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How does gene ontology analysis help in understanding the functional roles of genes within biological systems?

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How does gene ontology analysis help in understanding the functional roles of genes within biological systems?

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What are some key databases and tools available for conducting gene ontology analysis?

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What are some key databases and tools available for conducting gene ontology analysis?

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How does gene ontology analysis aid in identifying enriched biological processes, molecular functions, and cellular components within a set of genes?

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How does gene ontology analysis aid in identifying enriched biological processes, molecular functions, and cellular components within a set of genes?

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How can gene ontology analysis be integrated with other omics data, such as transcriptomics, proteomics, and metabolomics, to gain deeper insights into biological systems?

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How can gene ontology analysis be integrated with other omics data, such as transcriptomics, proteomics, and metabolomics, to gain deeper insights into biological systems?

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What are the challenges and potential biases associated with gene ontology analysis, and how can they be addressed?

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What are the challenges and potential biases associated with gene ontology analysis, and how can they be addressed?

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How can gene ontology analysis contribute to the identification of disease-associated genes and pathways?

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How can gene ontology analysis contribute to the identification of disease-associated genes and pathways?

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What strategies can be employed to visualize and interpret gene ontology analysis results effectively?

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What strategies can be employed to visualize and interpret gene ontology analysis results effectively?

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using bioinformatics resources to annotate the genes in terms of molecular functions, biological processes, etc

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using bioinformatics resources to annotate the genes in terms of molecular functions, biological processes, etc

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Integrating GO analysis with omics data, such as gene expression profiles, protein-protein interaction networks, and genetic variation data, can provide a comprehensive understanding of disease-associated genes and pathways

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Integrating GO analysis with omics data, such as gene expression profiles, protein-protein interaction networks, and genetic variation data, can provide a comprehensive understanding of disease-associated genes and pathways

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GO analysis helps understand the functional roles of genes by categorizing them based on molecular functions, biological processes, and cellular components.

GO analysis identifies overrepresented functional categories, links genes to pathways, facilitates comparative genomics, and helps prioritize candidate genes in studies of diseases or biological processes. I

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the webstite gene ontology, iPathwayGuide,

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It helps us understand functional roles of genes by comparing gene in different species? It distinctly annotates the gene across multiple species and forms groups together of the main roles of the genes in the species (most popular annotation) to determine likely/common group function of gene?

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provides knowledge from molecular level to larger pathways from many different organisms

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Gene Ontology website, GOnet, iPathway guide

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DAVID (Database for Annotation, Visualization, and Integrated Discovery)

GOrilla

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The Gene Ontology (GO) project is a major bioinformatics initiative to develop a computational representation of our evolving knowledge of how genes encode biological functions at the molecular, cellular and tissue system levels.

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GO analysis identifies enriched biological processes, molecular functions, and cellular components within a set of genes by giving anotation to each gene. It compare the gene to a reference genome, with the function and locations of the gee set, which help for future study to prioritize gens bases on their functions

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bias with some genes being more extensively studied and annotated than others. 

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bias with some genes being more extensively studied and annotated than others. 

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Bias : Annotation bias, species-specific,functional homogenity assumption.

Challenge : Dynamics shifts in gene function, quality and completenss of the sample, Threshold selection, Heterogenous sample

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by the comparaison of healthy and sick sample

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uses statistical methods such as enrichment analysis, False Discovery Rate (FDR) Correctio to identify significantly enriched or depleted groups of genes within a universe of genes

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whith heatmaps, chart..etc, specific interactive website

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Using heatmap, treemap, network diagrams, pathway analysis, annotation clusters

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Using heatmap, treemap, network diagrams, pathway analysis, annotation clusters

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Performing enrichment analysis or ORA. Cannot analyse using raw data need to compare the actual number of occurrences with the expected number of occurrences for each individual category (annotation). Observe differences between raw vs expected data.

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challenges: annotaion incompleteness - regularly updating GO

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Transcriptomics: used alongside transcriptome profiling to determine biological systems affected due to difference in transcription under certain conditions

Proteomic: can determine function of binding sites i think? like binding domains what it binds to? I know uniprot has a GO annotation section to help identify certain protein domains.

Metabolomics: