Workshop on Future Directions in Network Biology
June 12-14, 2022
Morris Inn, University of Notre Dame (ND), Indiana, USA

Workshop summary

Network biology, a field in the intersection of computer science and biology, is critical for deepening understanding of cellular functioning and disease. While the field is relatively young, there have already been rapid changes to it and new computational/algorithmic challenges have arisen, owing to many factors, including increasing data complexity. So, research directions in the field need to evolve accordingly. This workshop, funded by NSF award CCF-1941447, aims to identify pressing challenges in this field and propose solutions to the challenges. Thus, the workshop will help shape the short- and long-term vision for algorithmic research in network biology.

The workshop is a targeted meeting of scientists (primarily faculty or equivalent researchers in industry or government) who are doing active and state-of-the-art research in various aspects of network biology. The workshop will be held in person. The in-person component is critical for the planned highly interactive nature of the workshop, which is why we have waited for two years to hold this workshop, which was originally planned for 2020. Note that because of the pandemic-related uncertainty and changing policies related to international travel, we have been unable to invite for in-person participation those located outside of the United States. Yet, to allow for participation of international network biology researchers and others who have been unable to travel to the workshop venue, an online component of the workshop will be offered as well (details will be sent to confirmed online workshop participants). The in-person workshop participants will coordinate into teams corresponding to several key scientific topics in the field of network biology, and present their views of important current and future research directions on the topics. All (in-person and online workshop participants) will then have a chance to engage into lively discussions on any and all of the topics. A goal is to understand how the field of computer science and algorithms in particular is benefiting the field of network biology, and vice versa, and how to strengthen this synergy even further.

Organizers

Tijana Milenkovic, Frank M. Freimann Collegiate Professor of Engineering, University of Notre Dame
Jinbo Xu, Professor, Toyota Technological Institute at Chicago
Marinka Zitnik, Assistant Professor of Biomedical Informatics, Harvard Medical School

Schedule

In-person workshop participants

Serdar Bozdag, Associate Professor, Computer Science and Engineering, University of North Texas
Danny Chen, Professor, Computer Science and Engineering, University of Notre Dame
Kapil Devkota, PhD. Candidate, Computer Science, Tufts University
Anthony Gitter, Associate Professor, Biostatistics and Medical Informatics, University of Wisconsin-Madison
Kimberly Glass, Assistant Professor, Medicine, Harvard Medical School
Sara Gosline, Team Lead, Molecular Analytics, Pacific Northwest National Laboratory
Pengfei Gu, Ph.D. Student, Computer Science and Engineering, University of Notre Dame
Heng Huang, Professor, Electrical and Computer Engineering, University of Pittsburg
Meng Jiang, Assistant Professor, Computer Science and Engineering, University of Notre Dame
Arjun Krishnan, Assistant Professor, Computational Mathematics, Science and Engineering & Biochemistry and Molecular Biology, Michigan State University
Michelle Li, Ph.D. Candidate, Biomedical Informatics, Harvard Medical School
Gang Liu, Ph.D. Student, Computer Science and Engineering, University of Notre Dame
Tijana Milenkovic, Professor, Computer Science and Engineering, University of Notre Dame
Deisy Morselli Gysi, Associate Research Scientist, Network Science Institute, Northeastern University
T. M. Murali, Professor, Computer Science, Virginia Tech
Ziynet Nesibe Kesimoglu, Ph.D. Candidate, Computer Science and Engineering, University of North Texas
Michael Pfrender, Professor, Biology, University of Notre Dame
Alex Pico, Core Director, Bioinformatics, Gladstone Institutes
Teresa Przytycka, Senior Investigator, National Library of Medicine, National Institutes of Health
Predrag Radivojac, Professor, Computer Science, Northeastern University
Ben Raphael, Professor, Computer Science, Princeton University
Anna Ritz, Associate Professor, Biology, Reed College
Sushmita Roy, Associate Professor, Biostatistics and Medical Informatics, University ofWisconsin-Madison
Yang Shen, Associate Professor, Electrical and Computer Engineering, Texas A&M University
Mona Singh, Professor, Computer Science, Princeton University
Donna Slonim, Professor, Computer Science, Tufts University
Hanghang Tong, Associate Professor, Computer Science, University of Illinois Urbana-Champaign
Xinan Holly Yang, Research Associate Professor, Pediatrics, University of Chicago
Byung-Jun Yoon, Associate Professor, Electrical and Computer Engineering, Texas A&M University
Haiyuan Yu, Professor, Computational Biology, Cornell University
Marinka Zitnik, Assistant Professor, Biomedical Informatics, Harvard Medical School

Online workshop participants

Gary Bader, Professor, Donnelly Centre, University of Toronto
Mitra Basu, Program Director, Division of Computing and Communication Foundations (CISE/CCF), National Science Foundation
Anais Baudot, Networks and Systems Biology for Diseases, Marseille Medical Genetics
Carlo Cannistraci, Professor, Laboratory of Brain and Intelligence, Tsinghua University
Lenore Cowen, Professor, Computer Science, Tufts University
Pietro Guzzi, Associate Professor, Medical and Surgical Sciences, University of Catanzaro
Mehmet Koyuturk, Professor, Computer and Data Sciences, Case Western Reserve University
Jian Ma, Professor, Computer Science, Carnegie Mellon University
Roded Sharan, Professor, Computer Science, Tel-Aviv University

Scientific sessions, presentation slides, and workshop videos

    Playlist of all videos combined

  • Higher-order network analysis (presentation slides and video from the workshop), e.g.:
    • Network motifs/graphlets
    • Hypergraphs
    • Network clustering
  • Multimodal networks and integration (presentation slides and video from the workshop), e.g.:
    • Network fusion
    • Heterogeneous and attributed networks
    • Multi-scale and multi-level networks; networks of networks
    • Spatio-temporal networks
    • Omics data integration
  • Inference and comparison of biological networks (presentation slides and video from the workshop), e.g.:
    • Network de-noising/link prediction (including protein interaction prediction from sequence/3D fold data)
    • Network construction (e.g., gene regulatory networks, condition-specific networks, etc.)
    • Random graph modeling
    • Alignment-based network comparison (network alignment, differential network analysis)
    • Alignment-free network comparison (quantifying network similarity)
  • Machine learning on networks (presentation slides and video from the workshop), e.g.:
    • Deep learning on graphs
    • Network embeddings
    • Generative network models
    • Transfer learning across graphs
  • Network-based personalized medicine in and outside of clinic (presentation slides and video from the workshop), e.g.:
    • Inside: molecular, electronic health record, therapy, etc. data
    • Outside: social interaction, mobility, lifestyle, health app (e.g., Fitbit), etc. data
  • Discussion and closing remarks (video from the workshop), e.g.:

Representative fundamental, influential, or recent papers (this is not an exhaustive list)

University of Notre Dame's policy on sexual harassment, other forms of harassment, and sexual assault

The Notre Dame's policy on sexual and other forms of harassment will apply to all workshop participants. The policy and reporting procedures are available as follows: