Mirna Ponce-Flores, Juan Frausto-Solís, Guillermo Santamaría-Bonfil, Joaquín Pérez-Ortega, Juan J. González-Barbosa

Entropy 2020, 22, 89

 

Entropy is a key concept in the characterization of uncertainty for any given signal, and its extensions such as Spectral Entropy and Permutation Entropy. They have been used to measure the complexity of time series. However, these measures are subject to the discretization employed to study the states of the system, and identifying the relationship between complexity measures and the expected performance of the four selected forecasting methods that participate in the M4 Competition. This relationship allows the decision, in advance, of which algorithm is adequate. Therefore, in this paper, we found the relationships between entropy-based complexity framework and the forecasting error of four selected methods (Smyl, Theta, ARIMA, and ETS). Moreover, we present a framework extension based on the Emergence, Self-Organization, and Complexity paradigm. The experimentation with both synthetic and M4 Competition time series show that the feature space induced by complexities, visually constrains the forecasting method performance to specific regions; where the logarithm of its metric error is poorer, the Complexity based on the emergence and self-organization is maximal.

Source: www.mdpi.com

David Fajardo Ortiz, Annie Shattuck, Stefan Hornbostel

 

In the present investigation, we set out to determine and compare the evolution of the research on viral vectors, RNAi and genomic editing platforms as well as determine the profile of the main research institutions and funding agencies. A search of papers on viral vectors RNAi, CRISPR/Cas, TALENs, ZFNs and meganucleases was carried out in the Web of Science. A citation network of 16,746 papers was constructed. An analysis of network clustering combined with text mining was performed. In the case of viral vectors a long term process of incremental innovation in which the clusters of papers are organized around specific improvements of clinical relevance was identified. The most influential investigations on viral vectors were conducted in the United States and the European Union where the main funders were government agencies. The trajectory of RNAi research included clusters related to the study of RNAi as a biological phenomenon and its use in functional genomics, biomedicine and pest control. A British philanthropic organization and a US pharmaceutical company played a key role in the development of basic RNAi research and clinical application respectively, in addition to government agencies and academic institutions. In the case of CRISPR/Cas research, basic science discoveries led to the development of technical improvements, and these two in turn provided the information required for the development of biomedical, agricultural, livestock and industrial applications. The trajectory of CRISPR/Cas research exhibits a geopolitical division of the investigation efforts between the US, as the main producer of basic research and technical improvements, and China increasingly leading the applied research. A set of philanthropic foundations played a key role in specific stages of the CRISPR/Cas research. Our results reflect a change in the model in the financing of science and the emergence of China as a scientific superpower, with implications for the trajectory of development for applications of genomic technologies.

Source: www.biorxiv.org

Klaus Jaffe

 

For the first time, empirical evidence allowed to construct the frequency distribution of an index related to the degree of genetic relatedness between the parents of about 0.5 million humans living in the UK. The results show that a large proportion of the population is not the product of parents choosing a mate randomly. Assortative mating leading to offspring, that occurs between genetic related individuals, is very common. High degrees of genetic relatedness, i.e. extreme inbreeding, is rare. The evidence shows that assortative mating is highly prevalent in this large population sample. This novel empirical result suggests that assuming random mating, as widely done in population genetic studies, is not an appropriate approximation to reality.

Source: www.biorxiv.org