Applications of Genomic Technology in Disease Outcome Prediction

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Cellular and Molecular Bioengineering".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 2608

Special Issue Editor


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Guest Editor
1. Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA 6150, Australia
2. Perron Institute for Neurological and Translational Science, Perth, WA 6009, Australia
Interests: genomics; polygenic inheritance; medical genomics; genetic pathology; neurodegenerative diseases; complex diseases
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Special Issue Information

Dear Colleagues,

This Special Issue focuses on the enormous volume of genetic information obtained from technologies that can provide insights into the genetic factors influencing the development and progression of disease.

By analyzing genomic data in conjunction with clinical information, researchers and healthcare professionals can identify the genetic markers associated with specific diseases and their outcomes. These markers may include specific gene mutations, gene expression patterns, or variations in the genome. Studying these markers enables patients who are at risk of developing certain diseases or experiencing poor treatment responses to be identified.

The application of genomic technology in disease outcome prediction has the potential to revolutionize personalized medicine. By employing this approach, physicians can develop targeted treatment plans based on an individual's genetic profile, leading to more effective treatments and improved patient outcomes. Additionally, disease risk prediction can aid in early detection and prevention efforts, as individuals identified as high-risk can undergo regular monitoring or preventative interventions.

However, challenges remain in translating genomic data into clinically actionable information. The interpretation of genomic data requires expertise in bioinformatics, statistical analysis, and clinical medicine. Furthermore, ethical considerations must be taken into account, such as protecting patient privacy and ensuring adequate informed consent.

Continued research in this field holds promise for a future in which the application of genomic technology will enhance the accuracy of disease outcome prediction, leading to personalized, targeted treatments that improve patient care and outcomes.

Prof. Dr. Sulev Koks
Guest Editor

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Keywords

  • genomic technology
  • disease outcome prediction
  • genetic analysis
  • genetic variations
  • genome-wide association studies (GWAS)
  • genetic risk factors
  • biomarkers
  • genetic risk score
  • next-generation sequencing (NGS)
  • rare genetic variants
  • personalized medicine
  • treatment strategies.

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Published Papers (1 paper)

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Review

18 pages, 5759 KiB  
Review
Application and Technical Challenges in Design, Cloning, and Transfer of Large DNA
by Song Bai, Han Luo, Hanze Tong and Yi Wu
Bioengineering 2023, 10(12), 1425; https://doi.org/10.3390/bioengineering10121425 - 15 Dec 2023
Viewed by 2307
Abstract
In the field of synthetic biology, rapid advancements in DNA assembly and editing have made it possible to manipulate large DNA, even entire genomes. These advancements have facilitated the introduction of long metabolic pathways, the creation of large-scale disease models, and the design [...] Read more.
In the field of synthetic biology, rapid advancements in DNA assembly and editing have made it possible to manipulate large DNA, even entire genomes. These advancements have facilitated the introduction of long metabolic pathways, the creation of large-scale disease models, and the design and assembly of synthetic mega-chromosomes. Generally, the introduction of large DNA in host cells encompasses three critical steps: design-cloning-transfer. This review provides a comprehensive overview of the three key steps involved in large DNA transfer to advance the field of synthetic genomics and large DNA engineering. Full article
(This article belongs to the Special Issue Applications of Genomic Technology in Disease Outcome Prediction)
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