现在生物信息学的定义已经改变了。它被定义为计算的方法来研究生物学数据的使用（Higgs &阿特伍德，2009）。此外，生物信息学领域也越来越广泛，应用也越来越广泛。近10年来，出现了各种生物信息学的分支学科。除了生物信息学最原始的利用分子生物学外，它还可应用于化学、神经生物学、免疫学、毒理学等领域。事实上，一些新的词汇一样，化学信息学、神经信息学和免疫信息学的出现（Perez Iratxeta，安德拉德纳瓦罗和雷恩，2007）。
As early as the beginning of the 1970s, the term “bioinformatics” has been used by Paulien Hogeweg and Ben Hesper, when it was defined as the research of informatization processes in biosystems (Hogeweg, 2011). Information processing is one of properties of organisms, which includes diverse forms like evolution causing information accumulation, and information interpretation at multiple levels (Hogeweg, 2011). These information processing is a good channel to study living systems.
Now the definition of bioinformatics has been changed. It is defined as the use of computational methods to study biology data (Higgs & Attwood, 2009). In addition, the area of bioinformatics also becomes wider and the application of it has been put into use on multiple fields. In recent 10 years, various bioinformatics sub-disciplines appear. Besides molecular biology which is the most original utilization of bioinformatics, it can be applied to chemistry, neurobiology, immunology, toxicology and so forth. Actually, some new terms like cheminformatics, neuroinformatics and immunoinformatics emerge (Perez-Iratxeta, Andrade-Navarro & Wren, 2007).
Bioinformatics has been applied in various fields and improve clinical including drug virtual screening. However, there are still countless problems. For example, the accuracy of numerous predictions from bioinformatics needs to be tested, which has led to quality assessment standard. Personalized medicines are hardly popularized and the factors influencing the variation are needed to study. In addition, when bioinformatics comes to neurobiology, there are more challenges. For brain is the most complex organ, much more information may contain and need to be integrated. Facing neuro-diseases, therapies that can affect the etiology are always lacking. Therefore, it is essential to study bioinformatics further, and more efforts are needed to apply it to clinical.