3 Search Results for "Vasic, Marko"

Document
DOI: 10.4230/LIPIcs.DNA.32.8
Amplification at Equilibrium: Structural and Thermodynamic Limitations, and Implementation

Authors: Hamidreza Akef, Chia-Yu Sung, Aneesh Vanguri, and David Soloveichik

Published in: LIPIcs, Volume 387, 32nd International Conference on DNA Computing and Molecular Programming (DNA 32) (2026)

Abstract
Amplifying weak molecular signals is essential in both natural and engineered biochemical systems. While most amplification schemes operate out of equilibrium, relying on kinetic barriers and fuel-driven cascades, it is also possible to amplify at thermodynamic equilibrium by shifting the energy landscape upon addition of an analyte. Equilibrium amplification is appealing because, in principle, the system can remain indefinitely in the untriggered state. In this work, we establish fundamental structural and thermodynamic limits on equilibrium-based amplification. We first prove that dimerization networks - systems restricted to complexes of at most two monomers - are inherently incapable of equilibrium amplification. This no-go theorem explains the absence of amplification in prior undercomplementary "strand commutation" designs. We then show that allowing trimeric complexes breaks this barrier. We propose an isometric trimer-based equilibrium amplifier whose output preserves the size of the input, enabling modular composition, and validate it experimentally, achieving an amplification factor close to the expected 2×. Finally, we derive universal thermodynamic bounds applicable regardless of complex size: the maximum amplification factor scales linearly with the free energy of interaction between the analyte and the amplifier components. For nucleic acid systems, this implies that the analyte length must grow linearly with the desired amplification factor, and that composing modular amplifiers yields diminishing returns for a fixed analyte. Together, these results delineate the structural and energetic boundaries of equilibrium amplification and rigorously justify the necessity of out-of-equilibrium approaches for achieving high gain.
Cite as

Hamidreza Akef, Chia-Yu Sung, Aneesh Vanguri, and David Soloveichik. Amplification at Equilibrium: Structural and Thermodynamic Limitations, and Implementation. In 32nd International Conference on DNA Computing and Molecular Programming (DNA 32). Leibniz International Proceedings in Informatics (LIPIcs), Volume 387, pp. 8:1-8:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{akef_et_al:LIPIcs.DNA.32.8,
  author =	{Akef, Hamidreza and Sung, Chia-Yu and Vanguri, Aneesh and Soloveichik, David},
  title =	{{Amplification at Equilibrium: Structural and Thermodynamic Limitations, and Implementation}},
  booktitle =	{32nd International Conference on DNA Computing and Molecular Programming (DNA 32)},
  pages =	{8:1--8:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-444-4},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{387},
  editor =	{Scalise, Dominic and Schweller, Robert},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.32.8},
  URN =		{urn:nbn:de:0030-drops-267789},
  doi =		{10.4230/LIPIcs.DNA.32.8},
  annote =	{Keywords: Equilibrium amplification, Dimerization networks, Strand commutation, Thermodynamics of amplification}
}
Document
DOI: 10.4230/LIPIcs.DNA.31.4
Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems

Authors: Inhoo Lee, Salvador Buse, and Erik Winfree

Published in: LIPIcs, Volume 347, 31st International Conference on DNA Computing and Molecular Programming (DNA 31) (2025)

Abstract
Many molecular systems are best understood in terms of prototypical species and reactions. The central dogma and related biochemistry are rife with examples: gene i is transcribed into RNA i, which is translated into protein i; kinase n phosphorylates substrate m; protein p dimerizes with protein q. Engineered nucleic acid systems also often have this form: oligonucleotide i hybridizes to complementary oligonucleotide j; signal strand n displaces the output of seesaw gate m; hairpin p triggers the opening of target q. When there are many variants of a small number of prototypes, it can be conceptually cleaner and computationally more efficient to represent the full system in terms of indexed species (e.g. for dimerization, M_p, D_pq) and indexed reactions (M_p + M_q → D_pq). Here, we formalize the Indexed Chemical Reaction Network (ICRN) model and describe a Python software package designed to simulate such systems in the well-mixed and reaction-diffusion settings, using a differentiable programming framework originally developed for large-scale neural network models, taking advantage of GPU acceleration when available. Notably, this framework makes it straightforward to train the models’ initial conditions and rate constants to optimize a target behavior, such as matching experimental data, performing a computation, or exhibiting spatial pattern formation. The natural map of indexed chemical reaction networks onto neural network formalisms provides a tangible yet general perspective for translating concepts and techniques from the theory and practice of neural computation into the design of biomolecular systems.
Cite as

