Bioinformatics 2025 Outlook: Thoughts from Bioinformaticians
- 7th January 2025
- Posted by: Breige McBride
- Category: Bioinformatics
What can we expect from bioinformatics in 2025? To find out, we surveyed our large team of bioinformaticians, as we do each year. If you are interested in their outlook on key skills, challenges and advances in the field, read on.
Or, if you would rather check how accurate their predictions have been in previous years first, visit:
The Future of Bioinformatics in 2023
Bioinformatics 2024: Predictions and Challenges
Bioinformatics 2025 Outlook
Most in-demand skills for Bioinformaticians in 2025
When answering the question “What skills do you think will be most in-demand for bioinformaticians in 2025?” the majority of our bioinformaticians included AI and machine learning related skills in their answer. The overall feeling is that experience with machine learning methods and engineering will be in high demand, as well as expertise in training Large Language Models (LLMs). Cloud computing also received a number of mentions as more and more analyses are performed using workflows run on the cloud.
Biological understanding is also a skill area our bioinformaticians believe will be more important than ever in 2025. Answers about this focused on expertise, making the importance of specialised knowledge in fields such as genomics, proteomics and metabolomics, clear. With ‘omics projects varying in type, scale and complexity, and often requiring integration and comparison, specialised biological expertise is in demand in order to derive meaningful conclusions. A general theme running through these answers was related to the bioinformatician career-path. There were comments about it being better to train a biologist to be computational rather than trying to instil biological expertise in someone with a solely computational background. For this reason, we believe the most in-demand bioinformaticians in 2025 will be those with biological backgrounds.
Key Challenges in Bioinformatics in 2025
Artificial Intelligence
Many Fios Genomics bioinformaticians strongly believe that AI will be the biggest challenge facing bioinformatics in 2025. There are a variety of reasons why they believe this. One reason centres on the mushrooming of AI tools available for use in the industry. Although it is positive to have so many AI tools available for bioinformaticians, the process of evaluating their performance is very much trial and error. Therefore, designing reliable performance metrics for AI tools could be one of the biggest challenges this year. However, with so many AI start-ups currently battling for market share, a wait-and-see approach to see which companies (and which respective tools) emerge as the dominant players, may go some way to resolving this challenge.
Another challenge AI presents for bioinformatics in 2025 is how to optimally integrate AI into bioinformatics workflows. For example, data quality and noise can impact the accuracy of AI predictions. Also, many AI techniques require large, well-labelled datasets, which is challenging as a high number of available biological datasets are small or lack sufficient annotation. While AI will be integrated into workflows to assist analyses, it will not be a sufficient replacement for expert analysis by bioinformaticians. This is why our bioinformaticians believe we will start to see a gradual shift in the bioinformatician job role this year. They believe bioinformaticians will become more focused on biological interpretation, and less focused on coding tasks which can be delegated to AI.
Another AI-related challenge facing bioinformatics in 2025 is misunderstanding of AI technology and its applications. For example, as stated above, many AI techniques require large datasets in order to be effective. However, this is not always known to those requesting AI-assisted analyses. In fact, as news spreads about AI being used in bioinformatics, we are likely to see more confusion from non-bioinformaticians about where AI can add value to bioinformatic analyses. Whether or not AI can add value to a bioinformatics project depends on the specific project. In many cases, AI will be unnecessary, or worse – detrimental. Of course, there will be many projects where it can add value to a project. The key is being able to determine which projects will benefit and which will not. Skilled bioinformaticians are those best-placed to make such judgements.
Data Storage and Handling
It is no surprise that our bioinformaticians predict data storage will be a key bioinformatics challenge in 2025, as it has been a major challenge in the industry for some time. Data storage is a challenge due to the sheer volume of biological data that continues to be generated. One contributing factor is the increasing popularity of single-cell data sets, which tend to be large as well as resource intensive. However, as a whole, the industry is seeing larger datasets which require more complex and larger scale processing. In 2025, our bioinformaticians expect to see the current shift to cloud computing accelerate in response, with more data storage and analysis moving to the cloud.
2025 Bioinformatics Predictions
Our bioinformaticians shared their thoughts about the project trends they expect to see in 2025. Their answers show a clear expectation for continued interest in spatial transcriptomics and single-cell projects, with a strong expectation of more single-cell Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) projects. They also predict increasing demand for T-cell receptor (TCR) sequencing and immune profiling.
However, the key area that most of their predictions focus on is AI. Our bioinformatics team believe:
- There will be more interest in how AI and machine learning approaches can be integrated with data analysis
- The tech industry’s focus on AI will lead to better tools to streamline coding
- We can expect more bioinformatics related AI tools such as protein language models (PLMs) to predict protein structures
One bioinformatician also predicts that Google publishing the source code for its AlphaFold 3 AI model will upend small molecule discovery pipelines.
Beyond 2025
Looking beyond 2025, our bioinformaticians also shared thoughts on some developments they expect to see in bioinformatics in the future.
The future they paint is one where large scale population-level genomics data, along with clinical and demographic information, is readily available to researchers. They also expect the current functional analysis standards of hypergeometric tests of GO terms will be superseded by AI-based functional summaries.
Finally, given the growing prominence of precision medicine in bioinformatics research, advancements are also anticipated in the availability of precision medicines for cancer treatment. In fact, one bioinformatician mentioned that they are keen to see the impact of the DETERMINE precision medicine trial, which will match rare cancer patients to treatments based on genetic alterations.
Summary
Our bioinformaticians are clearly aligned in some key areas in their bioinformatics predictions for 2025. They are confident that skills related to AI and cloud computing will be in high-demand, as will bioinformaticians with strong biological backgrounds. Also, they see AI being one of the main challenge areas for bioinformatics, with data storage continuing also to present a challenge this year. When it comes to trends, they anticipate spatial transcriptomics and single-cell projects will be of particular interest. They also believe AI will have a significant impact on the bioinformatics industry this year. They expect AI approaches will be integrated more with data-analysis, and that the next 12 months will see better AI tools becoming available to streamline coding tasks.
Thank you for reading our Bioinformatics 2025 outlook, (and special thanks the Fios Genomics bioinformaticians who made this blog possible). If you would like to discuss bioinformatics with our team in more detail, you can contact us via the form below, and we will be happy to help!
Author: Breige McBride, Marketing Manager, Fios Genomics
Reviewed by Fios Genomics Bioinformatics Experts to ensure accuracy
See also:
Bioinformatics Report Example: Your Data Explained
