存在哪些生物信息学子领域？

 

DNA测序最初的价值是用来揭示细胞的DNA含量。然而，可能令许多人感到惊讶的是，生物信息学未来的最重大希望可能在于其他应用上。一般而言，大多数生物信息学问题属于以下四类之一：

1.分类：确定生物群的物种组成

2.装配：确定基因组的核苷酸组成

3.重测序：确定基因组中的突变和变异

4.定量：使用DNA测序来测量细胞的功能特征

DNA sequencing as initially valued for revealing the DNA content of a cell. It may come as a surprise to many, however, that the most significant promise for the future of bioinformatics might lie in other applications. In general, most bioinformatics problems fall under one of four categories:

1. Classification: determining the species composition of a population of organisms

2. Assembly: establishing the nucleotide composition of genomes

3. Resequencing: identifying mutations and variations in genomes

4. Quantification: using DNA sequencing to measure the functional characteristics of a cell

 

人类基因组计划在装配类别中大跌眼镜。自完成以来，科学家们已经组装了数千种其他物种的基因组。但是，数百万个物种的基因组仍然完全未知。

The Human Genome Project fell squarely in the assembly category. Since its completion, scientists have assembled the genomes of thousands of others species. The genomes of many millions of species, however, remain entirely unknown.

 

试图识别相对于已知基因组的变化的研究属于重测序研究领域。 DNA突变和变异可能会导致表型变化，例如新出现的疾病，适应性变化，不同的生存率等。例如，正在进行一些工作来编译人类基因组中存在的所有变体-这些工作将属于重测序类别。由于生物信息学家的工作，正在进行大量的计算工作，以从通过重新测序获得的知识中产生具有临床价值的信息。

Studies that attempt to identify changes relative to known genomes fall into the resequencing field of study. DNA mutations and variants may cause phenotypic changes like emerging diseases, changing fitness, different survival rates, and many others. For example, there are several ongoing efforts to compile all variants present in the human genome—-these efforts would fall into the resequencing category. Thanks to the work of bioinformaticians, massive computing efforts are underway to produce clinically valuable information from the knowledge gained through resequencing.

 

活着的微生物围绕着我们，我们与它们共存于复杂的集体中，这些集体只有维持相互依存的和谐才能生存。通过其遗传材料对这些最不知名的微生物物种进行分类是生物信息学的一个快速发展的子领域。

Living micro-organisms surround us, and we coexist with them in complex collectives that can only survive by maintaining interdependent harmony. Classifying these mostly-unknown species of micro-organisms by their genetic material is a fast-growing subfield of bioinformatics.

 

最后，也许是最出乎意料的是，生物信息学方法可以通过量化帮助我们更好地理解生物学过程，例如基因表达。在这些协议中，测序程序用于确定与其他生物过程相关的各种DNA片段的相对丰度。

Finally, and perhaps most unexpectedly, bioinformatics methods can help us better understand biological processes, like gene expressions, through quantification. In these protocols, the sequencing procedures are used to determine the relative abundances of various DNA fragments that were made to correlate with other biological processes.

 

几十年来，生物学家已经成为操纵DNA的专家，现在能够选择许多自然发生的分子过程来复制，翻译和复制DNA分子，并将这些作用与生物学过程联系起来。测序为这个世界打开了一个新窗口，不断发现新的方法和序列操作。各种方法通常称为Something-Seq，例如RNA-Seq，Chip-Seq，RAD-Seq，以反映捕获/连接到测序的机制。例如，RNA-Seq通过逆转录将其变成DNA，从而揭示了RNA的丰富性。对该构建体进行测序允许同时测量细胞所有基因的表达水平。例如RAD-Seq使用限制酶在特定位置切割DNA，然后仅对这些位置周围的片段进行测序。这种方法在这些位点周围产生很高的覆盖率，因此适用于群体遗传学研究。

Over the decades biologists have become experts at manipulating DNA and are now able to co-opt the many naturally-occurring molecular processes to copy, translate, and reproduce DNA molecules and connect these actions to biological processes. Sequencing has opened a new window into this world, new methods and sequence manipulations are continuously discovered. The various methods are typically named as Something-Seq for example RNA-Seq, Chip-Seq, RAD-Seq to reflect what mechanism was captured/connected to sequencing. For example, RNA-Seq reveals the abundance of RNA by turning it into DNA via reverse transcription. Sequencing this construct allows for simultaneously measuring the expression levels of all genes of a cell. The for example RAD-Seq uses restriction enzymes to cleave DNA at specific locations and only the fragments around these locations are then sequenced. This method produces very high coverage around these sites, thus is suited for population genetics studies.

 

FROM https://www.biostars.org/