How to Develop Bioinformatics Software [Step-by-Step] Guide for Beginners

Software development is almost a 50-year-old discovery. The recent establishments in computational fields reflect how software development has revolutionized Bioinformatics and similar sectors.

You might come across the question like what are the steps to develop a bioinformatics tool. For instance, imagine you have a DNA sequence, and you wish to identify similar sequences from an immense repository of the DNA sequence database. To execute such meticulous work, you would need an outstanding tool.

In this article, we will learn how to develop Bioinformatics software step by step as a beginner, using simple resources, coding skills, and basic biological knowledge.

So now the problem is to find DNA sequences similar to the query sequence. Solving this problem is easy. To know-how, keep reading!

How to Develop Bioinformatics Software & Tools Beginners Guide

STAGE 1 : Learning The Basics

Determine the type of software you want to develop. There are two types of software development, first application software development, and second, systems software development. Developing a Bioinformatical tool that meets the need of users is called application development.

Understanding Biology

To design a relevant software, first, you should know what the problems in Biology are. An understanding of the subject, specifically nucleotides, proteins, carbohydrates, lipids, and enzymes, is necessary.

The trending tools in Bioinformatics presently are Molecular Docking and Simulations based. If you capture the basics of biochemistry, you could design tools related to finding the ligand inhibitors for a protein active site. This way, you could contribute to drug discovery, an essential step for therapeutics designing.

Learn The Basic Programming Languages

If you have ideas to solve the biological problems with something logical, then you should try to learn programming languages. Familiarity with coding and programming is important for software development. There are several programming languages that you can learn. Some of them are mentioned below:

  • C programming is the oldest language that is still used for coding. This is used to develop low-level programs and works in coordination with the computer’s hardware. If you wish to develop simple biological tools that could run a search operation in a repository you can use this language.
  • C++ programming- this language is popular among the coders. Chrome, Firefox is built using C++. It is used for creating video games and is always in high demand.
  • Java is a popular language when it comes to bioinformatics tools development. It is easy to run and use Java software as compared to the C++ language. It has been used recently in developing games, business software, and Bioinformatics analysis tools.
  • Python is very common and incredibly easy to learn and apply. Recently python has developed many tools related to analyzing DNA and RNA sequences.
  • Biopython is a specialized language for coding. It is embedded with special biological packages that help in Bioinformatical tools development.
  • BioPerl and BioJava are easy to understand languages. They are the most used programming language for developing Bioinformatics tools.
  • R language is also used sometimes for solving by Bioinformatics problems. You can use it to manipulate the biological data in the database, produce graphs and charts to represent significant data. You could even code a program for Bioinformatical tool using R language.

These languages have been used to solve the following biological problems:

  • 2D and 3D molecular structure visualization and modeling
  • Biological pathway, disease pathway, and network analysis
  • DNA, RNA, and protein sequence editing and primer design
  • Drug discovery and molecular docking
  • Metabolomic, genomics, and proteomic data analysis
  • Microarray analysis
  • Microscope image processing, PCR, mutagenesis, and gel analysis
  • Molecular graphics systems
  • NGS and metagenomics analysis and statistics
  • Sequence alignment and evolutionary relationships

Choose The Appropriate Resources

You should suitably select the programming books, video tutorials, and references while working on developing software. You can look for both websites such as, Khan Academy, and many more to help you with the coding problem.

You can take classes for a short duration and learn fundamental coding.

Find and work on small projects and challenge yourself to solve problems within a short duration using a programming language. It will help you in developing software and your skills.

You must practice regularly to perfect the programming skills and ask questions to fix any loopholes in your program.


STAGE 2 : Program Development

Develop your idea

The first and most important part is to have an idea. If you know the problem very well and also have an enlightening idea to solve it via reliable Algorithms and coding, then the possibility of success is high.

Next, you need to design a document. This document should have an outline of features and the targets you wish to achieve. You can keep track of your progress and see the details you include in the document every day.

User Story

If you are an inexperienced programmer, the task to construct a Bioinformatics tool may be convoluted at first. Divide the project into smaller tasks. Write down the features. It is also called as User Story. User Story adds value for users. It is a brief write-up. It doesn’t include technical details. Keep the user stories visible on a pin board. Complete a task and move it to the “done” section. It is a good approach as a starting point to understand the background of your program.

Collecting Example Data

You need to collect the exact data that will be used by your program. You need to get the unambiguous input files that would be run in the program. Having the exact input and output data helps in the breakdown of the problem into smaller chunks and design the main functions of the program by creating intermediate input data for each of them.

Class responsibility collaboration cards (CRC)

After dividing the program into smaller units, the architecture of the program has to be tailored. You can define the components like classes, models, packages, etc. Assign responsibilities to each one of them. CRC cards are useful to define Central elements to write a prototype and adjusting the details later on.

Write Prototype Program

Now you need to write a basic program that shows the functionality that you are trying to achieve. This program can be called a prototype of a program. It will help you to finalize a code that works efficiently.

For example, if you are creating a DNA sequence alignment software, the prototype would include most of the genomic data and a way to index that data for running easy search operations. You can use the Biopython package for coding the Biological sequence alignment tool. Bioperl and Biojava are also very popular languages.

