1. INTRODUCTION
Incorporation of prior pathway knowledge into microarray data has become a popular research area in bioinformatics. Ever since the advent of microarray technology in the field of biomedical research, it led to the development of numerous analytic methods to analyse gene expression data from microarray. However, most of the methods are single gene based which unable to detect subtle but coordinated differentially expressed genes and these genes often dropped during feature selection by strict cut-off threshold [1,2]. In contrast, pathway-based microarray analysis consider a set of biologically related genes and help to detect these subtle changes in gene expression. Many discussion has been done by researchers regard pathway-based analysis such as reviews done regarding computational approaches proposed for pathway-based analysis by Curtis et al. [3] and also Misman et al. [4], enrichment-approach using various Kolmogorov-Smirnov by Subramanian et al. [5], random forest-based pathway analysis by Pang et al. [6], and Harris et al. [7] who proposed gene grouping based on gene ontology.
A biological pathway is a series of action among molecules in a cell that triggers the production of new molecules such as fat or proteins or spur a cell to move as well as generate signal that able to turn genes on and off. This is very important to researchers as they can detect the problem or details regarding a particular disease by identifying genes, proteins and other
Introduction: Cellular respiration and fermentation are used in cells to generate ATP. All cells in a living organism require energy or ATP to perform cellular tasks (Urry, Lisa A., et al. , pg. 162). Since energy can not be created (The first law of thermodynamics) just transformed, the cell must get its energy from an outside source (Urry, Lisa A., et al. , pg.162). “Totality of an organism’s chemical reactions is called metabolism” (Urry, Lisa A., et al., pg. 142). Cells get this energy through metabolic pathways, or metabolism. As it says in Campbell biology, “Metabolic pathways that release stored energy by breaking down complex molecules are called catabolic pathways” (Urry, Lisa A., et al. pg.
Biological science is related to psychology, which studies the activities of all living beings and deals with people thoughts & feelings. Biological psychology is the scientific study of the links between biological and psychological processes.
3. Cells use enzymes as biological catalysts to increase or accelerate the rate of reactions, such as those in photosynthesis or glycolysis. This allows reactions to occur under conditions that sustain life.
Enzymes are a key aspect in our everyday life and are a key to sustaining life. They are biological catalysts that help speed up the rate of reactions. They do this by lowering the activation energy of chemical reactions (Biology Department, 2011).
There are thousands of chemical reactions that occur in a cell at every moment. These chemical reactions do not occur randomly, they are highly under the control of biological catalysts called enzymes. Most of these enzymes are proteins. These proteins have certain primary structures directed by
One key role that proteins have in biology, is their roles as enzymes. Enzymes are natural catalysts that bring about certain hydrolysis and condensation reactions in the body, and they are in fact proteins. Enzymes are 3D proteins that have an active site, which is complementary to a specific substrate,
Life on earth would not be possible without enzymes. Enzymes are proteins whose primary function is to act as catalysts in metabolic pathways by binding to specific molecules, called substrates in this context, at their active site. They are defined by two distinctive characteristics, the first being their ability to increase the rate of a reaction without being used up or modified by the reaction
1A. What is your chosen innovation and its intended purpose (i.e. the problem it solved, the opportunities it created, etc.)?
5. For pathway analysis the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resource v6.7 (Huang da, Sherman et al. 2009), can be used to generate a functional annotation chart, using a term-centric singular enrichment analysis so that the protein profiles can be investigated. More sophisticated programs such as ingenuity or metacore can also be used to probe specific pathways. However a subscription is needed, whereas DAVID is freely availalbe
According to the Merriam-Webster dictionary (“Physiology,” n.d.), physiology is defined as a branch of biology that deals with the functions and activities of life or of living matter and of the physical and chemical phenomena observed. Compared to physiology, pathophysiology is a much more specific section of physiology that deals specifically with the functional changes that accompany a particular syndrome or disease (“Pathophysiology,” n.d.). Braun and Anderson (2011) discuss that
A Metabolic pathway is a series of chemical reactions in which the product of one reaction becomes the substrate for the next reaction. (Nature.com, 2010). Chemical reactions in metabolic pathways rarely take place spontaneously. Each reaction step is catalysed, by an enzyme. Enzymes are important for catalysing all types of biological reactions: those that require energy as well as those that release energy. (Metabolic Pathways, 2016)
The biological standpoint gives an inside look as to what mechanisms are going on inside the body to cause a person’s behavior. This aspect is defined as, “Major explanatory focus is how the
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These four biomolecules are metabolized by the animal body. Each biomolecule is broken down in a different process. The end result of each process is the creation of usable energy for the body. This energy is used to work and generate other chemical reactions that help the body move and think. Carbohydrates, lipids, proteins and nucleic acids each provide energy to different places within the body that, in turn, stimulate other chemical reactions to occur, creating a chain reaction of chemical reactions throughout the body. The metabolization of these major
Over the last decade, advent of high throughput sequencing technologies has enabled data collection at a scale that is essential to understand the complexities of GRN’s that underpin every cellular function. Following closely with the progress of these technologies, researchers have come up with various computational methods and tools to infer GRN from time-series gene expression data. Some of the most popular methods are Boolean networks, Bayesian Networks, Recurrent neural networks, S-systems, Regression based methods, Clustering methods, Information theory based approach, Maximal information coefficient based approach, Ordinary Differential Equation based approach.