Items where Subject is "31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310202 Biological network analysis"

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Number of items at this level: 6.

D

Dinh, Xuyen T., Stanley, Dragana, Smith, Letitia D., Moreau, Morgane, Berzins, Stuart P., Gemiarto, Adrian, Baxter, Alan G., and Jordan, Margaret A. (2021) Modulation of TCR signalling components occurs prior to positive selection and lineage commitment in iNKT cells. Scientific Reports, 11. 23650.

S

Sadeghi, Mehdi, Karimi, Mohammad Reza, Karim, Amir Hossein, Farshbaf, Nafiseh Ghorbanpour, Barzegar, Abolfazl, and Schmitz, Ulf (2023) Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors. Genes, 14 (750).

Sadeghi, Mehdi, Ranjbar, Bijan, Ganjalikhany, Mohamad Reza, Khan, Faiz M., Schmitz, Ulf, Wolkenhauer, Olaf, and Gupta, Shailendra K. (2016) MicroRNA and transcription factor gene regulatory network analysis reveals key regulatory elements associated with prostate cancer progression. PLoS ONE, 11 (12). e0168760.

W

Wu, Siyuan, Cui, Tiangang, Zhang, Xinan, and Tian, Tianhai (2020) A non-linear reverse-engineering method for inferring genetic regulatory networks. PeerJ, 8. e9065.

Wu, Siyuan, Cui, Tiangang, and Tian, Tianhai (2019) Mathematical Modelling of Genetic Network for Regulating the Fate Determination of Hematopoietic Stem Cells. In: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine. pp. 2167-2173. From: BIBM 2018: IEEE International Conference on Bioinformatics and Biomedicine, 3-6 December 2018, Madrid, Spain.

Waardenberg, Ashley J., Homan, Bernou, Mohamed, Stephanie, Harvey, Richard P., and Bouveret, Romaric (2016) Prediction and validation of protein–protein interactors from genome-wide DNA-binding data using a knowledge-based machine-learning approach. Open Biology, 6. 160183.

This list was generated on Mon Mar 27 23:01:17 2023 AEST.