Call for | Submission Deadline | Notification of Acceptance |
---|---|---|
Papers | July 15, 2024 | Sep 22, 2024 |
Workshops | July 15, 2024 | July 29, 2024 |
Posters | Sep 25, 2024 | Sep 30, 2024 |
Highlights | Sep 10, 2024 | Sep 25, 2024 |
Biosketch: Dr. Aidong Zhang is the Thomas M. Linville Endowed Professor of Computer Science with joint appointment at Data Science, and Biomedical Engineering at University of Virginia (UVA). Prof. Zhang’s research interests include machine learning, data science, bioinformatics and computational biology, and health informatics. Prof. Zhang was the Editor-in-Chief of the IEEE Transactions on Computational Biology and Bioinformatics (TCBB) from 2017 to 2021. She served as the founding Chair of ACM Special Interest Group on Bioinformatics and Computational Biology (SIGBio) from 2011 to 2015 and also served as the Chair of its advisory board from 2015 to 2018. She was also the founding and steering chair of ACM international conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) from 2010 to 2019. Prof. Zhang is a fellow of ACM and IEEE. She is also a fellow of the American Institute for Medical and Biological Engineering (AIMBE).
Abstract: The past decade has been a very exciting time for machine learning (ML) research. Significant research effort has focused on improving predictive performance of Deep Neural Networks (DNN) by proposing increasingly complex architectures which have surpassed even human-level performance. Even though these methods demonstrate incredible potential in saving valuable man-hours and minimizing inadvertent human mistakes, their adoption has been met with rightful skepticism and extreme circumspection in critical applications such as medical diagnosis, etc. The most paramount of these challenges is the lack of rationale behind DNN predictions - making them notoriously a black-box in nature. In extreme cases, this can create a lack of alignment between the designer's intended behavior and the model's actual performance. In this talk, I will discuss our recent research on explainable deep learning, in particular, I will discuss the concept learning models and show how the concept-based learning models and example-based learning models can be designed for explainable deep tabular learning. I will also discuss their applications in biomedicine and healthcare.
Biosketch: Dr. Lin Gao is a professor in the Department of Computer Science and Technology, Xidian University. Her research interests include bioinformatics, data mining and machine learning, graph theory and optimization. She focused on computational model and algorithm in omics-data analysis, especially its application in cancer. Her research has been funded by the National Natural Science Foundation of China, National Key Research and Development Program of China, the Foundation of the Ministry of Education of China and other project. She has over 170 publications in professional journals, such as Nature Methods, Science Advances, Nature Communications, Advanced Science, Nucleic Acids Research, PLoS Computational Biology, Bioinformatics, et al. She also serves on various academic communities, member of China Computer Federation, Director of CCF Bioinformatics Committee, member of Chinese Association for Artificial Intelligence.
Title: Models and Algorithms for Single-cell Multi-omics Data Analysis Abstract: The rapid development of single-cell multi-omics sequencing technology has made it possible to explore cells in multiple dimensions (genomics, transcriptomics, epigenomics, and spatial transcriptomics), which has been highly valued by life science and has posed new challenges to computational methods in computer science. How to deeply understand the cellular function described by single-cell data and how to model the related biological problems by feature complementarity of multi-omics data poses a computational challenge. In this talk, I will introduce our work in the integration of multiple batches, cell type decomposition, cell-cell interaction and the discovery of tissue cellular neighborhoods.
Biosketch: Xing-Ming Zhao received his PhD degree from the University of Science and Technology of China. Currently, he is a distinguished professor and vice dean of the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, China. He is also the chair of Shanghai Society for Bioinformatics. He focuses on the interdisciplinary research between biomedicine and artificial intelligence. He has published more than 150 papers in peer-reviewed journals, e.g. Nature and Cell. He is the senior member of IEEE, Co-Chair of IEEE SMC Technical Committee on Systems Biology and Vice-Chair of ACM SIGBIO China. He is also the lead guest editor and the editorial member of several journals, e.g. IEEE/ACM TCBB, Neurocomputing, Journal of Theoretical Biology, IET Systems Biology, and so on.
Title:AI driven exploration of human microbiome Abstract: The human body is composed of various types of microbiome. However, our knowledge about human microbiome is far from comprehensive. In this talk, I’ll present our recent work on the exploration of human gut microbiome with long-read sequencing, and some algorithms and tools we have developed for analysis of human microbiome. I’ll also show some new findings on the enterotypes of gut mycobiome and the association between gut microbiome and diseases.
Please use the registration link below to attend ACM-BCB 2024 : [ACM-BCB 2024 Registration].
The early bird registration deadline is October 10, 2024, and attendees registering by this date are entitled for a lower registration fee. The registration fees are shown as follows:
Registration Policy:
DAYHELLO INTERNATIONAL HOTEL SHENZHEN CHINA
Hotel Information
The conference will be held at the DayHello International Hotel Shenzhen China. Located in Baoan District, Shenzhen, Guandong Province, the Dayhello International Hotel (登喜路国际大酒店) is located within easy reach of National Road 107. The Tycoon Golf Club is just a 10 minute drive away and Shenzhen Bao’an International Airport is 12.2 km (7.6) away. Guests can enjoy both Chinese and Western cuisine at the on-site restaurants or enjoy a drink at the lobby bar. This Shenzhen hotel provides free Wi-Fi in public areas.For recreation, guests can work out in the gym or take a dip in the outdoor swimming pool or spa. Please check the hotel details at: http://www.shenzhendayhellohotel.cn/en.
Address
NO.12 Bao tian 1st Road
Bao’an District,Shenzhen,Guangdong
Phone number: +86-755-23008888
Booking via email or phone call:
ACM-BCB participants can book hotel room at discounted conference rates (550 RMB) via email or phone. Please mention coupon code(大会优惠券) ACMBCB24 in your booking email or when you are calling. Payment will be collected at the time of check-in.
How to book:
Contact: Liu, Juan (manager)
Phone number: +86 18128818186
E-mail: 2327948683@qq.com
Room Types and Fees:
Letter request for VISA application
For visa support letters send a message to: bcb24@siat.ac.cn including:
Visa-Free policy of mainland China
Call for | Submission Deadline | Notification of Acceptance |
---|---|---|
Papers | July 15, 2024 | Sep 22, 2024 |
Workshops | July 15, 2024 | July 29, 2024 |
Posters | Sep 25, 2024 | Sep 30, 2024 |
Highlights | Sep 10, 2024 | Sep 25, 2024 |