Dr Uzma Uzma
- Research Associate (Infrastructure & Environment)
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Gupta, R., Hajabdollahi Ouderji, Z., Uzma, , Yu, Z. , Sloan, W. T. and You, S. (2024) Machine learning for sustainable organic waste treatment: a critical review. npj Materials Sustainability, 2, 5. (doi: 10.1038/s44296-024-00009-9)
Ameer, A., Cheng, Y., Saleem, F., Uzma, , McKenna, A., Richmond, A., Gundogdu, O., Sloan, W. T. , Javed, S. and Ijaz, U. Z. (2023) Temporal stability and community assembly mechanisms in healthy broiler cecum. Frontiers in Microbiology, 14, 1197838. (doi: 10.3389/fmicb.2023.1197838) (PMID:37779716) (PMCID:PMC10534011)
Uzma, , Manzoor, U. and Halim, Z. (2023) Protein encoder: an autoencoder-based ensemble feature selection scheme to predict protein secondary structure. Expert Systems with Applications, 213(Part B), 119081. (doi: 10.1016/j.eswa.2022.119081)
Uzma, , Al-Obeidat, F., Tubaishat, A., Shah, B. and Halim, Z. (2022) Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data. Neural Computing and Applications, 34(11), pp. 8309-8331. (doi: 10.1007/s00521-020-05101-4)
Uzma, and Halim, Z. (2021) An ensemble filter-based heuristic approach for cancerous gene expression classification. Knowledge-Based Systems, 234, 107560. (doi: 10.1016/j.knosys.2021.107560)
Halim, Z., Sargana, H. M., Aadam, , Uzma, and Waqas, M. (2021) Clustering of graphs using pseudo-guided random walk. Journal of Computational Science, 51, 101281. (doi: 10.1016/j.jocs.2020.101281)
Uzma, and Halim, Z. (2020) Optimizing the DNA fragment assembly using metaheuristic-based overlap layout consensus approach. Applied Soft Computing, 92, 106256. (doi: 10.1016/j.asoc.2020.106256)
Halim, Z. and Uzma, (2018) Optimizing the minimum spanning tree-based extracted clusters using evolution strategy. Cluster Computing, 21(1), pp. 377-391. (doi: 10.1007/s10586-017-0868-6)
Gupta, R., Hajabdollahi Ouderji, Z., Uzma, , Yu, Z. , Sloan, W. T. and You, S. (2024) Machine learning for sustainable organic waste treatment: a critical review. npj Materials Sustainability, 2, 5. (doi: 10.1038/s44296-024-00009-9)
Ameer, A., Cheng, Y., Saleem, F., Uzma, , McKenna, A., Richmond, A., Gundogdu, O., Sloan, W. T. , Javed, S. and Ijaz, U. Z. (2023) Temporal stability and community assembly mechanisms in healthy broiler cecum. Frontiers in Microbiology, 14, 1197838. (doi: 10.3389/fmicb.2023.1197838) (PMID:37779716) (PMCID:PMC10534011)
Uzma, , Manzoor, U. and Halim, Z. (2023) Protein encoder: an autoencoder-based ensemble feature selection scheme to predict protein secondary structure. Expert Systems with Applications, 213(Part B), 119081. (doi: 10.1016/j.eswa.2022.119081)
Uzma, , Al-Obeidat, F., Tubaishat, A., Shah, B. and Halim, Z. (2022) Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data. Neural Computing and Applications, 34(11), pp. 8309-8331. (doi: 10.1007/s00521-020-05101-4)
Uzma, and Halim, Z. (2021) An ensemble filter-based heuristic approach for cancerous gene expression classification. Knowledge-Based Systems, 234, 107560. (doi: 10.1016/j.knosys.2021.107560)
Halim, Z., Sargana, H. M., Aadam, , Uzma, and Waqas, M. (2021) Clustering of graphs using pseudo-guided random walk. Journal of Computational Science, 51, 101281. (doi: 10.1016/j.jocs.2020.101281)
Uzma, and Halim, Z. (2020) Optimizing the DNA fragment assembly using metaheuristic-based overlap layout consensus approach. Applied Soft Computing, 92, 106256. (doi: 10.1016/j.asoc.2020.106256)
Halim, Z. and Uzma, (2018) Optimizing the minimum spanning tree-based extracted clusters using evolution strategy. Cluster Computing, 21(1), pp. 377-391. (doi: 10.1007/s10586-017-0868-6)