Large language model to multimodal large language model: A journey to shape the biological macromolecules to biological sciences and medicine

Abstract

After ChatGPT was released, large language models (LLMs) became more popular. Academicians use ChatGPT or LLM models for different purposes, and the use of ChatGPT or LLM is increasing from medical science to diversified areas. Recently, the multimodal LLM (MLLM) has also become popular. Therefore, we comprehensively illustrate the LLM and MLLM models for a complete understanding. We also aim for simple and extended reviews of LLMs and MLLMs for a broad category of readers, such as researchers, students in diversified fields, and other academicians. The review article illustrates the LLM and MLLM models, their working principles, and their applications in diversified fields. First, we demonstrate the technical concept of LLMs, working principle, Black Box, and the evolution of LLMs. To explain the working principle, we discuss the tokenization process, token representation, and token relationships. We also extensively demonstrate the application of LLMs in biological macromolecules, medical science, biological science, and other areas. We illustrate the multimodal applications of LLMs or MLLMs. Finally, we illustrate the limitations, challenges, and future prospects of LLMs. The review acts as a booster dose for clinicians, a primer for molecular biologists, and a catalyst for scientists, and also benefits diversified academicians.

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