Our statistical experts will communicate with the clients to learn better about their needs and goals, and thus provide targeted statistical services based on their experimental purposes and methods.
We design the experimental program structure based on scientific research ideas and provide data collection services for doctors and biomedical researchers. We help you to get the key data you need in advance based on your future business goals, and establish comprehensive data quality standards for the data, as well as production process management solutions that implement the data sources. At the same time, we help you to assess the collection and management of data, predicting the data analysis and subsequent impact of various business adjustments involving critical data, so that you can pre-complete the experimental program.
We will help you to comprehensively analyze data, discover and improve quality audit rules, find out data quality issues, and provide data quality related reports to facilitate customers to display and query analysis audit results, thereby realizing the distribution, processing, review and management of data quality tasks, synchronization, and monitoring. According to the purpose of the experiment, we will choose the most appropriate data analysis method.
We can help you to interpret missing data, correct logic rules, make data corrections, and track and alert data exception as much as possible through predictive analytics to maximize data quality across domains, platforms, and systems.
We guarantee the confidentiality and sensitivity of our customers' data. We are committed to providing you timely and high-quality deliverables. At the same time, we guarantee you cost-effective, complete and concise reports.
If you are unable to find the specific service you are looking for, please feel free to contact us.
References: 1. Mehta, J. P., & Rani, S. (2011) ‘Software and Tools for Microarray Data Analysis’, Gene Expression Profiling, 784, 41-53.2. Sharov AA, et al. (2005) ‘A web-based tool for principal component and significance analysis of microarray data’，Bioinformatics, 21(10), 2548-9.