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首页> 外文会议>2011 9th IEEE/ACS International Conference on Computer Systems and Applications >AudioGene: Computer-based prediction of genetic factors involved in non-syndromic hearing impairment
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AudioGene: Computer-based prediction of genetic factors involved in non-syndromic hearing impairment

机译：AudioGene：基于计算机的非综合征性听力障碍涉及的遗传因素预测

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摘要

AudioGene is a software system developed at the University of Iowa to classify and predict gene mutations that indicate causal or increased risk factors of disease. We focus on a concise example — the most likely genetic causes of a particular form of inherited hearing loss — ADNSHL. Whereas the cost and throughput involved in the collection of genomic data have advanced dramatically during the past decade, gathering and interpreting clinical information regarding disease diagnosis remains slow, costly and error-prone. AudioGene employs machine-learning techniques in an iterative procedure to prioritize probable genetic risk factors of disease, which are then verified with a molecular (wet lab) assay. In our current implementation AudioGene achieves 67% first-choice accuracy (versus 23% using a majority classifier). When the top three choices are considered, accuracy increases to 83%. This has numerous implications for reducing the cost of genetic screening as well as increasing the power of novel gene discovery efforts. While AudioGene is focused on hearing loss, the design and underlying mechanisms are generalizable to many other diseases including heart disease, cancer and mental illness.
机译：AudioGene是爱荷华大学开发的一种软件系统，用于分类和预测表明疾病的因果关系或风险因素增加的基因突变。我们将重点放在一个简洁的例子上-ADNSHL，这是一种特殊形式的遗传性听力损失的最可能的遗传原因。尽管在过去的十年中，基因组数据的收集所涉及的成本和吞吐量已大大提高，但有关疾病诊断的临床信息的收集和解释仍然缓慢，昂贵且容易出错。 AudioGene在迭代过程中采用了机器学习技术来确定可能的疾病遗传风险因素的优先级，然后通过分子（湿实验室）分析对其进行验证。在我们当前的实现中，AudioGene达到了67％的首选准确度（相比之下，使用多数分类器则为23％）。当考虑到前三个选择时，准确性将提高到83％。这对于降低遗传筛选的成本以及增加新型基因发现工作的力量具有许多意义。虽然AudioGene专注于听力损失，但其设计和潜在机制可推广到许多其他疾病，包括心脏病，癌症和精神疾病。

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