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Multi-omics Analysis
Published in Altuna Akalin, Computational Genomics with R, 2020
The recent decades of genomics have uncovered many of the ways in which genes cooperate to perform biological functions in concert. This work has resulted in rich annotations of genes, groups of genes, and the different functions they carry out. Examples of such annotations include the Gene Ontology Consortium’s GO terms (Ashburner et al., 2000, Consortium (2017)), the Reactome pathways database (Fabregat et al., 2018 b), and the Kyoto Encyclopaedia of Genes and Genomes (Kanehisa et al., 2017). These resources, as well as others, publish lists of so-called gene sets, or pathways, which are sets of genes which are known to operate together in some biological function, e.g. protein synthesis, DNA mismatch repair, cellular adhesion, and many other functions. Gene set enrichment analysis is a method which looks for overlaps between genes which we have found to be of interest, e.g. by them being implicated in a certain tumor type, and the a-priori gene sets discussed above.
Process perspective
Published in Olaf Dammann, Etiological Explanations, 2020
According to the Gene Ontology Consortium, a biological process is defined as follows: A biological process is a recognized series of events or molecular functions. A process is a collection of molecular events with a defined beginning and end. Mutant phenotypes often reflect disruptions in biological processes.14A biological process term describes a series of events accomplished by one or more organized assemblies of molecular functions. Examples of broad biological process terms are “cellular physiological process” or “signal transduction.” Examples of more specific terms are “pyrimidine metabolic process” or “alpha-glucoside transport.” The general rule to assist in distinguishing between a biological process and a molecular function is that a process must have more than one distinct step.A biological process is not equivalent to a pathway. At present, the [gene ontology] does not try to represent the dynamics or dependencies that would be required to fully describe a pathway.15
Developing General Models and Theories of Addiction
Published in Hanna Pickard, Serge H. Ahmed, The Routledge Handbook of Philosophy and Science of Addiction, 2019
Robert West, Simon Christmas, Janna Hastings, Susan Michie
The field of biology suffered from a similar problem until the development of what is known as the Gene Ontology (Ashburner et al. 2000). The gene ontology is not just about genes, but is a representational system for the whole of biology, unifying terms, definitions and models across species and research groups in a way that has revolutionised the field (Lewis 2017).
Integrated Analysis of Long Non-Coding RNA -mRNA Profile and Validation in Diabetic Cataract
Published in Current Eye Research, 2022
Xiaoyan Han, Lei Cai, Yumeng Shi, Zhixiang Hua, Yi Lu, Dan Li, Jin Yang
To identify the potential functions of the differentially expressed genes in GO terms and biological pathways, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Gene ontology has the detailed annotation of genes, and classified them into three categories: biological processes (BP), cellular components (CC), and molecular functions (MF). Fisher’s exact test was used to determine whether there was more overlap between the differential expressionlist and the GO annotation list than occasionally expected. The p value indicates the significance of the GO term enrichment in the list of DE genes, and a p value ≤0.05 is considered as significant. KEGG pathway (http://www.genome.jp/kegg/) analysis was performed to cluster the target genes to biological pathways. The p value represents the significance of the conditional-related pathway and the p‐value less than 0.05 represents the significance of the pathway.
A complete proteomic profile of human and bovine milk exosomes by liquid chromatography mass spectrometry
Published in Expert Review of Proteomics, 2021
Kanchan Manohar Vaswani, Hassendrini Peiris, Yong Qin Koh, Rebecca J. Hill, Tracy Harb, Buddhika J. Arachchige, Jayden Logan, Sarah Reed, Peter S. W. Davies, Murray D. Mitchell
However, it is to be noted that there are some limitations to this study. One being the large variation in unique proteins identified (Figure 1) between the two species. This may be explained by 1) the use of separate UniProt databases developed for human and bovine proteomic studies since using the same database is not possible. 2) Fewer bovine proteins compared to human proteins have been identified by Swiss-Prot hence for the analysis we used both Swiss-Prot and TrEMBL for bovine searches. This was done to maximize the number of identified proteins. This percentage of shared/common proteins may be higher if the Bos Taurus database was as well characterized as the Homo Sapiens database. As the reviewed (Swiss-Prot ‘sp’) are lower in the bovine database, we used the TrEmbL database as well, to identify more proteins. From the bovine list, only 135 proteins were detected using Swiss-Prot alone. 3) Functional groups identified may vary depending on the classification tools used. There are several different tools that provide enrichment analysis using Gene Ontology. These tools differ in the algorithms they use, the statistical tests they perform, and the frequency at which the underlying GO data are updated. PANTHER Pathway analysis was used as it is GO endorsed and it is relatively simple to use and categorize proteins into their various subgroups based on function and process etc. hence distribution of proteins is well presented. However, the analyses could be further enhanced using other tools depending on the research question.
Alginate nanogels-based thermosensitive hydrogel to improve antidepressant-like effects of albiflorin via intranasal delivery
Published in Drug Delivery, 2021
Dong Xu, Tao Qiao, Yue Wang, Qiang-Song Wang, Yuan-Lu Cui
Gene Ontology is an international standard classification system for gene function, and differentially expressed genes were classified according to cellular component, molecular function, and biological process. KEGG is also the classic public database of pathways (Fang et al., 2020). The above methods were performed using gene function analysis and pathway analysis in the present study. The distribution of target genes in enriched GO functions in the albiflorin-NGSTH vs. CUMS model is shown in Figure 8(E). KEGG enrichment analysis was performed to screen for a significantly enriched KEGG pathway (Figure 8(F)). From the point of view of biological pathway, the specific pathway was found with significant difference in expression between groups through the enrichment analysis of differential expressed genes. Enrichment analysis of GO and KEGG showed that differentially expressed genes induced by CUMS were involved in the regulation of multiple neural pathways, including cAMP signal pathway, calcium ion signal pathway and cGMP PKG signal pathway. It was reported that cAMP signal pathway, calcium ion signal pathway and cGMP PKG signal pathway were related to the incidence of depression (Armstrong et al., 2009; Bergantin, 2020). Therefore, the results of pharmacodynamics and transcriptomics showed albiflorin-NGSTH had a good antidepressant effect on depressive disorder through the regulation of cAMP signal pathway, calcium ion signal pathway, and cGMP PKG signal pathway.