virus: A computational perspective,
Plos One (2021),   [abstract]

DOI: https://doi.org/10.1371/journal.pone.0247200

   12. M. Habibi, G. Taheri and R. Aghdam,
A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing,
Scientific Reports 11(2021), 1-15  [abstract]
DOI: https://doi.org/10.1038/s41598-021-88427-w

   13. A. R. Alizad-Rahvar, S. Vafadar, M. Totonchi and M. Sadeghi,
False Negative Mitigation in Group Testing for COVID-19 Screening,
frontiers in medicine 8(2021), 579  [abstract]
DOI: 10.3389/fmed.2021.661277

   14. 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

   15. 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

   16. 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

   17. 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]

   18. 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

   19. 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

   20. 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

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