HOUSTON — A new data analysis tool developed by researchers at The University of Texas MD Anderson Cancer Center incorporates a user-friendly, natural-language interface to allow biomedical researchers without specialized expertise in bioinformatics or programming languages to conduct intuitive analysis of large datasets.
The open-access, artificial intelligence (AI)-driven program, called DrBioRight, was created to lower barriers for all researchers to make full use of the increasingly large amounts of data generated in modern research methods. A report of this platform was published today in Cancer Cell.
“We felt that we could improve the current model for conducting routine bioinformatics analysis and greatly speed up turnaround time by creating a tool that any researcher could use,” said Han Liang, Ph.D., professor of Bioinformatics and Computational Biology. “Our long-term goal for DrBioRight is to be an intelligent collaborator for every researcher.”
High-throughput technologies used in modern biomedical research generate large, complex datasets that provide comprehensive information about patients, animal models or cell lines being studied. These may include, for example, studying the whole of genetic information (genomics), gene expression (transcriptomics), or protein expression (proteomics).
Because these “omics” datasets are so complex, it can be challenging to answer specific biological questions without specialized analytical approaches, explained Liang. These analyses are usually done with using a computer script written in a variety of programming languages, which requires some understanding of both programming and bioinformatics.
Bioinformaticians can help to navigate and process these complex datasets, but the work can be time consuming. Therefore, the research team developed DrBioRight to enable researchers to more easily conduct