How to Become a Bioinformatics Researcher

This article provides in-depth information into What is a Bioinformatics Researcher? What Bioinformatics Researcher do? Degrees for Bioinformatics Researcher, Steps to become Bioinformatics Researcher and much more.

Bioinformatics Researcher

A bioinformatics researcher’s point is to better comprehend life through an application of a mix of computer science, statistics, life sciences, molecular biology, genetics, chemistry, etc. A bioinformatics analyst tries to display, find, and oversee biological data normally through computational means.

What does Bioinformatics Researcher do ?

Bioinformatics Scientists use computers to store, retrieve, and analyze genetic information. Their work helps pharmaceutical and biotechnology companies develop gene therapies to prevent, treat, and cure illnesses like cancer, Alzheimer’s disease, Parkinson’s disease, arthritis, and even asthma.

  • Study and examine sub-atomic level information.

  • Manipulate database containing genomic and post-genomic data.

  • Design and update informatics tools.

  • Analytically and computationally solve biological problems in order to meet research goals.

  • Work with other biologists and software engineers to develop biological databases.

  • Design bioinformatics endeavors that will enhance well-being or pharmaceutical enterprises.


Steps for becoming Bioinformatics Researcher

1

Procure A Bachelor’s Degree

A few bioinformatics or related interdisciplinary programs are available for undergraduates such as computational biology or biomathematics. Applying to a graduate program in bioinformatics does not require majoring in bioinformatics or a related field. Applicants may have bachelor's degrees in life and physical sciences, computer science, statistics, and math.

2

Get An Internship

Internships are normally required in senior year of undergraduate study. Doing a summer internship in the related field will give students a chance to gain real-world experience. It will also increase your chances to get into a good college for masters.

3

Pursue Master’s Degree

A graduate degree in bioinformatics is not necessary to get an entry-level job but a graduate degree opens up more opportunity for advancement. It is not necessary to get your bachelor’s degree in bioinformatics to qualify to pursue a master in bioinformatics. However, students need to complete prerequisites in subjects that typically include molecular biology, genetics, chemistry, statistics, linear algebra and computer programming.

4

Get Training

Students have an opportunity to get hands-on training during their bachelor’s and master’s program. Several universities offer summer institutes to provide undergraduate students with bioinformatics research experiences. Bioinformatics students may also gain research experience through on-campus research laboratories in genome science or bioinformatics research centers, as well as seek options in companies.

5

Get A Ph.D.

Doctoral projects commonly offer educating and shared research with associations, for example, the National Cancer Institute, the National Institutes of Health and the National Science Foundation.


Bioinformatics Researcher Salaries

Bioinformatics Researcher

Bioinformatics Researcher Degree Levels

Bachelors

A bachelor’s degree in bioinformatics covers both theoretical and practical aspects of biology and computing. It gives students a solid foundation in biology, computer science, mathematics, chemistry, and statistics so that students have the necessary skills to use computing tools to address contemporary problems in biology and medicine.

Molecular Biology
  • DNA Replication

  • Gene structure and transcription

  • RNA Processing

Objectives
  • Understand biological activity at the molecular level

  • Conduct scientific research

  • Implement the scientific method to explain biological phenomena

Programming for Bioinformatics
  • R

  • Python

  • perl

Objectives
  • Coding in the genetic level

  • Solve biological problems

  • Apply computational algorithms

Linear Algebra
  • Matrix operations, including inverses

  • Matrix operations, including inverses

  • Linear models and least-squares

Objectives
  • Study of linear sets of equations

  • Transformation properties

  • Solve systems of linear equations

Masters

Master's programs in bioinformatics can lead to careers working in biotechnology, bioinformatics companies or labs. In master’s program students develop skills in programming, statistical modeling, and other areas of computer science to analyze and interpret complex biological data.

Molecular modeling
  • Molecular Dynamics

  • Monte Carlo Methods

  • First Principles Methods

Objectives
  • Theoretical and computational models

  • Mimic the behavior of molecules

  • Evaluating molecular models

Biochemistry
  • Amino Acids and Protein Structure

  • Enzymes

  • Protein Function

Objectives
  • Chemical process in the living organism
  • Identify polymeric biomolecules

  • Specificity of enzymes

Molecular cell biology
  • Organelles and membrane systems

  • Sterilisation techniques

  • cultivation of eukaryotic cells

Objectives
  • Fundamental discoveries in gene expression

  • Genome organization, cellular morphology

  • Function molecular metabolism

Doctorate

A Ph.D. in bioinformatics, genetics or genomics is generally required to engage in advanced research. Ph.D. programs in bioinformatics emphasize research and lab rotations that are responsive to the evolving nature of bioinformatics and computational biology.

Computational neuroscience
  • Linear algebra

  • Neuroanatomy

  • Hodgkin Huxley model

Objectives
  • Use of mathematical tools and theories

  • Investigate brain function

  • Computation of biological neurons

Macromolecular structure
  • DNA recognition

  • Transcription Factor Binding

  • Catalysis

Objectives
  • Levels of protein structure

  • Enzyme mechanisms

  • Membrane chemistry & architecture

Probabilistic modeling
  • Bayesian statistics

  • Regression

  • Ensemble learning

Objectives
  • Incorporate random variables

  • Probability distribution

  • Cognitive modeling