Solving Exact Cover Instances with Molecular-Motor-Powered Network-Based Biocomputation
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
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.
Details
Originalsprache | Englisch |
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Seiten (von - bis) | 396-403 |
Seitenumfang | 8 |
Fachzeitschrift | ACS nanoscience Au : an open access journal of the American Chemical Society |
Jahrgang | 2 |
Ausgabenummer | 5 |
Publikationsstatus | Veröffentlicht - 23 Juni 2022 |
Peer-Review-Status | Ja |
Externe IDs
unpaywall | 10.1021/acsnanoscienceau.2c00013 |
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PubMed | 36281252 |
ORCID | /0000-0002-0750-8515/work/142235522 |
Schlagworte
Forschungsprofillinien der TU Dresden
ASJC Scopus Sachgebiete
Schlagwörter
- biocomputation, biofunctionalization, computational nanotechnology, molecular motors, nanobiotechnology, parallel computing