Proteins encoded by genes are engaged in most of the processes within a cell. Typing a minimal set of genes required for survival is still a challenging task. Essential genes seem to be more conservative and are usually responsible for basic functions, for instance, genetic information flow or energy production. Despite persistent advances in experimental methods, computer predictions may constitute an important part of this investigation. Firstly, they may embrace a huge amount of data and provide some characteristic patterns. Furthermore, they enable scientists to build models for predicting essential genes which are not yet verified experimentally. Some papers indicate interesting dependencies within essential genes sequences using different computer models. In this paper, an author took a three-step analysis for a deeper understanding of the fundamentals of essential and non-essential genes. Beginning from a simple nucleotide composition and finishing at long-range correlations, presents some characteristic patterns that are expected to be developed in future studies.

由基因编码的蛋白质参与细胞内的大部分过程。输入生存所需的最少基因集仍然是一项具有挑战性的任务。必需基因似乎更为保守，通常负责基本功能，例如遗传信息流或能量生产。尽管实验方法不断取得进步，但计算机预测可能构成这项调查的重要组成部分。首先，它们可能包含大量数据并提供一些特征模式。此外，它们使科学家能够建立模型来预测尚未通过实验验证的必需基因。一些论文使用不同的计算机模型指出了必需基因序列中有趣的依赖性。在本文中，为了更深入地了解必需基因和非必需基因的基本原理，作者进行了三步分析。从简单的核苷酸组成开始到长程相关性结束，呈现了一些有望在未来研究中开发的特征模式。