DrBioRight

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An artificial intelligence (AI) powered bioinformatics platform for analyzing and visualizing high-dimensional omics data.

DrBioRight interacts with users by human language and translates it to a series of actions based on the deep-learning algorithms that have been developed and trained by bioinformatics experts. Through the interactions with users, DrBioRight dynamically improves himself based on user feedbacks and also allows users to add their own modules as well as collaborate with each other.

Usage

Visit DrBioRight and start chatting!

Infrastructure

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The infrastructure of DrBioRight was designed to generically address all the bioinformatics related issues that biomedical researchers have experienced in their studies. In total, it consists of seven core components:

  1. human language recognition (i)
  2. module scoring (ii) and assignment (iii)
  3. job scheduling and executing (iv)
  4. data interpretation and visualization (v)
  5. results rating and model retraining (vi)
  6. module customization
  7. user collaboration

Compared to other bioinformatics tools, DrBioRight has the simplest user interface which only consists of one input and output area. All the interactions between DrBioRight and users are based on human language. Based on the cutting-edge natural language processing (NLP) libraries, DrBioRight can understand user’s requests, perform the correct bioinformatics analysis, and select the best visualization approaches to present the results. Moreover, DrBioRight will dynamically correct its behavior and conduct new combinations of individual tasks by learning from user feedbacks and expert curations. This positive feedback system enables DrBioRight to be a real problem solver through automated self-evolving.

Citation

If you use DrBioRight in your work, please cite the following paper and the corresponding base functions.

  • Li J*, Chen H*, Wang Y*, Chen, M*, and Liang H. “DrBioRight: a smart bio-analytic assistant powered by artificial intelligence for analyzing and visualizing cancer omics data.”