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: 14.

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.

G

Gillman, Rhys, Field, Matt A., Schmitz, Ulf, Karamatic, Rozemary, and Hebbard, Lionel (2023) Identifying cancer driver genes in individual tumours. Computational and Structural Biotechnology Journal, 21. pp. 5028-5038.

Gill, Jaskaran, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Combining kinetic orders for efficient S-System modelling of gene regulatory network. BioSystems, 220. 104736.

Gamage, Hasini Nakulugamuwa, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Ensemble Regression Modelling for Genetic Network Inference. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2022: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 15-17 August 2022, Ottawa, Canada.

Gamage, Hasini Nakulugamuwa, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Filter feature selection based Boolean Modelling for Genetic Network Inference. BioSystems, 221. 104757.

Gill, Jaskaran, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2022) Integrating steady-state and dynamic gene expression data for improving genetic network modelling. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2022: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 15-17 August 2022, Ottawa, Canada.

Gill, Jaskaran, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2021) Dynamically Regulated Initialization for S-system Modelling of Genetic Networks. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2021: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 13-15 October 2021, Melbourne, VIC, Australia.

Gamage, Hasini Nakulugamuwa, Chetty, Madhu, Shatte, Adrian, and Hallinan, Jennifer (2021) An Efficient Boolean Modelling Approach for Genetic Network Inference. In: Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology. From: CIBCB 2021: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 13-15 October 2021, Melbourne, VIC, Australia.

M

Marcoli, Roberta, Symonds, Jane E., Walker, Seumas P., Battershill, Christopher N., and Bird, Steve (2023) Characterising the Physiological Responses of Chinook Salmon (Oncorhynchus tshawytscha) Subjected to Heat and Oxygen Stress. Biology, 12. 1342.

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 Wed Apr 24 22:46:59 2024 AEST.