ChatGPT, a recently developed product by openAI, is successfully leaving its
mark as a multi-purpose natural language based chatbot. In this paper, we are
more interested in analyzing its potential in the field of computational
biology. A major share of work done by computational biologists these days
involve coding up Bioinformatics algorithms, analyzing data, creating
pipelining scripts and even machine learning modeling & feature extraction.
This paper focuses on the potential influence (both positive and negative) of
ChatGPT in the mentioned aspects with illustrative examples from different
perspectives. Compared to other fields of Computer Science, Computational
Biology has - (1) less coding resources, (2) more sensitivity and bias issues
(deals with medical data) and (3) more necessity of coding assistance (people
from diverse background come to this field). Keeping such issues in mind, we
cover use cases such as code writing, reviewing, debugging, converting,
refactoring and pipelining using ChatGPT from the perspective of computational
biologists in this paper.

在本文中，我们着重分析了 ChatGPT 在计算生物学领域的潜力，讨论了它对 Bioinformatics 算法编写、数据分析、脚本编排以及机器学习建模和特征提取等方面的积极和消极影响，并给出了来自不同视角的具体示例。