Comprehensive Updates in Network Synthesis Models to Create An Improved Benchmark for Network Alignment Algorithms
Pages 587 - 588
Abstract
Network synthesis models in NAPAbench provide effective means to generate synthetic network families that can be used to rigorously assess the performance of network alignment algorithms. In recent years, the protein-protein-interaction (PPI) databases have been significantly updated, hence the network synthesis models in NAPAbench need to be updated to be able to create synthetic network families whose characteristics are close to those of real PPI networks. In this work, we present updated models based on an extensive analysis of real-world PPI networks and their key features.
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Index Terms
- Comprehensive Updates in Network Synthesis Models to Create An Improved Benchmark for Network Alignment Algorithms
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Published In
August 2018
727 pages
ISBN:9781450357944
DOI:10.1145/3233547
- General Chairs:
- Amarda Shehu,
- Cathy Wu,
- Program Chairs:
- Christina Boucher,
- Jing Li,
- Hongfang Liu,
- Mihai Pop
Copyright © 2018 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
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Published: 15 August 2018
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BCB '18
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BCB '18: 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
August 29 - September 1, 2018
DC, Washington, USA
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BCB '18 Paper Acceptance Rate 46 of 148 submissions, 31%;
Overall Acceptance Rate 254 of 885 submissions, 29%
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