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Prioritization of Candidate Genes for Attention Deficit Hyperactivity Disorder by Computational Analysis of Multiple Data Sources [PDF]
Protein and Cell, 2012 Attention deficit hyperactivity disorder (ADHD) is a common, highly heritable psychiatric disorder characterized by hyperactivity, inattention and increased im-pulsivity. In recent years, a large number of genetic studies for ADHD have been published and
Suhua Chang, Jing Wang
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Recent approaches to the prioritization of candidate disease genes
WIREs Systems Biology and Medicine, 2012AbstractMany efforts are still devoted to the discovery of genes involved with specific phenotypes, in particular, diseases. High‐throughput techniques are thus applied frequently to detect dozens or even hundreds of candidate genes. However, the experimental validation of many candidates is often an expensive and time‐consuming task.
Doncheva, N. +2 more
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Prioritization of genes for translation: a computational approach
Expert Review of ProteomicsGene 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.In this paper, we discussed ...
Simone C. da Silva Rosa +4 more
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Conditional Random Field for Candidate Gene Prioritization
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics, 2013Prioritization of novel disease genes is a major challenge in bioinformatics. The large amount of data collected from modern biological experiments makes it difficult for biologists to determine how information on a particular gene relates to a disease or phenotype, whereas performing exhaustive experiments on all possible combinations is impossible ...
Bingqing Xie +3 more
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Gene prioritization through genomic data fusion
Nature Biotechnology, 2006The identification of genes involved in health and disease remains a challenge. We describe a bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena ...
Stein, Aerts +11 more
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Candidate gene prioritization.
Molecular genetics and genomics : MGG, 2012Candidate gene identification is typically labour intensive, involving laboratory experiments required to corroborate or disprove any hypothesis for a nominated candidate gene being considered the causative gene. The traditional approach to reduce the number of candidate genes entails fine-mapping studies using markers and pedigrees.
Ali, Masoudi-Nejad +3 more
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Prioritizing Disease Genes and Understanding Disease Pathways
International Journal of Knowledge Discovery in Bioinformatics, 2009Genetic factors play a major role in the etiology of many human diseases. Genome-wide experimental methods produce an increasing number of genes associated with such diseases. This chapter introduces data sources, bioinformatics tools, and computational methods for prioritizing disease candidate genes and identifying disease pathways. The main strategy
Xiaoyue Zhao +2 more
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A study of gene prioritization algorithms on PPI networks
2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016The undiscovered genes that contribute to a particular disease are of great interest in medical informatics. The candidate pool of such genes from GWAS or similar studies is typically vast. A direct experimental verification all such genes is prohibitively expensive in terms of time and money. In order to limit the number of candidates for experimental
K. P. Sinsha, Bhadrachalam Chitturi
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Gene Prioritization Using a Deep Learning Approach
2018The research of related genes is an extremely important issue in the study of human genes. Scientists could utilize related human genes to build huge, integrated gene regulatory network which enables scientists to discover the relationships between genes and diseases. In this research, we conduct the text mining through Natural Language Processing (NLP)
Feng Liu, Yuting Xiong, Zezhen Wang
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