Sentence examples for evolution and developing from inspiring English sources

These results further highlight the significance of our findings on modeling network evolution and developing model-based methods for ancestral network reconstruction (Navlakha and Kingsford 2011; Zhu and Nakhleh 2012).

Interestingly, organisms that possess elegant and economical organization of their gene network (like the one in Fig. 3) appear to arise in two different ways: either by remaining simple throughout their evolution and developing homeostasis of [A] and [X] through adjustment of kinetic constants alone, or by first becoming highly complex and then going through the process of simplification.

This paper assesses the hydrogeological implications of glacial landscape evolution and develops a conceptual model of glacial landscape evolution and hydrogeological interaction.

In an effort to understand how to improve student learning about evolution, a major thrust of science education research has been to focus on students' naive ideas (misconceptions) about evolution and develop pedagogies to initiate conceptual change (e.g., Demastes et al. 1995).

Taking these correlations together, the dynamics of the tumour progression offers an opportunity to interfere in the tumour evolution and develop a more customized treatment.

Here, we review general arguments for the importance of selection at levels above that of organisms in evolution, and develop them further for a common genomic feature: the carriage of transposable elements (TEs).

In this paper, we introduce an advanced architecture of K-means clustering-based polynomial Radial Basis Function Neural Networks (p-RBF NNs) designed with the aid of Particle Swarm Optimization (PSO) and Differential Evolution (DE) and develop a comprehensive design methodology supporting their construction.

These enhancers might help shed light on the factors driving the evolution of gene regulatory sequences and developing models of enhancer evolution.

In view of this, utilizing other directional crossover and mutation operators to accelerate the evolution of a population and developing new performance indicators to enhance distribution of set-based EAs will be our research topics.

We thank all our colleagues in the genesis and evolution of aptamer science and developing aptamer-based biotechnology over the past decades.

Future research will focus on extending GRFP to model the evolution of noncoding exon, and developing GRFP-based methods for comparative genomics studies.