The prototype can change as you come up with new ideas and tackle the problems.

The prototype is a rough outline. Therefore, it is not supposed to be perfect. It can have drawbacks. You have to correct it as you test your prototype again and again.

Fix The Bugs and Errors

Another important aspect is to find bugs and fix them. Errors in the program are presumed to happen until the finished product runs smoothly. Keep testing the software with your colleagues, analytical community, friends, and others until you have progressive feedback regarding development.


STAGE 3 : Finalization, Validation, and Marketing

Develop User Interface

Now, you need to finalize your project with the ultimate program. Spend time on designing the user interface. It should be clean, error-free, and without any bugs. Finish the product with maximum result capacity.

Validate your Program

GitHub is a community that helps you to share your code with others. You can upload your program or code here and ask for solutions from the people in the group. It is a great learning source, and it will help you to better your program.

Finishing and Marketing

Once you have developed your software, it’s time that you distribute the finished product among the users. One way is to distribute it to small teams of technical developers and make it available through personal websites. You can include screenshots tutorials if you are selling the software. Make sure to have a secure payment system if you are charging for the software.

If your biological tool is available as open-source, you can upload it on your website. You may want to develop it into an app and make it available on the Google Play Store or Amazon app store, or any other platform.


Why Bioinformatical Tools are in High Demand?

The last two decades have witnessed an emerging rise in computer science studies. The conversion of wet labs into dry labs is the latest trend. High-throughput biological data and computational analysis have contributed to solving the next-to-impossible biological problems.

The most recent COVID-19 that took a toll on the world is currently under study extensively using the Bioinformatical tools. The full genome was sequenced with the help of electron microscopy. The crystal structure of SARS-CoV-2 has been isolated too. With the help of Bioinformatical tools such as AutoDockVina, VMD, NAMD, and many more, potential drug inhibitors have been detected.

Looking at the great potential of Bioinformatical tools in producing optimum results in a short period, we can say that the future of Bioinformatics appears bright.

Given below is the statistical analysis on the marketing scope of Bioinformatics tools.

According to, the global bioinformatics market is expected to reach $13901.5 billion by 2023 at a CAGR of 14.5 % during the forecast period.

Why Bioinformatical Tools are in High Demand

The growing demand for nucleic acid and protein analysis is driving the growth of the bioinformatics market. With the introduction of the latest technologies such as Nanopore sequencing and Next Generation Sequencing, the market is expected to come up with better, successful, and accurate solutions.

The market is in demand for fast and accurate bioinformatics tools in order to increase platforms for drug discovery and genomic applications. The information for better treatments and diagnostic tests should be collected.

Due to a reduction in the expense of sequencing, many organizations have taken the initiative to perform sequencing on their own. However, data analysis and interpretation is a more sophisticated process that can be performed with sophisticated tools only.

The lack of standardization in this platform across the industry restraints the growth of this market. Bioinformatics professionals with skills and knowledge of coding programs are also in high demand in the market of software development.

Read our reviews of most used bioinformatics tools:


Important Tips for Designing Bioinformatics Software

Commonly the programmers write a program first and then test it. However, the test-after approach is the inverse method where a programmer writes the test code first and then writes the implementation. It is called TDD.

It is a test function that is written for the part of the code that is going to be written next. The TDD can be used to design an entire program that can be guided in a divide and conquer method. The test usually contains sufficient information that can make you start to code. The larger and complicated pass should be divided into smaller units and more tests should be written.

An advantage of this method is to create strong motivational forces for beginner programmers. To write a test, a programmer should be clear with the entire problem. Writing a test requires a full understanding of the specifications.

With this approach, programmers are more prepared during the implementation period. TDD method produces more reliable and successful codes, although it is a slow process.

Other important tips are:

Important Tips for Designing Bioinformatics Software
Image source: NCBI

This is an efficient method to debug and fix the errors in program. Debugging and writing test goes along simultaneously. The test function can be launched when a bug is detected. The code becomes more reliable without attending the same bug.

Another important step is to deliver programs to users. To enhance functionality and improving the quality of the program, the users must get access to it and provide suggestions for improvements.

Providing a software cookbook is also an excellent idea. It is a collection of practical usage examples of a software library. Instead of writing long descriptions, this would contain the codes and that can be copied and executed directly.

Collaborate with skilled and professional people to guarantee success. Avoid interpersonal frictions, misconceptions, etc.



Start the project with the formalization of the tasks. Gather example data and write short notes or a summary of the project. Start working. Use CRC sheets and simple UML diagrams to facilitate initial design decisions. Work on the prototype.

Perform the automatic test, release the software frequently, use the repository, review the codes, maintain the coding guidelines, and maintain high-quality coding during the process. Some use techniques that make the code reliable, reusable, and readable.

During the training of bioinformaticians, take pieces of advice from people like which test module should be added, should be tested, which class has to be on the same CRC sheet, etc.


The article is a detailed description on how to develop Bioinformatics software step by step. We have discussed details on

  • writing a good software program
  • improving the code quality
  • debugging
  • testing
  • validating
  • marketing

With so many resources around, you can also be a good programmer. All you need is the right amount of focus and clear architecture of workflow.

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