Recruiter's Glossary

Examples: Capillary Electrophoresis • Epigenetics • Gene Annotation

Bioinformatics

Term from Genetic Research industry explained for recruiters

Bioinformatics is where computer science meets biology. It's a field where specialists use computer tools to make sense of complex biological data, especially genetic information. Think of it like being a detective who uses powerful computer programs to analyze DNA, proteins, and other biological information to help researchers discover new medicines, understand diseases, or improve crops. Some similar terms you might see are "computational biology" or "biological data science." People in this field create and use computer programs that help scientists organize, search through, and understand massive amounts of biological information that would be impossible to analyze by hand.

Examples in Resumes

Developed Bioinformatics pipelines to analyze cancer genomics data

Applied Bioinformatics techniques to process DNA sequencing results

Led a team of researchers using Bioinformatics tools for drug discovery

Used Computational Biology methods to analyze genetic variations

Implemented Bioinformatics workflows for protein structure prediction

Typical job title: "Bioinformaticians"

Also try searching for:

Bioinformatics Scientist Computational Biologist Biological Data Analyst Research Scientist Bioinformatics Engineer Genomics Data Scientist Biomedical Data Scientist

Where to Find Bioinformaticians

Online Communities

Professional Networks

Job Boards

Conferences & Events

Example Interview Questions

Senior Level Questions

Q: How would you design a pipeline for analyzing large-scale genomic data?

Expected Answer: A senior candidate should explain how they would organize a workflow to handle DNA data efficiently, including data quality checks, processing steps, and result validation. They should mention experience with handling large datasets and ensuring accuracy.

Q: Describe a challenging bioinformatics project you led and how you overcame the difficulties.

Expected Answer: Look for answers that demonstrate leadership, problem-solving abilities, and experience managing complex biological data analysis projects. They should explain how they coordinated with wet-lab scientists and other team members.

Mid Level Questions

Q: What methods would you use to analyze gene expression data?

Expected Answer: Should be able to explain in simple terms how they would compare gene activity levels between different samples and what tools they would use. Look for understanding of basic statistical concepts and data visualization.

Q: How do you ensure the quality of your data analysis results?

Expected Answer: Should discuss methods for checking data quality, validating results, and ensuring reproducibility of their analysis. Should mention documentation and version control practices.

Junior Level Questions

Q: What basic file formats are commonly used in bioinformatics?

Expected Answer: Should be able to describe common formats for storing DNA sequences and other biological data, showing they understand the basics of handling scientific data.

Q: How would you approach analyzing a new dataset you've never worked with before?

Expected Answer: Should demonstrate basic understanding of data analysis steps: examining data structure, checking quality, and applying appropriate analysis methods.