importance of data science and scenic communication
Science Communication
Background Information
Data science is defined as an interdisciplinary field based on the use of scientific methods, algorithms, systems, and processes to extract knowledge and insights from unstructured and structured data. It has a huge correlation with big data and data mining. Typically, data science is a concept that unifies statistics, machine learning, and data analysis so as to analyze and understand natural phenomena Data science employs many skills, which are adopted from computer science, mathematics, and other disciplines. Generally, data science is essential in enhancing the abilities of scientists to communicate with fellow scientists and non-scientists.
To show the importance of data science and scenic communication, an article by Stephanie, Xiaolu, and Pernilla will be discussed. The title of the article is “Single-cell tracking demonstrates copper chaperone Atox1 to be required for breast cancer cell migration”. The main research question in the article investigates breast cancer cell migration as a function of antioxidant 1 copper chaperone (Atox1). According to Stephanie et al., copped ions are hallmarks of different types of cancers(2019). Despite this fact, the involved mechanisms, involved pathways, and copper-binding proteins are mostly unknown. In this research study, tracking of hundreds of cells, depending on individual situations was done. The tracking was done in nine-horror series, and the results showed that directionality and cell migration velocity were significantly reduced upon Atox 1 silencing in the cells.
Figures descriptions
Figures and data charts are popular ways in which scientists communicate. Through the use of figures, scientists can easily present their results in an easily understandable manner, not just to scientists, but also to non-scientists. It is essential for researchers to use figures that are clear and representative of the actual data collected from a study. In the research article by Stephanie et al., several figures are used to represent the results from their cell tracking experiment. Figures 1 and 3 from the research article are discussed below :
Figure 1
From this figure, one of the trends observed is that the silencing of Atox1 has the effect of reducing the migration velocity and Euclidean distance of breast cancer cells. This answers the specific research questions by the authors on the effects of the silencing of Atox1 on the migration velocity and directionality of breast cancer cells. The data is clearly represented in graphs and models, in such a way that a person with no background information on cancer studies can understand it. The margins or error are also presented in this figure, and this gives readers the ability to understand the accuracy and confidence levels of the data presented.
Figure 3
In this figure, PLAs and bar graphs are used to show the relationship between Atox1, ATP7A, and LOXPP. From the results, it is revealed that Atox1, ATP7A, and LOXPP have high proximity and high correlation. It is also evident from the results that Atox1 levels have a significant impact on LOX activity. The margins of error are also presented in this figure. This is key in understanding the accuracy and confidence levels of scientific data, as per the principles of data science. Generally, this figure represents results that are consistent with the primary research question. The results show that Atox1 plays a significant role in putative cancer cells migration. According to the authors, further studies on the properties of Atox1 could lead to developments of copper depletion therapy in cancer management.
References
Stephanie, B., Zhang, X., & Wittung-Stafshede, P. (2020). Single-cell tracking demonstrates copper chaperone Atox1 to be required for breast cancer cell migration. Proceedings of the National Academy of Sciences.