Sentence examples for development of novel algorithms from inspiring English sources

Furthermore, its current implementation in C++, with a highly modular design of well-documented data structures and functions, offers a convenient environment for the development of novel algorithms.

The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems.

The expansion of computational power, better parameterization of force fields, and the development of novel algorithms to enhance the sampling of the free energy landscapes of proteins have allowed molecular dynamics (MD) simulations to become an indispensable tool to understand the function of biomolecules.

In the future we will seek to further improve our current tradeoff benchmarks with the development of novel algorithms and to apply our techniques to the design of high-multiplexing assays that achieve broad coverage of the complete human genome.

Furthermore, it can be expected that standardization of RPPA data in a common framework can substantially aid the development of novel algorithms and allow better integration at the level of network biology and other multi-OMICS data.

The series of steps involved in these solutions is not yet recorded by Fraxinus, but previous work on the FoldIt game has shown that recording and sharing protein-folding recipes allow rapid development of novel algorithms (Khatib et al., 2011); we are hopeful that similar improvements will be possible with Fraxinus.

With technological developments, introduction of novel algorithms for data analysis and the availability of tools and software, microarray technology has found widespread application in biological research [ 9, 10].

Currently, we have the following article categories: Research articles: these articles should present original research work on the development and analysis of novel algorithms in bioinformatics.

With the continued development and improvement of novel algorithms (Karakoc et al., 2011), the detection of CNVs from next-generation sequence data has improved significantly, but more work needs to be done to capture more complex variation as well as specific classes such as inversions and novel insertions.

The former concentrates on the development and performance testing of novel algorithms and models, the latter focuses on the development and delivery of reliable data products within a pre-defined time schedule [37].

Results like the ones obtained here will anyhow provide new hints for a better understanding of social phenomena that are mediated by new communication platforms and for the development of novel manmade algorithms for effective and costless dissemination (viral) dynamics.