# Elastic Multi-scale Mechanisms: Computation and Biological Evolution

@article{Ochoa2017ElasticMM, title={Elastic Multi-scale Mechanisms: Computation and Biological Evolution}, author={Juan G. D{\'i}az Ochoa}, journal={Journal of Molecular Evolution}, year={2017}, volume={86}, pages={47-57} }

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt…

## 7 Citations

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### A Theory of Intrinsic Bias in Biology and its Application in Machine Learning and Bioinformatics

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### Differential Evolution in Wireless Communications: A Review

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It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied and will continue to be utilized in this context.

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This work proposed a new quantile model which is used to fit the machine values of QF of some selected parameters of the Nakagami-m distribution, using the root mean square error as the performance metric.

### Relative distances between homology groups to assess persistent defects in time series

- Computer Science
- 2020

This work presents a methodology based on the definition of homological groups to evaluate persistent anomalies in the structure of the sampled time series and aims to obtain a patient stratification of the time series to customize models in medicine.

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