Math and Programming for BioTechnology and BioInformatics

Bioinformatics is a scientific discipline that deals with the collection, storage, retrieval, processing, analysis, and management of biological information by using computational techniques. This branch of science uses mathematics, statistics, biology, computer programming, and information technology to understand the biological importance of an wide variety of data. Pharmaceutical companies and organisations working in the biotechnology sector use bioinformatics technologies. Bioinformatics is also being increasing used for drug discovery and development process.

Bioinformatics seeks to understand and solve the following the disease-related problems at molecular level:

• Nucleic acid and protein sequencing and analysis
• Find proteins, their interactions, and activity
• Molecular modeling, and molecular dynamics
• Study the function of a molecule based on its structure
• Gene expression, analysis, prediction and establish genomic library.
• Drug designing and discovery

Students often drop out mathematics at higher secondary level (grades 11 and 12) and they feel that if they study biology in future, they don’t have to study mathematics. While this may have been true 20 years back, today mathematics, computer science and programming are essential to study two branches of science that are going to be extremely important – bioinformatics and biotechnology.

Bioinformatics = biology + informatics (information technology) and biotechnology = biology + technology. Both informatics and technology involve study of mathematics, statistics and computer science. So, in a typical bioinformatics and biotechnology course, in addition to subjects from life sciences such as molecular biology, genetics, biochemistry, cell biology, proteomics, immunology, medicinal chemistry, enzymology, industrial psychology and intellectual property rights (IPR), the following subjects based on mathematics, statistics, and computer science are also taught:

Mathematics and Statistics-based courses:

• Mathematical Methods
• Matrices and Determinants
• Differential Calculus
• Integral Calculus
• Linear Algebra
• Eigen Value Problems
• Statistical Methods
• Differential Equations
• Numerical Analysis
• Probability Theory
• Random variables
• Central Limit Theorem
• Distributions – Binomial, Poisson, and Normal distributions
• Test of Hypothesis

Programming and Computer Science Based courses:

• Computer Fundamentals and Networking
• Linux operating system
• Programming (usually two out of Python, C, Java and Perl)
• Microsoft Excel or similar spreadsheet
• Data Structures
• Algorithms and Graph Theory
• Database Management Systems – SQL
• Data Mining
• Web Technologies
• Digital Image Processing
• Data Analysis with R
• Artificial Intelligence
• Machine Learning and Deep Learning Algorithms for Bioinformatics
• Matlab package
• Monte Carlo Simulation
• Markov Chains
• Computer-Aided Drug Designing
• Embedded Systems in Life Sciences

So if you plan to study bioinformatics, biotechnology and other life sciences-based courses, it is better not to drop mathematics and statistics subjects at the higher secondary classes. Bioinformatics is a subject with tremendous potential for research, innovation and entrepreneurship and will be a booming business in 2020s.

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