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Computational Biology for Clinical Research
Published in Rishabha Malviya, Pramod Kumar Sharma, Sonali Sundram, Rajesh Kumar Dhanaraj, Balamurugan Balusamy, Bioinformatics Tools and Big Data Analytics for Patient Care, 2023
Rakhi Mishra, Rupa Mazumder, Prem Shankar Mishra
The following software is used in the field of computational biology for undertaking clinical, cellular, and molecular work [1,13,31]:PLOS Computational Biology Software;Nature Computational Biology Tools;Institute for Systems Biology List of Open-Source Computational Biology Software.This software helps to give information on the progression of a disease; a clinician can also link specific patient characteristic patterns to the biology of a target through this software [3]. For the development of personalized medicines, linking patient body physiology with distinct phenotypes is an essential task for providing specific treatment [32]. The software used for computational biology successfully performs two functions [33]. Firstly, to identify and analyze measurable biochemical data of the patient related to the patient’s prevention, diagnosis, and treatment—known as “GOLD STANDARD PARAMETERS” [4,23].
Personalized Medicine and a Data Revolution
Published in Ahmed Elngar, Ambika Pawar, Prathamesh Churi, Data Protection and Privacy in Healthcare, 2021
Subhajit Basu, Adekemi Omotubora
Genomics, as it is argued, enables the tailoring of treatments to the genomic basis of each individual’s disease-pharmacogenomics [14]. Personalized medicine recognizes that complex diseases should no longer be considered as a single entity [15]; instead “it seeks to focus on ‘causes of cases’ and to target more specifically the biological pathways to disease in individuals” [16]. In 2015, the European Commission defined personalized medicine as:A medical model using the characterisation of individuals’ phenotypes and genotypes (e.g. molecular profiling, medical imaging, lifestyle data) for tailoring the right therapeutic strategy for the right person at the right time, and/or to determine the predisposition to disease and/or to deliver timely and targeted prevention. Personalised medicine relates to the broader concept of patient-centred care, which considers that, in general, healthcare systems need to better respond to patient needs.[17]
Robustness and evolvability of biological systems
Published in Karthik Raman, An Introduction to Computational Systems Biology, 2021
While the genotype denotes the genetic makeup, the phenotype refers to higher-level observable characteristics or traits of an organism. At the molecular level, features such as protein structures, RNA structures or folds can be regarded as molecular phenotypes. At a higher level of organisation, namely the network level, more complex phenotypes can be considered. Table 13.1 lists some examples of genotype–phenotype mapping from RNA to metabolic networks to artificial human-made systems such as digital circuits. Once we determine the mapping between genotype and phenotype—this could be via an experiment, or theoretically, via computation—we can unravel the various genotype networks that span the genotype space. Figure 13.2b shows phenotypes mapped on to genotypes using a variety of colours. Evidently, the genotype space is laced with numerous genotype networks, of different sizes and connectivities.
Transhumanist Genetic Enhancement: Creation of a ‘New Man’ Through Technological Innovation
Published in The New Bioethics, 2021
To correlate genes with traits, there are other fundamental problems. The expressivity of a genotype is the degree to which its phenotype can differ between individuals (Miko 2008a). Even for characteristics that are controlled by a single gene, it is possible for individuals with the same genotype to have different phenotypes. In the case of a genetic disorder, people with the same disease genotype may have stronger or weaker forms of the disorder, and some may never develop the disorder at all. Penetrance is the frequency of occurrence of a particular trait or condition amongst individuals who carry the same gene variant (Miko 2008a). Thus, in a group of people with a disease-causing genotype, some might develop a severe form of the disorder, while others might have a milder form. In incomplete penetrance, individuals with a certain genotype may or may not develop a phenotype associated with it.