1. Enzyme cascade to enzyme complex phase-transition-like transformation studied by the maximum entropy production principleAndrej Dobovišek, Tina Blaževič, Samo Kralj, Aleš Fajmut, 2025, izvirni znanstveni članek Opis: In biological cells, soluble enzymes often spontaneously reorganize into higher-order complexes called metabolons, providing regulatory advantages over individual soluble enzymes under specific conditions. Despite their importance, the mechanisms underlying metabolon formation remain unclear. Here we report a theoretical model that elucidates the spontaneous transition between soluble enzyme cascades and complexes, driven by fluctuations in intermediate metabolite concentrations. The model integrates the maximum entropy production principle (MEPP) and the Shannon information entropy (MaxEnt), Landau phase-transition theory, kinetic modeling, stability analysis, and metabolic control analysis. Our results show that soluble enzymes and enzyme complexes represent two distinct catalytic states with unique kinetic and regulatory properties. The transition from an enzyme cascade to an enzyme complex displays features of a first-order phasetransition, highlighting the system's tendency to reorganize into its most thermodynamically favorable state, providing a potential pathway for metabolic regulation.
Ključne besede: theoretical modeling, irreversible thermodynamics, maximum entropy production principle, Shannon information entropy, first-order phase transition, enzyme organization, enzyme cascade, enzyme complex
Objavljeno v DKUM: 06.02.2025; Ogledov: 0; Prenosov: 1
 Celotno besedilo (1,52 MB)
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2. A case study on entropy-aware block-based linear transforms for lossless image compressionBorut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek, 2024, izvirni znanstveni članek Opis: Data compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. In this regard, lossless image data compression is especially challenging. Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. In this paper, a block optimisation programming framework is introduced to support various experiments on raster images, divided into blocks of pixels. Eleven methods were implemented within , including prediction methods, string transformation methods, and inverse distance weighting, as a representative of interpolation methods. Thirty-two different greyscale raster images with varying resolutions and contents were used in the experiments. It was shown that reduces information entropy better than the popular JPEG LS and CALIC predictors. The additional information associated with each block in is then evaluated. It was confirmed that, despite this additional cost, the estimated size in bytes is smaller in comparison to the sizes achieved by the JPEG LS and CALIC predictors.
Ključne besede: computer science, information entropy, prediction, inverse distance transform, string transformations
Objavljeno v DKUM: 07.01.2025; Ogledov: 0; Prenosov: 9
Celotno besedilo (5,13 MB) |
3. A new transformation technique for reducing information entropy : a case study on greyscale raster imagesBorut Žalik, Damjan Strnad, David Podgorelec, Ivana Kolingerová, Luka Lukač, Niko Lukač, Simon Kolmanič, Krista Rizman Žalik, Štefan Kohek, 2023, izvirni znanstveni članek Opis: This paper proposes a new string transformation technique called Move with Interleaving (MwI). Four possible ways of rearranging 2D raster images into 1D sequences of values are applied, including scan-line, left-right, strip-based, and Hilbert arrangements. Experiments on 32 benchmark greyscale raster images of various resolutions demonstrated that the proposed transformation reduces information entropy to a similar extent as the combination of the Burrows–Wheeler transform followed by the Move-To-Front or the Inversion Frequencies. The proposed transformation MwI yields the best result among all the considered transformations when the Hilbert arrangement is applied.
Ključne besede: computer science, algorithm, string transformation, information entropy, Hilbert space filling curve
Objavljeno v DKUM: 22.05.2024; Ogledov: 160; Prenosov: 15
Celotno besedilo (26,44 MB)
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