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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Biochemical cascade | 8/9 | https://en.wikipedia.org/wiki/Biochemical_cascade | reference | science, encyclopedia | 2026-05-05T10:46:07.942614+00:00 | kb-cron |
== Pathway-oriented approaches == In the post-genomic age, high-throughput sequencing and gene/protein profiling techniques have transformed biological research by enabling comprehensive monitoring of a biological system, yielding a list of differentially expressed genes or proteins, which is useful in identifying genes that may have roles in a given phenomenon or phenotype. With DNA microarrays and genome-wide gene engineering, it is possible to screen global gene expression profiles to contribute a wealth of genomic data to the public domain. With RNA interference, it is possible to distill the inferences contained in the experimental literature and primary databases into knowledge bases that consist of annotated representations of biological pathways. In this case, individual genes and proteins are known to be involved in biological processes, components, or structures, as well as how and where gene products interact with each other. Pathway-oriented approaches for analyzing microarray data, by grouping long lists of individual genes, proteins, and/or other biological molecules according to the pathways they are involved in into smaller sets of related genes or proteins, which reduces the complexity, have proven useful for connecting genomic data to specific biological processes and systems. Identifying active pathways that differ between two conditions can have more explanatory power than a simple list of different genes or proteins. In addition, a large number of pathway analytic methods exploit pathway knowledge in public repositories such as Gene Ontology (GO) or Kyoto Encyclopedia of Genes and Genomes (KEGG), rather than inferring pathways from molecular measurements. Furthermore, different research focuses have given the word "pathway" different meanings. For example, 'pathway' can denote a metabolic pathway involving a sequence of enzyme-catalyzed reactions of small molecules, or a signaling pathway involving a set of protein phosphorylation reactions and gene regulation events. Therefore, the term "pathway analysis" has a very broad application. For instance, it can refer to the analysis physical interaction networks (e.g., protein–protein interactions), kinetic simulation of pathways, and steady-state pathway analysis (e.g., flux-balance analysis), as well as its usage in the inference of pathways from expression and sequence data. Several functional enrichment analysis tools and algorithms have been developed to enhance data interpretation. The existing knowledge base–driven pathway analysis methods in each generation have been summarized in recent literature.
== Applications of pathway analysis in medicine ==
=== Colorectal cancer (CRC) === A program package MatchMiner was used to scan HUGO names for cloned genes of interest are scanned, then are input into GoMiner, which leveraged the GO to identify the biological processes, functions and components represented in the gene profile. Also, Database for Annotation, Visualization, and Integrated Discovery (DAVID) and KEGG database can be used for the analysis of microarray expression data and the analysis of each GO biological process (P), cellular component (C), and molecular function (F) ontology. In addition, DAVID tools can be used to analyze the roles of genes in metabolic pathways and show the biological relationships between genes or gene-products and may represent metabolic pathways. These two databases also provide bioinformatics tools online to combine specific biochemical information on a certain organism and facilitate the interpretation of biological meanings for experimental data. By using a combined approach of Microarray-Bioinformatic technologies, a potential metabolic mechanism contributing to colorectal cancer (CRC) has been demonstrated Several environmental factors may be involved in a series of points along the genetic pathway to CRC. These include genes associated with bile acid metabolism, glycolysis metabolism and fatty acid metabolism pathways, supporting a hypothesis that some metabolic alternations observed in colon carcinoma may occur in the development of CRC.
=== Parkinson's disease (PD) === Cellular models are instrumental in dissecting a complex pathological process into simpler molecular events. Parkinson's disease (PD) is multifactorial and clinically heterogeneous; the aetiology of the sporadic (and most common) form is still unclear and only a few molecular mechanisms have been clarified so far in the neurodegenerative cascade. In such a multifaceted picture, it is particularly important to identify experimental models that simplify the study of the different networks of proteins and genes involved. Cellular models that reproduce some of the features of the neurons that degenerate in PD have contributed to many advances in our comprehension of the pathogenic flow of the disease. In particular, the pivotal biochemical pathways (i.e. apoptosis and oxidative stress, mitochondrial impairment and dysfunctional mitophagy, unfolded protein stress and improper removal of misfolded proteins) have been widely explored in cell lines, challenged with toxic insults or genetically modified. The central role of a-synuclein has generated many models aiming to elucidate its contribution to the dysregulation of various cellular processes. Classical cellular models appear to be the correct choice for preliminary studies on the molecular action of new drugs or potential toxins and for understanding the role of single genetic factors. Moreover, the availability of novel cellular systems, such as cybrids or induced pluripotent stem cells, offers the chance to exploit the advantages of an in vitro investigation, although mirroring more closely the cell population being affected.