Duman, E.T., Tuna, G., Ak,E., Avsar, G & Pir, P (2024). Optimized network based natural language processing approach to reveal disease comorbidities in COVID-19.) Sci Rep 14, 2325
Avşar, G. & Pir, P. (2023) An integrated study to decipher immunosuppressive cellular communication in the PDAC environment. NPJ Systems Biology and Applications 9, 1-13
https://doi.org/10.1038/s41540-023-00320-6
Karakurt, H. U., & Pir, P. (2023) “SUMA: A Lightweight Machine Learning Model Powered Shared Nearest Neighbour Based Clustering Application Interface of scRNA-Seq,” Turkish Journal of Biology: Vol. 47: No. 6, Article 8.
Karakurt, H. U., & Pir, P. (2023) “Machine learning based bioinformatics analysis of intron usage alterations and metabolic regulation in adipose browning” Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 31: No. 7, Article 11.
Avşar, G. & Pir, P. (2023) A comparative performance evaluation of imputation methods in spatially resolved transcriptomics data. Molecular Omics 19 (2), 162-173
Cesur, M.F., Çakır, T., Pir, P. (2022) Genome-Wide Analysis of Yeast Metabolic Cycle through Metabolic Network Models Reveals Superiority of Integrated ATAC-seq Data over RNA-seq Data. Msystems 7 (3)
Karakurt, H.U. & Pir, P. (2022) In silico analysis of metabolic effects of bipolar disorder on prefrontal cortex identified altered GABA, glutamate-glutamine cycle, energy metabolism and amino acid synthesis pathways. Integrative Biology, Volume 14, Issue 6, June 2022, Pages 127–136. https://doi.org/10.1093/intbio/zyac012
Boccaletto, P., Stefaniak, F., Ray, A., Cappannini, A., Mukherjee, S, Purta, E., Kurkowska, M., Shirvanizadeh, N., Destefanis, E., Groza, P., Avşar, G., Romitelli, A., Pir, P., Dassi, E., Conticello, S. G., Aguilo, F., Bujnicki, J. M., (2022) “MODOMICS: a database of RNA modification pathways. 2021 update.”, Nucleic Acids Research, Volume 50, Issue D1, 7 January 2022, Pages D231–D235. https://doi.org/10.1093/nar/gkab1083
Uzuner, D., Akkoç, Y., Peker, N., Pir, P., Gözüaçık, D., Çakır, T., (2021) Transcriptional landscape of cellular networks reveal interactions driving the dormancy mechanisms in cancer Scientific Reports 11 (1), 15806 https://doi.org/10.1038/s41598-021-94005-x
Destefanis, E., Avşar, G., Groza, P., Romitelli, A., Torrini, S., Pir, P., Conticello S. G., Aguilo F., & Dassi, E. (2020). A mark of disease: how mRNA modifications shape genetic and acquired pathologies. RNA.
https://doi.org/10.1261/rna.077271.120
Çakır, B., Prete, M., Huang, N., Van Dongen, S., Pir, P., & Kiselev, V. Y. (2020). Comparison of visualisation tools for single-cell RNAseq data. NAR Genomics and Bioinformatics.
https://doi.org/10.1093/nargab/lqaa052
Ak, E., & Pir, P. (2020). Transcriptional response of signalling pathways to SARS-CoV-2 infection in normal human bronchial epithelial cells. bioRxiv.
https://doi.org/10.1101/2020.06.20.163006
Karakurt, H.U., Pir, P. (2020). Integration of transcriptomic profile of SARS-CoV-2 infected normal human bronchial epithelial cells with metabolic and protein-protein interaction networks. Turkish Journal of Biology.
https://doi.org/10.3906/biy-2005-115
Çakır, T., Kökrek, E., Avşar, G., Abdik, E., & Pir, P. (2019). Next-Generation Genome-Scale Models Incorporating Multilevel ‘Omics Data: From Yeast to Human. In Yeast Systems Biology (pp. 347-363). Humana, New York, NY.
https://doi.org/10.1007/978-1-4939-9736-7_20
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