Inhoo Lee, Salvador Buse, and Erik Winfree. Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems. In 31st International Conference on DNA Computing and Molecular Programming (DNA 31). Leibniz International Proceedings in Informatics (LIPIcs), Volume 347, pp. 4:1-4:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{lee_et_al:LIPIcs.DNA.31.4,
  author =	{Lee, Inhoo and Buse, Salvador and Winfree, Erik},
  title =	{{Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems}},
  booktitle =	{31st International Conference on DNA Computing and Molecular Programming (DNA 31)},
  pages =	{4:1--4:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-399-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{347},
  editor =	{Schaeffer, Josie and Zhang, Fei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.31.4},
  URN =		{urn:nbn:de:0030-drops-238534},
  doi =		{10.4230/LIPIcs.DNA.31.4},
  annote =	{Keywords: Differentiable Programming, Chemical Reaction Networks, Reaction-Diffusion Systems}
}
Document
DOI: 10.4230/LIPIcs.DNA.2020.4
CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks

Authors: Marko Vasic, David Soloveichik, and Sarfraz Khurshid

Published in: LIPIcs, Volume 174, 26th International Conference on DNA Computing and Molecular Programming (DNA 26) (2020)

Abstract
Formal methods have enabled breakthroughs in many fields, such as in hardware verification, machine learning and biological systems. The key object of interest in systems biology, synthetic biology, and molecular programming is chemical reaction networks (CRNs) which formalizes coupled chemical reactions in a well-mixed solution. CRNs are pivotal for our understanding of biological regulatory and metabolic networks, as well as for programming engineered molecular behavior. Although it is clear that small CRNs are capable of complex dynamics and computational behavior, it remains difficult to explore the space of CRNs in search for desired functionality. We use Alloy, a tool for expressing structural constraints and behavior in software systems, to enumerate CRNs with declaratively specified properties. We show how this framework can enumerate CRNs with a variety of structural constraints including biologically motivated catalytic networks and metabolic networks, and seesaw networks motivated by DNA nanotechnology. We also use the framework to explore analog function computation in rate-independent CRNs. By computing the desired output value with stoichiometry rather than with reaction rates (in the sense that X → Y+Y computes multiplication by 2), such CRNs are completely robust to the choice of reaction rates or rate law. We find the smallest CRNs computing the max, minmax, abs and ReLU (rectified linear unit) functions in a natural subclass of rate-independent CRNs where rate-independence follows from structural network properties.
Cite as

Marko Vasic, David Soloveichik, and Sarfraz Khurshid. CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks. In 26th International Conference on DNA Computing and Molecular Programming (DNA 26). Leibniz International Proceedings in Informatics (LIPIcs), Volume 174, pp. 4:1-4:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{vasic_et_al:LIPIcs.DNA.2020.4,
  author =	{Vasic, Marko and Soloveichik, David and Khurshid, Sarfraz},
  title =	{{CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks}},
  booktitle =	{26th International Conference on DNA Computing and Molecular Programming (DNA 26)},
  pages =	{4:1--4:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-163-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{174},
  editor =	{Geary, Cody and Patitz, Matthew J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.2020.4},
  URN =		{urn:nbn:de:0030-drops-129574},
  doi =		{10.4230/LIPIcs.DNA.2020.4},
  annote =	{Keywords: molecular programming, formal methods}
}
  • Refine by Type
  • 3 Document/PDF
  • 1 Document/HTML

  • Refine by Publication Year
  • 1 2026
  • 1 2025
  • 1 2020

  • Refine by Author
  • 2 Soloveichik, David
  • 1 Akef, Hamidreza
  • 1 Buse, Salvador
  • 1 Khurshid, Sarfraz
  • 1 Lee, Inhoo
  • Show More...

  • Refine by Series/Journal
  • 3 LIPIcs

  • Refine by Classification
  • 2 Computer systems organization → Molecular computing
  • 1 Applied computing → Systems biology
  • 1 Mathematics of computing → Mathematical analysis
  • 1 Theory of computation

  • Refine by Keyword
  • 1 Chemical Reaction Networks
  • 1 Differentiable Programming
  • 1 Dimerization networks
  • 1 Equilibrium amplification
  • 1 Reaction-Diffusion Systems
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact