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Brief Review on Bioinformatics

机译:生物信息学简述

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During the last years, the enthusiasm for applying feature selection methods in bioinformatics has get rid of from being a clarifying example to becoming a real precondition for perfect structure. In separate, the high dimensional nature of many modeling tasks in bioinformatics, going from sequence analysis over microarray analysis to spectral analyses and literature mining has given rise to a wealth of feature selection techniques being presented in the field. The most common problems are forming in biological developments at the molecular level and creating inferences from collected data. A bioinformatics solution collect statistics from biological data form various fields. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. Bioinformatics is a fusion of computing, biotechnology and biological.
机译:在过去的几年中,摆脱了将特征选择方法应用于生物信息学的热情,从成为一个清晰的例子成为成为完善结构的真正前提。另外,生物信息学中许多建模任务的高维性质,从序列分析到微阵列分析再到光谱分析和文献挖掘,已引起了该领域大量的特征选择技术。最常见的问题是在分子水平上的生物学发展过程中形成的,并从收集的数据中得出推论。生物信息学解决方案从各个领域的生物数据中收集统计信息。建立一个计算模型。解决计算建模问题。测试和评估计算算法。生物信息学是计算,生物技术和生物学的融合。

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