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  1. Article ; Online: A reaction network scheme for hidden Markov model parameter learning.

    Wiuf, Carsten / Behera, Abhishek / Singh, Abhinav / Gopalkrishnan, Manoj

    Journal of the Royal Society, Interface

    2023  Volume 20, Issue 203, Page(s) 20220877

    Abstract: With a view towards artificial cells, molecular communication systems, molecular multiagent systems and federated learning, we propose a novel reaction network scheme (termed the Baum-Welch (BW) reaction network) that learns parameters for hidden Markov ... ...

    Abstract With a view towards artificial cells, molecular communication systems, molecular multiagent systems and federated learning, we propose a novel reaction network scheme (termed the Baum-Welch (BW) reaction network) that learns parameters for hidden Markov models (HMMs). All variables including inputs and outputs are encoded by separate species. Each reaction in the scheme changes only one molecule of one species to one molecule of another. The reverse change is also accessible but via a different set of enzymes, in a design reminiscent of futile cycles in biochemical pathways. We show that every positive fixed point of the BW algorithm for HMMs is a fixed point of the reaction network scheme, and vice versa. Furthermore, we prove that the 'expectation' step and the 'maximization' step of the reaction network separately converge exponentially fast and compute the same values as the E-step and the M-step of the BW algorithm. We simulate example sequences, and show that our reaction network learns the same parameters for the HMM as the BW algorithm, and that the log-likelihood increases continuously along the trajectory of the reaction network.
    MeSH term(s) Algorithms ; Markov Chains
    Language English
    Publishing date 2023-06-21
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2156283-0
    ISSN 1742-5662 ; 1742-5689
    ISSN (online) 1742-5662
    ISSN 1742-5689
    DOI 10.1098/rsif.2022.0877
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Pooling Samples to Increase SARS-CoV-2 Testing.

    Gopalkrishnan, Manoj / Krishna, Sandeep

    Journal of the Indian Institute of Science

    2020  Volume 100, Issue 4, Page(s) 787–792

    Abstract: As SARS-CoV-2 continues to propagate around the world, it is becoming increasingly important to scale up testing. This is necessary both at the individual level, to inform diagnosis, treatment and contract tracing, as well as at the population level to ... ...

    Abstract As SARS-CoV-2 continues to propagate around the world, it is becoming increasingly important to scale up testing. This is necessary both at the individual level, to inform diagnosis, treatment and contract tracing, as well as at the population level to inform policies to control spread of the infection. The gold-standard RT-qPCR test for the virus is relatively expensive and takes time, so combining multiple samples into "pools" that are tested together has emerged as a useful way to test many individuals with less than one test per person. Here, we describe the basic idea behind pooling of samples and different methods for reconstructing the result for each individual from the test of pooled samples. The methods range from simple pooling, where each pool is disjoint from the other, to more complex combinatorial pooling where each sample is split into multiple pools and each pool has a specified combination of samples. We describe efforts to validate these testing methods clinically and the potential advantages of the combinatorial pooling method named Tapestry Pooling that relies on compressed sensing techniques.
    Keywords covid19
    Language English
    Publishing date 2020-10-18
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2139553-6
    ISSN 0970-4140 ; 0970-4140 ; 0019-4964
    ISSN (online) 0970-4140
    ISSN 0970-4140 ; 0019-4964
    DOI 10.1007/s41745-020-00204-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: Autonomous Learning of Generative Models with Chemical Reaction Network Ensembles

    Poole, William / Ouldridge, Thomas E. / Gopalkrishnan, Manoj

    2023  

    Abstract: Can a micron sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory, and statistical physics to ... ...

    Abstract Can a micron sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory, and statistical physics to develop a general architecture whereby a broad class of chemical systems can autonomously learn complex distributions. Our construction takes the form of a chemical implementation of machine learning's optimization workhorse: gradient descent on the relative entropy cost function. We show how this method can be applied to optimize any detailed balanced chemical reaction network and that the construction is capable of using hidden units to learn complex distributions. This result is then recast as a form of integral feedback control. Finally, due to our use of an explicit physical model of learning, we are able to derive thermodynamic costs and trade-offs associated to this process.
    Keywords Quantitative Biology - Molecular Networks ; Computer Science - Emerging Technologies ; Computer Science - Machine Learning ; Computer Science - Neural and Evolutionary Computing ; Electrical Engineering and Systems Science - Systems and Control ; Physics - Biological Physics
    Subject code 501
    Publishing date 2023-11-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines

    Poole, William / Ouldridge, Thomas / Gopalkrishnan, Manoj / Winfree, Erik

    2022  

    Abstract: Can a micron sized sack of interacting molecules understand, and adapt to a constantly-fluctuating environment? Cellular life provides an existence proof in the affirmative, but the principles that allow for life's existence are far from being proven. ... ...

    Abstract Can a micron sized sack of interacting molecules understand, and adapt to a constantly-fluctuating environment? Cellular life provides an existence proof in the affirmative, but the principles that allow for life's existence are far from being proven. One challenge in engineering and understanding biochemical computation is the intrinsic noise due to chemical fluctuations. In this paper, we draw insights from machine learning theory, chemical reaction network theory, and statistical physics to show that the broad and biologically relevant class of detailed balanced chemical reaction networks is capable of representing and conditioning complex distributions. These results illustrate how a biochemical computer can use intrinsic chemical noise to perform complex computations. Furthermore, we use our explicit physical model to derive thermodynamic costs of inference.

    Comment: Based on work in William Poole's Thesis "Compilation and Inference with Chemical Reaction Networks" available at: https://www.dna.caltech.edu/Papers/William_Poole_2022_thesis.pdf
    Keywords Quantitative Biology - Molecular Networks ; Condensed Matter - Statistical Mechanics ; Computer Science - Machine Learning
    Subject code 612
    Publishing date 2022-05-12
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Catalysis in reaction networks.

    Gopalkrishnan, Manoj

    Bulletin of mathematical biology

    2011  Volume 73, Issue 12, Page(s) 2962–2982

    Abstract: We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is "on" in the presence of certain catalysts and "off" in their absence. We show that examples of catalytic networks include synthetic ... ...

    Abstract We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is "on" in the presence of certain catalysts and "off" in their absence. We show that examples of catalytic networks include synthetic DNA molecular circuits that have been shown to perform signal amplification and molecular logic. Recall that a critical siphon is a subset of the species in a chemical reaction network whose absence is forward invariant and stoichiometrically compatible with a positive point. Our main theorem is that all weakly-reversible networks with critical siphons are catalytic. Consequently, we obtain new proofs for the persistence of atomic event-systems of Adleman et al., and normal networks of Gnacadja. We define autocatalytic networks, and conjecture that a weakly-reversible reaction network has critical siphons if and only if it is autocatalytic.
    MeSH term(s) Catalysis ; Mathematical Concepts ; Metabolic Networks and Pathways ; Models, Biological
    Language English
    Publishing date 2011-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 184905-0
    ISSN 1522-9602 ; 0007-4985 ; 0092-8240
    ISSN (online) 1522-9602
    ISSN 0007-4985 ; 0092-8240
    DOI 10.1007/s11538-011-9655-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Pooling Samples to Increase SARS-CoV-2 Testing

    Gopalkrishnan, Manoj / Krishna, Sandeep

    J Indian Inst Sci

    Abstract: As SARS-CoV-2 continues to propagate around the world, it is becoming increasingly important to scale up testing. This is necessary both at the individual level, to inform diagnosis, treatment and contract tracing, as well as at the population level to ... ...

    Abstract As SARS-CoV-2 continues to propagate around the world, it is becoming increasingly important to scale up testing. This is necessary both at the individual level, to inform diagnosis, treatment and contract tracing, as well as at the population level to inform policies to control spread of the infection. The gold-standard RT-qPCR test for the virus is relatively expensive and takes time, so combining multiple samples into "pools" that are tested together has emerged as a useful way to test many individuals with less than one test per person. Here, we describe the basic idea behind pooling of samples and different methods for reconstructing the result for each individual from the test of pooled samples. The methods range from simple pooling, where each pool is disjoint from the other, to more complex combinatorial pooling where each sample is split into multiple pools and each pool has a specified combination of samples. We describe efforts to validate these testing methods clinically and the potential advantages of the combinatorial pooling method named Tapestry Pooling that relies on compressed sensing techniques.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #888324
    Database COVID19

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  7. Book ; Online: Active Inference for Stochastic Control

    Paul, Aswin / Sajid, Noor / Gopalkrishnan, Manoj / Razi, Adeel

    2021  

    Abstract: Active inference has emerged as an alternative approach to control problems given its intuitive (probabilistic) formalism. However, despite its theoretical utility, computational implementations have largely been restricted to low-dimensional, ... ...

