Abstract
As biological datasets have grown exponentially in size and complexity, there has been an increasing need for integrative tools that can handle diverse data types and facilitate comprehensive analyses. Traditional methods often require significant computational expertise, creating barriers for many researchers. HBIcloud is a comprehensive online platform designed to facilitate multi-omics data analysis by integrating a wide array of tools across genomics, transcriptomics, proteomics, metabolomics, phenomics, and multi-omics integration. Developed to address the growing complexity and volume of biological data, HBIcloud provides researchers with a powerful and user-friendly resource for conducting sophisticated analyses without the need for extensive programming skills. With a total of 94 tools, the platform offers standardized workflows, extensive parameter options, and rich documentation, catering to the diverse needs of the scientific community. The research behind HBIcloud aimed to create a centralized, user-friendly platform that simplifies the analytical process, enabling researchers to focus on scientific discovery rather than technical challenges. By integrating a wide array of tools and offering extensive support and documentation, HBIcloud addresses the critical need for standardized, reproducible workflows in multi-omics research. This paper presents a detailed overview of HBIcloud, highlighting its development background, key features, and its significant contribution to advancing multi-omics research. Furthermore, we discuss the future prospects of HBIcloud, including planned enhancements and its potential for high citation impact within the scientific community. By providing a robust and versatile platform, HBIcloud aims to accelerate discovery and innovation in the field of multi-omics, fostering collaborative research and expanding the boundaries of biological understanding. The official website of HBIcloud is https://bioinformatics.hainanu.edu.cn/HBIcloud/.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
12416077{at}zju.edu.cn, +86-13244507081
23220951310155{at}hainanu.edu.cn, +86-19989697940
dongw26{at}mail2.sysu.edu.cn, +86-15960059795
wagnwenquan{at}itbb.org.cn, +86-13807665106