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Computational biologist skills for your resume and career

Updated January 8, 2025

4 min read

Quoted experts

Joseph Kezele,

Joseph Kezele

Below we've compiled a list of the most critical computational biologist skills. We ranked the top skills for computational biologists based on the percentage of resumes they appeared on. For example, 24.3% of computational biologist resumes contained python as a skill. Continue reading to find out what skills a computational biologist needs to be successful in the workplace.

15 computational biologist skills for your resume and career

1. Python

Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

Here's how computational biologists use python:

Designed and employed ad hoc tools in Perl and Python for analysis and display of complex data sets.
Developed workflow for genotyping including custom script development in Python.

2. Machine Learning

Here's how computational biologists use machine learning:

Developed new bioinformatics methods in RNA-seq variant classification using machine learning.
Used existing machine learning methods and tools such as SVM for the data analysis and trends predictions.

3. Next-Generation Sequencing

Here's how computational biologists use next-generation sequencing:

Build up infra-structure for next-generation sequencing data analysis.
Project 1: Built a clinical bioinformatics pipeline to process the Next-Generation Sequencing Data for Cancer Patients.

4. C++

C++ is a general-purpose programming language that is used to create high-performing applications. It was invented as an extension to the C language. C++ lets the programmer have a high level of domination over memory and system resources. C++ is an object-oriented language that helps you implement real-time issues based on different data functions

Here's how computational biologists use c++:

Designed and wrote code for parallelizing algorithms on a blade farm using an LSF scheduler using C++ on Linux.

5. Visualization

Here's how computational biologists use visualization:

Provided a diversity of data visualization tools.
Designed visualization templates in Plotly (D3) and TIBCO Spotfire to visualize gene expression.

6. Biological Data

Biological Data refers to the information gathered from a living organism. This may be regarding the organism's genetic code, the products made from the organism, or the environment where the organism was found. This information is added to a biological database, which can then be accessed by biologists to review previously gathered data and genetic code.

Here's how computational biologists use biological data:

Managed all of the biological data for the division on DEC VAX and PC computer systems.
Collected vessel activity and biological data while compelling compliance with federal regulations.

7. RNA-seq

Here's how computational biologists use rna-seq:

Performed comparison of RNA-seq and 3'-Tag Digital Gene Expression data to evaluate optimal choice for a study involving human gene expression
Reduced the operation cost of RNA-seq data processing procedure by optimizing and automating the pipeline on HPC clusters.

8. Java

Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

Here's how computational biologists use java:

Prototyped and evaluated algorithms in MATLAB, Java, and C++.
Web site design utilizing PHP, CSS, HTML, MySQL, Java.

9. NGS

Here's how computational biologists use ngs:

Developed best practice documentation for NGS analysis to enable transparent and reproducible data analysis.
Served as scrum master and temporary PM Successfully finished MongoDB NoSQL POC and Cloudera Hadoop POC projects for the NGS data

10. Computational Methods

Here's how computational biologists use computational methods:

Used statistical, mathematical and computational methods to formulate and program mathematical model for computer simulation of biological tissue development.

11. Linux

Linux is a Unix-like operating system. Just like Windows, Mac OS, and IOS, Linux is an operating system used by millions across the globe. Android itself is powered by the Linux operating system. Linux manages all the hardware resources that are associated with your computer. The software is famous because of the protection it grants from viruses, malware, and crashes. The Linux operating system is entirely free and is an open-source software meaning it can be altered by those equipped with the knowledge to code.

Here's how computational biologists use linux:

Performed Linux cluster administration and ensured efficient use of measurement resources throughout facility.
Maintained and increased functionality of automation software tools, internal project web server and Oracle database under Linux system.

12. Unix

UNIX is a computer operating system that was first created in the 1960s and has been constantly updated since then. The operating system refers to the set of programs that enable a machine to function. It is a multi-user, multi-tasking device that works on computers, laptops, and servers. UNIX systems also have a graphical user interface (GUI), similar to Microsoft Windows, that makes it simple to use.

Here's how computational biologists use unix:

Developed UNIX shell script, PERL and AWK program and applied TECPLOT software macro files to automate data processing and report.
Performed genetic research, using tools like GCG, BLAST, FASTA, pFAM on UNIX (SUN Solaris).

13. DNA

Deoxyribonucleic acid, or only DNA, which is considered the king of molecules, is a macromolecule that contains the main component of chromosomes. Shaped like a double helix, DNA is usually found in the nucleus of a cell. It is a type of material that transports characteristics in many forms, developed in nucleotides around one another.

Here's how computational biologists use dna:

Designed experiments to understand DNA damage response pathway dynamics in order to find drug combinations for MM-398 and MM-302 teams.
Conducted Literature annotation of E-coli proteins, particularly transporters, DNA repair, outer membranes and secretion systems for EcoCyc project.

14. New Algorithms

Here's how computational biologists use new algorithms:

Developed new algorithms to analyze the special usage of the new arrays.

15. Perl

A Practical Extraction and Report Language, or simply PERL, is a programming language used for a script intended for syntax. You can see this when a particular web programmer or a junior developer creates a script for servers. It is used to manipulate text and utilize tasks such as web development, programming, and system administration.

Here's how computational biologists use perl:

Designed and developed a methodology for antibody sequence annotation and implemented with PERL.
Created Perl scripts to aid scientists in their data collection, analysis, and results.

What skills help Computational Biologists find jobs?

Tell us what job you are looking for, we’ll show you what skills employers want.

What skills stand out on computational biologist resumes?

Joseph Kezele

Associate Professor of Biology, Arizona Christian University

Electrophoresis, PCR, Chromatography

What soft skills should all computational biologists possess?

Joseph Kezele

Associate Professor of Biology, Arizona Christian University

The ability to think and reason logically. Too many young people cannot do so because they were spoon-fed and then expected to regurgitate that back.

What computational biologist skills would you recommend for someone trying to advance their career?

Christopher Herren Ph.D.

Teaching Assistant Professor, Kansas State University

For a gap year, get a job related to your major.

What type of skills will young computational biologists need?

Meredith O'Hara Ph.D.

Associate Dean at College of Science and Engineering, Houston Baptist University

Regardless of principal or career interest, computer literacy is undoubtedly an imperative skill in today's workforce, and likely this won't change, even after Zoom and other virtual platforms are no longer a necessity for our safety. Even biologists need to be computer savvy to search online databases for protocols and previous research articles, analyze experimental data, and present data in a concise, accurate, and visually-pleasing ways. Another skill biologists will always need is the ability to think independently and collaboratively. This may sound contradictory, but as much as scientists and doctors work independently, their ability and willingness to collaborate is just as important. This becomes even more crucial during times like this when we are facing so many unknowns.

Do you want to know more?

List of computational biologist skills to add to your resume

The most important skills for a computational biologist resume and required skills for a computational biologist to have include:

Python
Machine Learning
Next-Generation Sequencing
C++
Visualization
Biological Data
RNA-seq
Java
NGS
Computational Methods
Linux

Unix
DNA
New Algorithms
Perl
HIV
Data Management
Regression
Experimental Data
Experimental Design
Sequence Analysis
HPC

Novel Algorithms
Computational Support
R
Stem Cells
SNP
Pathogens
Comparative Analysis
PCR
Elisa

Updated January 8, 2025

Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

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