Dataset Information

An Efficient Coding Technique for Stochastic Processes.

ABSTRACT: In the framework of coding theory, under the assumption of a Markov process (Xt) on a finite alphabet A, the compressed representation of the data will be composed of a description of the model used to code the data and the encoded data. Given the model, the Huffman's algorithm is optimal for the number of bits needed to encode the data. On the other hand, modeling (Xt) through a Partition Markov Model (PMM) promotes a reduction in the number of transition probabilities needed to define the model. This paper shows how the use of Huffman code with a PMM reduces the number of bits needed in this process. We prove the estimation of a PMM allows for estimating the entropy of (Xt), providing an estimator of the minimum expected codeword length per symbol. We show the efficiency of the new methodology on a simulation study and, through a real problem of compression of DNA sequences of SARS-CoV-2, obtaining in the real data at least a reduction of 10.4%.

SUBMITTER: Garca JE

PROVIDER: S-EPMC8775014 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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An Efficient Coding Technique for Stochastic Processes.

Garca Jesús E JE González-López Verónica A VA Tasca Gustavo H GH Yaginuma Karina Y KY

Entropy (Basel, Switzerland) 20211230 1

In the framework of coding theory, under the assumption of a Markov process (Xt) on a finite alphabet A, the compressed representation of the data will be composed of a description of the model used to code the data and the encoded data. Given the model, the Huffman's algorithm is optimal for the number of bits needed to encode the data. On the other hand, modeling (Xt) through a Partition Markov Model (PMM) promotes a reduction in the number of transition probabilities needed to define the mode ...[more]

PMID: 35052091

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Project description:Seamounts are ubiquitous in the ocean. However, little is known about how seamount habitat features influence the local microbial community. In this study, the microbial populations of sediment cores from sampling depths of 0.1 to 35 cm from 10 seamount summit sites with a water depth of 1,850 to 3,827 m across the South China Sea (SCS) Basin were analyzed. Compared with nonseamount ecosystems, isolated seamounts function as oases for microbiomes, with average moderate to high levels of microbial abundance, richness, and diversity, and they harbor distinct microbial communities. The distinct characteristics of different seamounts provide a high level of habitat heterogeneity, resulting in the wide range of microbial community diversity observed across all seamounts. Using dormant thermospores as tracers to study the effect of dispersal by ocean currents, the observed distance-decay biogeography across different seamounts shaped simultaneously by the seamounts' naturally occurring heterogeneous habitat and the limitation of ocean current dispersal was found. We also established a framework that links initial community assembly with successional dynamics in seamounts. Seamounts provide resource-rich and dynamic environments, which leads to a dominance of stochasticity during initial community establishment in surface sediments. However, a progressive increase in deterministic environmental selection, correlated with resource depletion in subsurface sediments, leads to the selective growth of rare species of surface sediment communities in shaping the subsurface community. Overall, the study indicates that seamounts are a previously ignored oasis in the deep sea. This study also provides a case study for understanding the microbial ecology in globally widespread seamounts. IMPORTANCE Although there are approximately 25 million seamounts in the ocean, surprisingly little is known about seamount microbial ecology. We provide evidence that seamounts are island-like habitats harboring microbial communities distinct from those of nonseamount habitats, and they exhibit a distance-decay pattern. Environmental selection and dispersal limitation simultaneously shape the observed biogeography. Coupling empirical data with a null mode revealed a shift in the type and strength, which controls microbial community assembly and succession from the seamount surface to the subsurface sediments as follows: (i) community assembly is initially primarily driven by stochastic processes such as dispersal limitation, and (ii) changes in the subsurface environment progressively increase the importance of environmental selection. This case study contributes to the mechanistic understanding essential for a predictive microbial ecology of seamounts.

Dataset Information

An Efficient Coding Technique for Stochastic Processes.

Publications

An Efficient Coding Technique for Stochastic Processes.

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