ChatGPT, a powerful language model and its potential uses in bioinformatics

This review investigates the future potential of ChatGPT, a transformer-based large language model (LLM), in bioinformatics applications such as text mining, protein sequence analysis, drug development, and clinical decision-making. Several research has demonstrated the success of ChatGPT in various domains, and its adaptability and versatility make it a valuable tool in the bioinformatics toolbox. ChatGPT's ability to learn and adapt to new data and tasks sets it apart from existing approaches, and its use has the potential to revolutionize how researchers analyze and interpret biological data. ChatGPT, has major applications in scientific literature review and text mining. Research has shown that pre-training GPT like models with biological text has improved the accuracy and reliability of such models when dealing with biological data. Additionally, ChatGPT shows a lot of promise in bioinformatics and has the potential to help a lot of people, due to its ubiquitousness and ease of handling. Major limitations and drawbacks of using ChatGPT involve its inability to handle complex biological data such as genomic data and also a large amount of training data is required to generate accurate results. But with the advancing technologies and development on newer advanced GPT models, can easily provide potential solutions to these limitations.