ArticleACS nanoscience Au2022
Solving Exact Cover Instances with Molecular-Motor-Powered Network-Based Biocomputation.
Article in ACS nanoscience Au, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Barcoding Microtubules: Encoding Information onto Macromolecules by Photobleaching.Nano letters · 2025Article
- Improved longevity of actomyosin in vitro motility assays for sustainable lab-on-a-chip applications.Scientific reports · 2024Article
- Exploitation of Engineered Light-Switchable Myosin XI for Nanotechnological Applications.ACS nano · 2023Article
- Nanolithographic Fabrication Technologies for Network-Based Biocomputation Devices.Materials (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Information processing by traditional, serial electronic processors consumes an ever-increasing part of the global electricity supply. An alternative, highly energy efficient, parallel computing paradigm is network-based biocomputation (NBC). In NBC a given combinatorial problem is encoded into a nanofabricated, modular network. Parallel exploration of the network by a very large number of independent molecular-motor-propelled protein filaments solves the encoded problem. Here we demonstrate a significant scale-up of this technology by solving four instances of Exact Cover, a nondeterministic polynomial time (NP) complete problem with applications in resource scheduling. The difficulty of the largest instances solved here is 128 times greater in comparison to the current state of the art for NBC.
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Registered trials
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