Guest Editors:
Prof. Gangqing Hu, michael.hu@hsc.wvu.edu, Department of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, WV, USA
Prof. Li Liu, liliu@asu.edu, College of Health Solutions, Arizona State University, Phoenix, AZ, USA
Prof. Dong Xu, xudong@missouri.edu, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
Background and Objective
Greeting esteemed readers and authors of Quantitative Biology! Over the last few months, we have all witnessed the excitements, chaos, and confusion that ChatGPT and other large language model based chatbots have brought to the world. This marks a significant milestone for a new era of Human-AI collaboration in our daily lives.
We have been amazed by ChatGPT’s potential in bioinformatics data analysis (https://doi.org/10.15302/J-QB-023-0327). Furthermore, ChatGPT-assisted health sciences research has just emerged in the literature. We are therefore thrilled to call for a community effort to explore the challenges and opportunities of using chatbots in bioinformatics, biomedical sciences, and health sciences. In this themed issue, we seek studies that push the limits of chatbots, such as ChatGPT, in designing and implementing bioinformatics algorithms, analyzing large-scale data in biomedical research, and assisting healthcare professionals in processing clinic records. Please join us on this unusual Human-AI expedition, and we will have some fun along the way!
We disclosed that ChatGPT contributed to this call for papers by proofreading it! When submitting your work, be sure to disclose how you are using a chatbot in your project as well if applicable.
Subject Coverage: We welcome submissions from authors on the topics listed below, but not limited to, for protocols, tutorials, perspectives, reviews, and original research articles:
· Chatbot-assisted algorithm development
· Chatbot-assisted analysis of omics data
· Chatbot-assisted mining of biomedical literature
· Chatbot-assisted processing of clinical records
· Prompt design for chatbot-based data analysis/mining
· Ethical and regulatory concerns on chatbots in data analysis
· Chatbot-based education in bioinformatics and health sciences
Quantitative Biology (Editors-in-Chief: Dr. Chao Tang and Dr. Michael Q. Zhang, Executive Editor-in-Chief: Dr. Xuegong Zhang; https://journal.hep.com.cn/qb) is an interdisciplinary journal that focuses on original research that uses quantitative approaches and technologies to analyze and integrate biological systems, construct and model engineered life systems, and gain a deeper understanding of the life sciences.
Quantitative Biology is an open-access journal. We offer APC free for authors. It has been indexed/abstracted by ESCI, Scopus, Chemical Abstracts Service (CAS), Google Scholar, Chinese Science Citation Database (CSCD), OCLC and Summon by ProQuest, etc.
Important Dates:
Submission Deadline for oral presentation in the International Conference on Intelligent Biology and Medicine (ICIBM-2023): April 5th, 2023.
Submission Deadline for this special issue: December 31th, 2023.
Note: If manuscripts are submitted before April 5th, 2023, authors may choose to be reviewed as part of the ICIBM-2023 collection of this special issue and present the studies in person at Tampa, FL, USA. Whether the studies are presented in ICIBM-2023 or not, QB journal will provide peer-review for the submissions.
Manuscripts Submission:
https://mc.manuscriptcentral.com/qb
For manuscripts concurrently considered for the ICIBM-2023 Conference, please use the EasyChair Conference System.
Content Available Online: