Showing papers by "Rolf Fagerberg published in 2021"
TL;DR: In this paper, the authors performed time-series multi-omics analyses of liver and plasma revealing that the majority of molecular oscillations are entrained by adaptations to fasting, food intake, and the post-prandial state.
21 citations
TL;DR: Using graph transformation, this work derives about 1000 rules for amino acid side chain chemistry from the M-CSA database, a curated repository of enzymatic mechanisms, and proposes hundreds of hypothetical catalytic mechanisms for a large number of unrelated reactions in the Rhea database.
Abstract: Motivation The design of enzymes is as challenging as it is consequential for making chemical synthesis in medical and industrial applications more efficient, cost-effective and environmentally friendly. While several aspects of this complex problem are computationally assisted, the drafting of catalytic mechanisms, i.e. the specification of the chemical steps-and hence intermediate states-that the enzyme is meant to implement, is largely left to human expertise. The ability to capture specific chemistries of multistep catalysis in a fashion that enables its computational construction and design is therefore highly desirable and would equally impact the elucidation of existing enzymatic reactions whose mechanisms are unknown. Results We use the mathematical framework of graph transformation to express the distinction between rules and reactions in chemistry. We derive about 1000 rules for amino acid side chain chemistry from the M-CSA database, a curated repository of enzymatic mechanisms. Using graph transformation, we are able to propose hundreds of hypothetical catalytic mechanisms for a large number of unrelated reactions in the Rhea database. We analyze these mechanisms to find that they combine in chemically sound fashion individual steps from a variety of known multistep mechanisms, showing that plausible novel mechanisms for catalysis can be constructed computationally. Availability and implementation The source code of the initial prototype of our approach is available at https://github.com/Nojgaard/mechsearch. Supplementary information Supplementary data are available at Bioinformatics online.
6 citations
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TL;DR: In this paper, the fragile complexity of algorithms with a fragile complexity parameterized by a quantity other than the input size n has been explored, and it was shown that searching for the predecessor in a sorted array has fragile complexity in both randomized and deterministic setting.
Abstract: The fragile complexity of a comparison-based algorithm is $f(n)$ if each input element participates in $O(f(n))$ comparisons. In this paper, we explore the fragile complexity of algorithms adaptive to various restrictions on the input, i.e., algorithms with a fragile complexity parameterized by a quantity other than the input size n. We show that searching for the predecessor in a sorted array has fragile complexity ${\Theta}(\log k)$, where $k$ is the rank of the query element, both in a randomized and a deterministic setting. For predecessor searches, we also show how to optimally reduce the amortized fragile complexity of the elements in the array. We also prove the following results: Selecting the $k$-th smallest element has expected fragile complexity $O(\log \log k)$ for the element selected. Deterministically finding the minimum element has fragile complexity ${\Theta}(\log(Inv))$ and ${\Theta}(\log(Runs))$, where $Inv$ is the number of inversions in a sequence and $Runs$ is the number of increasing runs in a sequence. Deterministically finding the median has fragile complexity $O(\log(Runs) + \log \log n)$ and ${\Theta}(\log(Inv))$. Deterministic sorting has fragile complexity ${\Theta}(\log(Inv))$ but it has fragile complexity ${\Theta}(\log n)$ regardless of the number of runs.
10 May 2021
TL;DR: In this article, the fragile complexity of comparison-based algorithms is explored, where each input element participates in O(f(n)) comparisons, where n is the number of elements in the input.
Abstract: The fragile complexity of a comparison-based algorithm is f(n) if each input element participates in O(f(n)) comparisons. In this paper, we explore the fragile complexity of algorithms adaptive to various restrictions on the input, i.e., algorithms with a fragile complexity parameterized by a quantity other than the input size n. We show that searching for the predecessor in a sorted array has fragile complexity \(\varTheta (\log k)\), where k is the rank of the query element, both in a randomized and a deterministic setting. For predecessor searches, we also show how to optimally reduce the amortized fragile complexity of the elements in the array. We also prove the following results: Selecting the kth smallest element has expected fragile complexity \(O(\log \log k)\) for the element selected. Deterministically finding the minimum element has fragile complexity \(\varTheta (\log (\mathrm {Inv}))\) and \(\varTheta (\log (\mathrm {Runs}))\), where \(\mathrm {Inv}\) is the number of inversions in a sequence and \(\mathrm {Runs}\) is the number of increasing runs in a sequence. Deterministically finding the median has fragile complexity \(O(\log (\mathrm {Runs}) + \log \log n)\) and \(\varTheta (\log (\mathrm {Inv}))\). Deterministic sorting has fragile complexity \(\varTheta (\log (\mathrm {Inv}))\) but it has fragile complexity \(\varTheta (\log n)\) regardless of the number of runs.
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TL;DR: In this article, the authors use the mathematical framework of graph transformation to express the distinction between rules and reactions in chemistry and derive about 1000 rules for amino acid side chain chemistry from the M-CSA database.
Abstract: Motivation: The design of enzymes is as challenging as it is consequential for making chemical synthesis in medical and industrial applications more efficient, cost-effective and environmentally friendly While several aspects of this complex problem are computationally assisted, the drafting of catalytic mechanisms, ie the specification of the chemical steps-and hence intermediate states-that the enzyme is meant to implement, is largely left to human expertise The ability to capture specific chemistries of multi-step catalysis in a fashion that enables its computational construction and design is therefore highly desirable and would equally impact the elucidation of existing enzymatic reactions whose mechanisms are unknown Results: We use the mathematical framework of graph transformation to express the distinction between rules and reactions in chemistry We derive about 1000 rules for amino acid side chain chemistry from the M-CSA database, a curated repository of enzymatic mechanisms Using graph transformation we are able to propose hundreds of hypothetical catalytic mechanisms for a large number of unrelated reactions in the Rhea database We analyze these mechanisms to find that they combine in chemically sound fashion individual steps from a variety of known multi-step mechanisms, showing that plausible novel mechanisms for catalysis can be constructed computationally