Chromosome region-specific libraries for human genome analysis

Personalized medicine is a model that aims at customizing healthcare and tailoring medicine according to an individual`s genetic makeup. It classifies individuals that differ in their susceptibility to a particular disease or response to a particular treatment into subpopulations based on individual's unique genetic and clinical information along with environmental factors. The completion of Human Genome Project and the advent of high-throughput genome analysis tools has helped in building and strengthening this model. There lies a huge potential in the implementation of personalized medicine to significantly improve the clinical outcomes; however, its implementation into clinical practice remains slow and is a matter of concern. This chapter aims at acquainting readers with the underlying concepts and components of personalized medicine supplemented with some disease-based case studies, discussing challenges and recent advancements in the implementation of the model of personalized medicine.

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The most common technologies and tools for functional genome analysis

Acta medica Lituanica ◽

10.6001/actamedica.v24i1.3457 ◽

2017 ◽

Vol 24 (1) ◽

pp. 1-11 ◽

Cited By ~ 10

Author(s):

Evelina Gasperskaja ◽

Vaidutis Kučinskas

Keyword(s):

Functional Analysis ◽

Human Genome ◽

Genome Analysis ◽

Bioinformatic Analysis ◽

Genome Wide ◽

Polymerase Chain ◽

Scientific Results ◽

The Right ◽

Generation Sequencing ◽

Functional Genome

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

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