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Items: 9

1.

A computational framework for DNA sequencing microscopy.

Hoffecker IT, Yang Y, Bernardinelli G, Orponen P, Högberg B.

Proc Natl Acad Sci U S A. 2019 Sep 24;116(39):19282-19287. doi: 10.1073/pnas.1821178116. Epub 2019 Sep 4.

PMID:
31484777
2.

Effects of Design Choices on the Stiffness of Wireframe DNA Origami Structures.

Benson E, Mohammed A, Rayneau-Kirkhope D, Gådin A, Orponen P, Högberg B.

ACS Nano. 2018 Sep 25;12(9):9291-9299. doi: 10.1021/acsnano.8b04148. Epub 2018 Sep 6.

PMID:
30188123
3.

Computer-Aided Production of Scaffolded DNA Nanostructures from Flat Sheet Meshes.

Benson E, Mohammed A, Bosco A, Teixeira AI, Orponen P, Högberg B.

Angew Chem Int Ed Engl. 2016 Jul 25;55(31):8869-72. doi: 10.1002/anie.201602446. Epub 2016 Jun 15.

4.

DNA rendering of polyhedral meshes at the nanoscale.

Benson E, Mohammed A, Gardell J, Masich S, Czeizler E, Orponen P, Högberg B.

Nature. 2015 Jul 23;523(7561):441-4. doi: 10.1038/nature14586.

PMID:
26201596
5.

Witness of unsatisfiability for a random 3-satisfiability formula.

Wu LL, Zhou HJ, Alava M, Aurell E, Orponen P.

Phys Rev E Stat Nonlin Soft Matter Phys. 2013 May;87(5):052807. Epub 2013 May 20.

PMID:
23767584
6.

Circumspect descent prevails in solving random constraint satisfaction problems.

Alava M, Ardelius J, Aurell E, Kaski P, Krishnamurthy S, Orponen P, Seitz S.

Proc Natl Acad Sci U S A. 2008 Oct 7;105(40):15253-7. doi: 10.1073/pnas.0712263105. Epub 2008 Oct 1.

7.

General-purpose computation with neural networks: a survey of complexity theoretic results.

Síma J, Orponen P.

Neural Comput. 2003 Dec;15(12):2727-78. Review.

PMID:
14629867
8.

Continuous-time symmetric Hopfield nets are computationally universal.

Síma J, Orponen P.

Neural Comput. 2003 Mar;15(3):693-733.

PMID:
12620163
9.

On the computational complexity of binary and analog symmetric hopfield nets

Sima J, Orponen P, Antti-Poika T.

Neural Comput. 2000 Dec;12(12):2965-89.

PMID:
11112262

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