Overview of What is Bioinformatics

Bioinformatics is the application of computer technology to the understanding and effective use of biological data. In other words, it helps to convert “big data” into “smart data” or knowledge. Computing has become a central component of modern scientific research: large volumes of data (“big data”) are generated by increasingly automated measuring devices. These data need to be stored, organized and analysed to extract new insights and knowledge. Because new discoveries often reveal their relevance when they are compared with the already available knowledge, extensive comparison with large datasets is a great advantage. In addition, computational simulation has become a third pillar of science – along with experimentation and theory – allowing researchers to advance their understanding of complex systems in silico. Continue reading on Swiss Institute of Bioinformatics

 

 

Getting Started With Bioinformatics

Bioinformatics is a field of study that uses computation to extract knowledge from biological data. It includes the collection, storage, retrieval, manipulation and modelling of data for analysis, visualization or prediction through the development of algorithms and software.

Bioinformatics  is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques.

Bioinformatics is both an umbrella term for the body of biological studies that use computer programming as part of their methodology, as well as a reference to specific analysis “pipelines” that are repeatedly used, particularly in the field of genomics. In a less formal way, bioinformatics also tries to understand the organisational principles within nucleic acid and protein sequences, called proteomics. Continue reading on wikipedia