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More Agility to Semantic Similarities Algorithm Implementations.

ABSTRACT: Algorithms for measuring semantic similarity between Gene Ontology (GO) terms has become a popular area of research in bioinformatics as it can help to detect functional associations between genes and potential impact to the health and well-being of humans, animals, and plants. While the focus of the research is on the design and improvement of GO semantic similarity algorithms, there is still a need for implementation of such algorithms before they can be used to solve actual biological problems. This can be challenging given that the potential users usually come from a biology background and they are not programmers. A number of implementations exist for some well-established algorithms but these implementations are not generic enough to support any algorithm other than the ones they are designed for. The aim of this paper is to shift the focus away from implementation, allowing researchers to focus on algorithm's design and execution rather than implementation. This is achieved by an implementation approach capable of understanding and executing user defined GO semantic similarity algorithms. Questions and answers were used for the definition of the user defined algorithm. Additionally, this approach understands any direct acyclic digraph in an Open Biomedical Ontologies (OBO)-like format and its annotations. On the other hand, software developers of similar applications can also benefit by using this as a template for their applications.

SUBMITTER: Tsaramirsis K

PROVIDER: S-EPMC6982023 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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More Agility to Semantic Similarities Algorithm Implementations.

Tsaramirsis Kostandinos K Tsaramirsis Georgios G Khan Fazal Qudus FQ Ahmad Awais A Khadidos Alaa Omar AO Khadidos Adil A

International journal of environmental research and public health 20191230 1

Algorithms for measuring semantic similarity between Gene Ontology (GO) terms has become a popular area of research in bioinformatics as it can help to detect functional associations between genes and potential impact to the health and well-being of humans, animals, and plants. While the focus of the research is on the design and improvement of GO semantic similarity algorithms, there is still a need for implementation of such algorithms before they can be used to solve actual biological problem ...[more]

PMID: 31905999

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Project description:In vehicle dynamics, it is commonly understood that there is an inverse relationship between stability and maneuverability. However, animal studies have found that stability and maneuverability can coincide. In this study, we examine humans running a reactive agility obstacle and consider the relationship between observational perceived agility and balance, as well as the relationship between quantified surrogates of agility and balance. Recreational athletes (n = 18) completed the agility task while wearing inertial measurement units (IMUs) on their body. The task was also video-recorded. An observational study was completed by a separate group of adults (n = 33) that were asked to view the videos and score each athlete on a Likert scale for balance and for agility. The data from the body-worn IMUs were used to estimate quantified surrogate measures for agility and balance, and to assess if the relationship between the quantified agility and balance was in the same direction as the perceived relationship from the Likert scale responses. Results indicate that athletes that were given a higher Likert agility score were also given a higher balance score (rs = 0.75,p < 0.001). Quantitative surrogates of agility and balance also showed this same relationship. Additional insights on technique for this reactive agility task were informed by the quantitative surrogates. We observed the importance of stepping technique in achieving the faster completion times. The fast performing athletes spent a greater proportion of the task in double support and lower overall time in single support indicating increased periods of static stability. The fast performing athletes did not have a higher body speed, but performed the task with a more efficient technique, using foot placement to enable heading changes, and thus may have had a more efficient path. Similar to animal studies, people use technique to enable agile strategies while also enabling increased balance across the task.

Dataset Information

More Agility to Semantic Similarities Algorithm Implementations.

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More Agility to Semantic Similarities Algorithm Implementations.

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