    Abstract Active inference has emerged as an alternative approach to control problems given its intuitive (probabilistic) formalism. However, despite its theoretical utility, computational implementations have largely been restricted to low-dimensional, deterministic settings. This paper highlights that this is a consequence of the inability to adequately model stochastic transition dynamics, particularly when an extensive policy (i.e., action trajectory) space must be evaluated during planning. Fortunately, recent advancements propose a modified planning algorithm for finite temporal horizons. We build upon this work to assess the utility of active inference for a stochastic control setting. For this, we simulate the classic windy grid-world task with additional complexities, namely: 1) environment stochasticity; 2) learning of transition dynamics; and 3) partial observability. Our results demonstrate the advantage of using active inference, compared to reinforcement learning, in both deterministic and stochastic settings.

    Comment: 12 pages, 5 figures, Accepted presentation at IWAI-2021 (ECML-PKDD)
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2021-08-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: A coercion-resistant protocol for conducting elections by telephone

    Gopalkrishnan, Manoj

    2013  

    Abstract: We present a protocol that allows voters to phone in their votes. Our protocol makes it expensive for a candidate and a voter to cooperate to prove to the candidate who the voter voted for. When the electoral pool is large enough, the cost to the ... ...

    Abstract We present a protocol that allows voters to phone in their votes. Our protocol makes it expensive for a candidate and a voter to cooperate to prove to the candidate who the voter voted for. When the electoral pool is large enough, the cost to the candidate of manipulating sufficiently many votes to have an influence on the election results becomes impossibly expensive. Hence, the protocol provides candidates no incentive to attempt inducement or coercion of voters, resulting in free and fair elections with the promise of cost savings and higher voter turnout over traditional elections. One major inadequacy with our suggested protocol is that we assume the existence of a trusted election authority to count the votes.

    Comment: v2: 15 pages, no figures. We point out that the protocol requires an assumption of a trusted election authority, unlike traditional paper ballots; v1: 14 pages, no figures
    Keywords Computer Science - Cryptography and Security ; Computer Science - Computers and Society
    Subject code 303
    Publishing date 2013-05-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: Catalysis in Reaction Networks

    Gopalkrishnan, Manoj

    2010  

    Abstract: We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is on in the presence of certain catalysts and off in their absence. We show that examples of catalytic networks include synthetic DNA ... ...

    Abstract We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is on in the presence of certain catalysts and off in their absence. We show that examples of catalytic networks include synthetic DNA molecular circuits that have been shown to perform signal amplification and molecular logic. Recall that a critical siphon is a subset of the species in a chemical reaction network whose absence is forward invariant and stoichiometrically compatible with a positive point. Our main theorem is that all weakly-reversible networks with critical siphons are catalytic. Consequently, we obtain new proofs for the persistence of atomic event-systems of Adleman et al., and normal networks of Gnacadja. We define autocatalytic networks, and conjecture that a weakly-reversible reaction network has critical siphons if and only if it is autocatalytic.

    Comment: 19 pages, 1 figure
    Keywords Quantitative Biology - Molecular Networks ; Mathematics - Commutative Algebra ; 34D23 ; 92B99 (Primary) 13A15 (Secondary)
    Publishing date 2010-06-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Autocatalysis in reaction networks.

    Deshpande, Abhishek / Gopalkrishnan, Manoj

    Bulletin of mathematical biology

    2014  Volume 76, Issue 10, Page(s) 2570–2595

    Abstract: The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is ... ...

    Abstract The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is that if all reactions are reversible in a weak sense, then no species can go extinct. A notion that has been found useful in thinking about persistence is that of "critical siphon." We explore the combinatorics of critical siphons, with a view toward the persistence conjecture. We introduce the notions of "drainable" and "self-replicable" (or autocatalytic) siphons. We show that: Every minimal critical siphon is either drainable or self-replicable; reaction networks without drainable siphons are persistent; and nonautocatalytic weakly reversible networks are persistent. Our results clarify that the difficulties in proving the persistence conjecture are essentially due to competition between drainable and self-replicable siphons.
    MeSH term(s) Algorithms ; Catalysis ; Kinetics ; Mathematical Concepts ; Models, Chemical ; Synthetic Biology ; Systems Biology
    Language English
    Publishing date 2014-10
    Publishing country United States
    Document type Journal Article
    ZDB-ID 184905-0
    ISSN 1522-9602 ; 0007-4985 ; 0092-8240
    ISSN (online) 1522-9602
    ISSN 0007-4985 ; 0092-8240
    DOI 10.1007/s11538-014-0024-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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