Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Recent flood of data from genome sequences and functional genomics i.e. large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. Bioinformatics is conceptualizing biology in terms of macromolecules and then applying "informatics" techniques to understand and organize the information associated with these molecules, on a large-scale.

In this open lecture and fireside chat event, Rezene Habte (a PhD Candidate in Central South University, Changsha, Hunan, China) will present a brief introduction to Bioinformatics and Healthcare Data Science by first providing an introduction to biological terminology and then discussing some classical and advanced bioinformatics problems organized by the types of data sources. Also Mr. Rezene will explain briefly about the healthcare business implications of Bioinformatics.

Over the past ten years, molecular biologists and computer scientists have experimented with various computational methods developed in artificial intelligence. These techniques usefully employed in bioinformatics, both for modeling biological data and for making new discoveries through symbolic machine learning approaches artificial neural networks and genetic algorithms. Prominent examples include knowledge-based and expert systems, qualitative simulation and artificial neural networks and other automated learning techniques. These methods have been applied to problems in data analysis, construction of advanced databases and modeling of biological systems. Practical results are now being obtained, notably in the recognition of active genes in genomic sequences, the assembly of physical and genetic maps and protein structure prediction.

Data science, an umbrella term that encompasses all of the techniques and tools used during the life cycle stages of useful data is widely applied in healthcare data analytics. Healthcare Data Scientist develop forecasting and modeling programs designed to form analyses of medical records or other forms of healthcare information. Sometimes you use the models themselves while in other instances you develop these models so that healthcare workers can use them in their daily practices.

In this unique of its kind event, questions like: What is big data analytics in healthcare? What does a healthcare data scientist do? How Big Data and Bioinformatics change Biology? What Challenges Does Big Data Face? Will be discussed. Also questions related to Business implications of Big Data and Bioinformatics are be addressed. Should have your own question related to biology, bioinformatics and data science, don't hesitate to join us.