Querying neXtProt nanopublications and their value for insights on sequence variants and tissue expression

Understanding how genetic differences between individuals impact the regulation, expression, and ultimately function of proteins is an important step toward realizing the promise of personal medicine. There are several technical barriers hindering the transition of biological knowledge into the applications relevant to precision medicine. One important challenge for data integration is that new biological sequences (proteins, DNA) have multiple issues related to interoperability potentially creating a quagmire in the published data, especially when different data sources do not appear to be in agreement. Thus, there is an urgent need for systems and methodologies to facilitate the integration of information in a uniform manner to allow seamless querying of multiple data types which can illuminate, for example, the relationships between protein modifications and causative genomic variants. Our work demonstrates for the first time how semantic technologies can be used to address these challenges using the nanopublication model applied to the neXtProt data set, a curated knowledgebase of information about human proteins. We have applied the nanopublication model to demonstrate querying over several named graphs, including the provenance information associated with the curated scientific assertions from neXtProt. We show by way of use cases using sequence variations, post-translational modifications (PTMs) and tissue expression, that querying the neXtProt nanopublication implementation is a credible approach for expanding biological insight.     

Impact of Weather Conditions and Built Environment on Public Bikesharing Trips in Beijing

As bicycling regains popularity around the world, the Beijing Public Bikesharing System, launched in 2012, enables users to access shared bicycles for short trips. After five years of operation, while the system is widely used, it faces the problems of bike unavailability and dock shortage at various stations due to the tidal characteristics of bicycle travel. It is necessary to investigate the influence of different weather conditions and nearby built station environments on bikesharing trips. Using historical trip data from 2016 concerning 543 stations in Beijing, log-linear regression models are developed to estimate the impact of daily weather and time events on bikesharing trips. Moreover, the effects of built environment variables, such as land use and transport infrastructure, are investigated both on workday and non-workday usage at the station level. The results indicate that temperature is not linearly associated with daily usage. Daily usage decreases according to rainfall, snowfall, wind speed and weekends/holidays. Light and heavy pollution have no significant influence on bikesharing demand; however, severe pollution has a negative influence on usage. The effect of transport infrastructure (subway stations, bus stops and bikeway length) is crucial in increasing bikesharing demand. The number of residential and shopping locations is generally associated with usage. Proximity to colleges does not show an obvious usage increase, which is different from the results obtained in other cities. Parks encourage more bikesharing usage on weekends/holidays than on workdays. The findings may help planners or managers to design and modify public bikesharing stations effectively, increasing usage while reducing rebalance costs.

     

语义传感器Web中传感器本体的构建及应用

语义传感器Web的出现为物联网中传感器系统间的数据互操作、信息共享和知识融合提供了实现方式,传感器本体的构建则是实现这些功能的前提.本文在参考万维网联盟提出的语义传感器网络本体的基础上,对传感器及配套的数据采集仪构建了对应的本体,为传感器系统提供了有效的知识组织模型.通过建立的传感器和数据采集仪本体,可以实现传感器的自动分类管理,设定推理规则后可以提供传感器和采集仪间的配接推荐,提高检测现场多传感器系统设计的效率和可靠性,将领域知识应用到系统设计和管理中.最后以具体的传感器实例对推理规则进行了测试,结果满足应用要求.