Prioritization of genes for translation: a computational approach.

IF 3.8 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Expert Review of Proteomics Pub Date : 2024-04-01 Epub Date: 2024-04-09 DOI:10.1080/14789450.2024.2337004
Simone C da Silva Rosa, Amir Barzegar Behrooz, Sofia Guedes, Rui Vitorino, Saeid Ghavami
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引用次数: 0

Abstract

Introduction: Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation.

Areas covered: In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes.

Expert opinion: Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

翻译基因的优先排序:一种计算方法。
导言:遗传疾病的基因鉴定对于开发新的诊断方法和个性化治疗方案至关重要。确定基因翻译的优先顺序是分子生物学领域的一个重要考虑因素,它能让研究人员专注于最有希望的候选基因,以便开展进一步研究:在本文中,我们讨论了确定基因翻译优先顺序的不同方法,包括计算工具和机器学习算法的使用,以及基因敲除和过表达研究等实验技术。我们还探讨了这些方法的潜在偏差和局限性,并提出了提高基因优先排序方法准确性和可靠性的策略。尽管已经为此开发了许多计算方法,但仍需要结合组织特异性信息的计算方法,以便更准确地确定候选基因的优先顺序。这种方法应能提供组织特异性预测、对潜在疾病机制的深入了解以及更准确的基因优先排序:利用先进的计算工具和机器学习算法来确定基因的优先顺序,我们就能找出治疗复杂疾病的潜在靶点。这是药物开发和个性化医疗的一种新兴方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Expert Review of Proteomics
Expert Review of Proteomics 生物-生化研究方法
CiteScore
7.60
自引率
0.00%
发文量
20
审稿时长
6-12 weeks
期刊介绍: Expert Review of Proteomics (ISSN 1478-9450) seeks to collect together technologies, methods and discoveries from the field of proteomics to advance scientific understanding of the many varied roles protein expression plays in human health and disease. The journal coverage includes, but is not limited to, overviews of specific technological advances in the development of protein arrays, interaction maps, data archives and biological assays, performance of new technologies and prospects for future drug discovery. The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections: Expert Opinion - a personal view on the most effective or promising strategies and a clear perspective of future prospects within a realistic timescale Article highlights - an executive summary cutting to the author''s most critical points.
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