In traditional medicine, a person’s illness is determined by an expert who is looking at the physically observable symptoms. Medicine has always relied on experts (doctors) that have specialized in certain aspects of human health, but with advances in science, new technologies are opening a door to a tremendous amount of new information coming from clinics, research labs and biobanks… Not only is this information very detailed, it also possesses unique properties that require a special skill set to analyze and interpret, often times different from the type of expertise doctors already possess. The approaches of medical analysis changed with inventions and discoveries like the microscope in the 16th century and the cell in the human body in the 17th century. When the X-ray machine was first used in the 19th century, it introduced a new dimension of studying living beings. Mendel’s work in the 19th century and William Bateson’s work in the 20th century ushered a new era for understanding how living beings function. Ever since, there has been a rapid increase in both data and machines that bring us to the role of big data in biology.
What is Big Data? And why is it important?
In a world of supercomputers, data is available to us in huge quantities and these repositories continue to store millions of bytes of data every second even as you read this article. Life sciences are no exception to this. For example, to understand the nature of cancer, doctors and researchers do not just study a single patient. Biomedical data is derived from hundreds of thousands of patients to analyze, process and understand the patterns of cancer across a demographic. The challenge that comes with this huge amount of data is the make it difficult to analyze, process and derive meaningful interpretation from it. This huge collection of data is rightly called Big Data.
The quantity of data available makes finding answers seem like finding a needle in a haystack. Yet it is important to understand and analyze as it answers important questions of our existence. Big Data analysis makes it possible to reach a more meaningful understanding of a disease and of its causes and symptoms. For example, looking at a single patient sample who had breast cancer, one can’t accurately determine determine best practices for patients in certain demographics, age groups, etc. However, it is not a logical solution to understanding breast cancer. This is where big data analysis and bioinformaticians play an important role in helping to make sense of the data available. By analyzing data across multiple dimensions, doctors and researchers understand the probable causes and develop a cure for patients with breast cancer.
Keeping up with this line of thought and the importance of mining the huge amount of data available to us, Pine Biotech in collaboration with the Institute of Genetic Engineering, Kolkata has launched a program called – “Data Science For Biologists”.
Data Science For Biologists – A collaboration between Pine Bio & Institute of Genetic Engineering Kolkata
“Data Science for Biologists” is a program by the Pine BioTech team in collaboration with the Institute of Genetic Engineering, Kolkata to introduce data driven approaches to analyzing biological data. The program commenced on 3rd September, 2019 at the Institute of Genetic Engineering. The introductory workshop was attended by students from the Institute as well as online participants from across the globe. Dr. Mohit Mazumder and Dr. Pratim Chakraborty spoke on the importance of data science its various applications. The participants were introduced to the educational and the analytical platform and given a brief of the upcoming programs.
The registrations for the program are still ongoing, click here to register- https://edu.tbioinfo.com/ige-kolkata
The program will give participants a deeper insight into the role of data science. Big data in biology plays a very important role in helping derive meaningful and logical conclusions. Understanding the biological data will help in answering important questions of life on earth, finding solutions for global health problems and can even help in solving problems like global warming.