Computational Biology, Bioinformatics, And Biostatistics

?????Computational biology is the study of biological, ecological, behavioural, and social systems through the development and implementation of data-analytical and theoretical methodologies, mathematical modelling, and computational simulation approaches. The field is extensive in scope, encompassing biology, applied mathematics, statistics, biochemistry, chemistry, biophysics, molecular biology, genetics, genomics, computer science, ecology, and evolution, but it is most usually conceived of as the intersection of computer science, biology, and big data. Biological computing, an area of computer engineering that uses bioengineering and biology to create computers, is not the same as computational biology.

Bioinformatics is an interdisciplinary science that develops methods and software tools for analyzing biological data, particularly big and complicated data sets. Bioinformatics is an interdisciplinary discipline of research that analyzes and interprets biological data by combining biology, chemistry, physics, computer science, information engineering, mathematics, and statistics. Bioinformatics has been utilized for mathematical and statistical in silico assessments of biological queries. Bioinformatics include biological research that employ computer programming as part of their approach, as well as repeatable analysis "pipelines," particularly in the field of genomics.

Bioinformatics and computational biology are frequently linked with laboratories, research institutions, and colleges. Because both areas rely on the availability and accuracy of data, they frequently collaborate to achieve their respective project objectives. Bioinformatics focuses on informatics and statistics, whereas computational biology focuses on the development of theoretical methodologies, computational simulations, and mathematical modelling.

The development and use of statistical approaches to a wide range of problems in biology is known as biostatistics (also known as biometry). It includes the planning of biological studies, gathering and analysing data from such experiments, and interpreting the outcomes.

• Integrative Methods
• Network Biology
• Development of Novel Tools and Techniques