The schematic view of the fruit fly optimization algorithm (FOA). by Mohsen Hesami (6917390)

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The results of optimization process via FOA for gene transformation efficiency of chrysanthemum. by Mohsen Hesami (6917390)

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Studies on <i>Agrobacterium</i>-mediated gene transformation of chrysanthemums using <i>GUS</i> gene. by Mohsen Hesami (6917390)

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The results of sensitivity analysis on the developed ensemble model to rank the importance of factors involved in <i>Agrobacterium</i>-mediated gene transformation of chrysanthemum... by Mohsen Hesami (6917390)

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Performance criteria of individual and ensemble models for gene transformation efficiency of chrysanthemum in training, testing, and validation processes. by Mohsen Hesami (6917390)

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Scatter plot of model predicted vs. observed data of chrysanthemum gene transformation efficiency by ensemble model. by Mohsen Hesami (6917390)

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The schematic view of the proposed ensemble model. by Mohsen Hesami (6917390)

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DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP by Liangliang Wang (580395)

“…Tumour mutation burden (TMB) was also analysed in the risk groups. Additionally, gene ontology and gene set variation analysis were used for biological function and pathway exploration. …”

Framework for identifying essential anticancer genes. by Chao-Ting Cheng (15675292)

“…(L) Optimal essential genes are identified on the basis of the decision criterion; otherwise, Steps (F) to (L) are repeated for the subsequent set of candidate genes generated by the NHDE algorithm.…”

Table4_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table3_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table2_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table5_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table1_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Bioinformatics pipeline for circadian function. by Patrick B. Schwartz (14782608)

“…Clock disruption (such as with clock gene knockout) causes suppressed rAMP, and thus rAMP can be considered a strong determinant of clock function (<u>lower left</u>). …”

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph by Guillaume Gautreau (8600556)

“…<div><p>The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</li><li><b>Linear support vector machine (Linear SVM):</b> This machine finds the optimal hyperplane to separate E. coli strains based on genomic features such as gene presence or sequence variations.…”

Table_2_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.…”

Image_3_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.…”

Image_4_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.…”