The Workshop on Algorithms in Bioinformatics (WABI), established in 2001, is one of the major annual conferences on algorithms in bioinformatics. Due to COVID-19, WABI 2021 will be held online on August 2-4.
WABI is an international conference covering research in algorithmic work in bioinformatics, computational biology and systems biology. The emphasis is mainly on discrete algorithms and machine-learning methods that address important problems in molecular biology, that are founded on sound models, that are computationally efficient, and that provide evidence of their potential usefulness in practice, preferably by testing on appropriately chosen simulated or real datasets. The goal is to present recent research results, including significant work-in-progress, and to identify and explore directions of future research. This year it is colocated with ACM-BCB 2021.
Submissions must be formatted in LaTeX using the LIPIcs style and must not exceed 15 pages excluding references. For details please see the information for authors. Each paper must contain a succinct statement of the issues and of their motivation, a summary of the main results, and a brief explanation of their significance, all accessible to non-specialist readers. All submissions must be made online, through the EasyChair submission system, at:
For scientific information, please contact one of the WABI program committee co-chairs, Alessandra Carbone (Alessandra.Carbone[at]lip6[dot]fr) or Mohammed El-Kebir (melkebir[at]illinois[dot]edu). For organizational information, please refer to the ACM-BCB 2021 website.
You will need to register on the EasyChair web site before submitting. A standard .pdf file must be received by April 20, 2021 (time zone of your choice) in order for your submission to be considered. Re-submission of already submitted papers will be possible until April 22, 2021 (time zone of your choice). Simultaneous submission to another conference with published proceedings is not permitted, but simultaneous submission to a journal is allowed, provided that the authors notify the program chairs; if published in a journal, such a contribution will be published as a short abstract in the WABI proceedings. Depositing in arxiv.org or biorxiv.org is allowed.
By submitting a paper the authors acknowledge that in case of acceptance at least one of the authors must register at ACM-BCB 2021, attend the conference, and present the paper.
Accepted papers will be published in WABI proceedings in the LIPIcs Leibniz International Proceedings in Informatics.
Selected papers will be invited for an extended publication in a thematic series in Algorithms for Molecular Biology (AMB).
Jason Moore, Penn Institute for Biomedical Informatics
Jason Moore is the Edward Rose Professor of Informatics and Director of the Penn Institute for Biomedical Informatics. He also serves as Senior Associate Dean for Informatics and Chief of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics. He leads an active NIH-funded research program focused on the development of artificial intelligence and machine learning algorithms for the analysis of complex biomedical data. Recent work has focused on automated machine learning. He is an elected fellow of the American Association for the Advancement of Science (AAAS), an elected fellow of the American College of Medical Informatics (ACMI), and an elected fellow of the American Statistical Association (ASA). He serves as Editor-in-Chief of the journal BioData Mining.
Mona Singh, Princeton University
Mona Singh obtained her AB and SM degrees at Harvard University, and her PhD at MIT, all three in Computer Science. She did postdoctoral work at the Whitehead Institute for Biomedical Research. She has been on the faculty at Princeton since 1999, and currently she is Professor of Computer Science in the computer science department and the Lewis-Sigler Institute for Integrative Genomics. She received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001, and is a Fellow of the International Society for Computational Biology and a Fellow for the Association for Computing Machinery. She is Editor-In-Chief of the Journal of Computational Biology. She has been program committee chair for several major computational biology conferences, including ISMB (2010), WABI (2010), ACM-BCB (2012), and RECOMB (2016), and has been Chair of the NIH Modeling and Analysis of Biological Systems Study Section (2012-2014).
Aidong Zhang, University of Virginia
Dr. Aidong Zhang is a William Wulf Faculty Fellow and Professor at University of Virginia. Prior to UVA, she is a SUNY Distinguished Professor and department chair (2009-2015) at the State University of New York (SUNY) at Buffalo. Her research interests include machine learning, data mining/data science, bioinformatics, and health informatics. She has authored over 350 research publications in these areas. She is a fellow of ACM, AIMBE, and IEEE.