Role of Statistics in Biotech, Medicine and Biomedical Research

Biomedical research is a wide-ranging branch of science that deals with the prevention and treatment of diseases. Handling data, both qualitative and quantitative is an activity professional in this field are constantly engaged in. Hence, the role of statistics in biotech and biomedical research is extremely critical.

Role of Statistics in Biotech & Biomedical Research

By Pavan Somwanshi

The use of statistics in biotech, and especially in biomedical research, begins at the preparation stage, with the most common use being the designing of an experiment. Further, the collected data is analyzed, this helps generate inferences that are valid over a larger population.

The application of statistical ideas to real-world situations in health and illness is highly useful in the planning and execution of biological investigations, clinical trials, and the development of relevant computational algorithms.

Why is Statistics so important in Biotechnology and Biomedical Research?

To guarantee seamless integration of two disciplines, close communication between statisticians, either specialists in that subject or medical research workers with a strong statistical background, is required.

It has often been observed that not everyone thinks of statistics as an important part of medical science and so it has been misunderstood. But the knowledge of statistics now is not only an integral part of medicine but also in most cases is inseparable.

The fact that a researcher cannot refuse to know statistics and make use of it in his or her project is enough to let one know the importance of statistics in medical science.

Top Statistical Methods/Tools Used in Biomedical Research

The estimation of sample size is of prime importance for biomedical studies. It is highly variable depending on the sample population.

Use of Statistics in Biotech and Biomedical Research

Statistical methods and tools come into play to predict reliable sample observations and produce results. They have been a leading contributor to biomedical research.

A biologist does not necessarily have to be a statistician as software tools bridge the divide between the creation and analysis of data to arrive at relevant conclusions.

To provide a brief understanding of the same, I’ve provided below some of the top statistical methods and tools used in biomedical research.

Top Use Cases of Statistics in Biotech & Biomedical Research

Statistical Methods

  • Observational study for example would evaluate the inferences about the effects of a medicine on a group of individuals. In this study, the data is already present. This study might be precursory to an experimental study (mentioned below) and is usually a starting point of research.
  • In an experimental study, researchers take measurements, manipulate the system, and then take measurements again using the same technique. According to a new study from the University of Manchester, a person’s capacity to anticipate the behavior of a group of individuals is linked to their age and gender. Discoveries like these can be made by performing various experimental studies.
  • Multivariate statistical analysis is a combination of many techniques which can be used to understand the relationship among multiple variables. This sort of study is beneficial because researchers frequently hypothesize that a particular outcome of interest is affected or impacted by several factors.
  • Relationship: To understand the relationship between the discipline of statistics and bioinformatics we must understand the levels at which they operate in union and the use cases of statistics in bioinformatics.

Statistical Tools (Software)

  • SAS: SAS is a statistical computer program used in advanced analytics. To mention a couple of uses of SAS, it has been used to study the influence of genetic polymorphisms on complex traits and fitness in plants and the regulation of wing pattern evolution in butterfly by optix gene.
  • ORIGIN is a software used for scientific graphing and data analysis. It has been in use in various analytical studies like electrophysiological analysis & biochemical assays.
  • SigmaPlot is a graphical representation software. SigmaPlot can import both plain and graphical data that will be used for graphical representation. If a graph is to be developed with a different dataset, SigmaPlot can save layouts to make the process of duplicating the format and other adjustments easier.

Role of Bioinformatics

The role of bioinformatics is very essential in today’s research. Bioinformatics, combines mathematics, information science, and biology and helps answer biological questions. Statistical integration in bioinformatics can be observed in areas such as genomic breeding and population genetics.

Other research areas include Statistics, Information technology, computational biology, genomics, plant breeding, population genetics, and mathematical modeling. 

Clinical Trails

Clinical Trials that help determine the efficacy of certain medicine or treatment are planned in an efficient manner taking the help of statistics. Statistics help determine the cause and effect of diseases along with the factors that allow the wider spread of these diseases.

Statistics allow the elimination of hypothetical causes and eventually arrive at an accurate description. On a local level statistics can help plan healthcare systems that operate efficiently with the help of available studies.

The integration and application of statistics in bioinformatics continue to grow as the field gives birth to more invocations.

Related Articles:

Careers in Epidemiology and Biostatistics: Scopes, Courses & Job Prospects

Role of Programming (R & Python) in Biotech and Medicine

4 Best Transferable Skills for PhD in Biomedical Science Applicants

Computational Biology Careers and Jobs

About Pavan Somwanshi:

Pavan_Statistics_Student

Pavan Somwanshi is an India-based freelance content writer and a curious human being trying to learn things every day to make a better sense of the world. Currently, Pavan is studying BSc Statistics from Pune University.

Additionally, Pavan is a management and entrepreneurship aspirant, a tech geek, an occasional philosopher, and a multitasker who excels at juggling tasks on both a professional and personal level.

He follows the liberal and egalitarian schools of thought, respects ideas, and encourages rational debates along with actively engaging in critical thinking. He finds his fulfillment with work, studies, communicating ideas, and being around people he cares about. You can connect with Pavan on LinkedIn.

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