Bioinformatics 2024: Predictions and Challenges
- 3rd January 2024
- Posted by: Breige McBride
- Category: Bioinformatics
We asked our large team of bioinformaticians to give us their thoughts on the topic ‘Bioinformatics 2024’. Specifically, what changes do they expect to see this year and what challenges may bioinformaticians have to overcome?
Their previous predictions have been pretty accurate. For example, one prediction for 2022 was that there would be a shift from data generation to mining public domain data, and data mining went on to become one of our top 3 services that year. Also, at the beginning of 2023, our bioinformaticians predicted the rise of ChatGPT within bioinformatics. ChatGPT certainly made an impact in the bioinformatics field over the last year, as a quick internet search will show. PLOS, National Institutes of Health, and Research Gate all published on the topic of ChatGPT, in relation to bioinformatics, in 2023.
However, these are predictions from previous years. Let’s find out what our bioinformaticians predict about bioinformatics in 2024!
Bioinformatics 2024: Key Predictions
Increasing Popularity of Whole Genome Sequencing
Fios bioinformaticians had lots of thoughts on what to expect in 2024, but there was consensus regarding two areas in particular. Firstly, Whole Genome Sequencing (WGS). This was top of mind for many of our bioinformaticians, who predict that due to the falling costs of long-read sequencing, WGS will increase in popularity in 2024. Some members of the team believe we will see WGS increasingly included in clinical trials to cluster patients. Consequently, they also predict that the use of binary mutation for this purpose will decrease.
More Spatial Data Will be Available/Generated
‘Spatial data’ was another term mentioned again and again when our bioinformaticians shared their thoughts on bioinformatics in 2024. Our team is confident that spatial data will become more widely used. In particular, they expect to be analysing more spatial transcriptomics and spatial proteomics data. They also think that spatial data will be increasingly combined with omics data for analysis.
Other Expectations for Bioinformatics in 2024
Although WGS becoming more popular and increasing generation of spatial data were the leading predictions from our team, they had a lot more to share. For example, some in our bioinformatics team expect 2024 will see lab-based companies increasingly including ‘basic’ bioinformatics outputs with their product offerings. In turn, they expect some study data will not receive the appropriate in-depth analysis it requires, leading to a reduction in study quality. However, on a more positive note, these members of the team also expect that the life sciences industry as a whole will quickly realise the dangers of relying on such ready-made bioinformatics outputs.
Further predictions from the team include:
- More use of public domain resources such as biobanks and public databases
- An increase in genome-wide association studies (GWAS) and phenome-wide association studies (pheWAS). Our team believes that, although many of these studies were previously underpowered, they will be able to provide more reliable results thanks to the increasing availability of large-scale biobanks which can be accessed to support such studies
- Further developments in single-molecule protein sequencing that will lead to it being used more widely.
Bioinformatics 2024: Key Challenges
Data Storage
One challenge in particular is top of mind for our bioinformatics team in 2024, and it is not new. Just like in 2023, they predict that the main challenge in bioinformatics in 2024 will be data storage. This is an ongoing challenge as, with more data becoming accessible every day, and with data sets continually increasing in size, the capacity needed to store it all grows ever-larger. This can lead to difficult decisions for those in charge of data storage. When running out of storage capacity they will need to ask themselves which data to keep, and how long to keep it for?
Working With Large-Scale Data Sets
Such large volumes of data present other challenges in addition to storage. For instance, our team notes that simply handling and analysing large-scale data sets can be challenging. This is due to the volume of data involved. What’s more, the larger data sets become, the more difficult it becomes to integrate them. These are challenges that those working in the field of bioinformatics in 2024 should certainly prepare for.
Many researchers in life science will also face the challenges of working with and storing large data sets. If this is a challenge you face, we can help. As a leading bioinformatics analysis provider, we continually invest in these areas. Thanks to our large capacity computing and secure data storage facilities, when we work on a bioinformatics project for you we store all your raw data, analysed data, and your data analysis report. You can access these via a password-protected html link, without having to worry about storing them yourself. If you would like to learn more, contact us and we will be happy to help!
Misuse of AI
Some of our bioinformaticians anticipate that misuse of AI will be a problem in bioinformatics in 2024. They fear that the use of AI-generated text summaries of bioinformatics analysis data could include false claims or references, as AI-powered large language models are known to ‘hallucinate’. In turn, they worry inaccuracies may be introduced to scientific publications.
Advances to Look Forward to in Bioinformatics, in 2024 and Beyond
Being passionate about bioinformatics, our team are looking forward to certain advances that could impact bioinformatics over the next few years. In particular, they are keen to see how developments in AI, especially in relation to large language models and machine learning, will boost the productivity of bioinformaticians as well as unlock previously inaccessible insights from biological data sets. One particular area where our team think AI will improve the productivity of bioinformaticians is in bioinformatics tool development. They expect AI will be widely used by bioinformaticians to speed up tool development and decrease time spent on the more menial aspects of bioinformatics. Consequently, they believe bioinformaticians will have more time to examine analysis results and their meaning in the wider context of the research area they are contributing to.
The team is also excited by the prospect of long-read sequencing becoming more generalised. One bioinformatician looks forward to how this will improve our understanding of structural variation, methylation, and splicing variation as well as their links to disease and drug discovery.
Our bioinformaticians are also keen to see how, as pan-genome and single-cell technologies become more accessible (which will in turn make pan-genome and single-cell data more accessible) they will positively impact targeted drug discovery.
Finally, what our bioinformaticians are most looking forward to is the increasing availability of public data sets. When commenting on bioinformatics in 2024 they mention this more than anything else. As technological advancements (enabling the collection, storage, and sharing of vast volumes of data), open access initiatives and data sharing mandates continue to increase, so does the amount of publicly available data sets. Our team is excited about the advancements this will enable the scientific community to make as a whole.
Public Data at Fios Genomics
In addition to what more public data means for the scientific community, both our bioinformaticians and the wider Fios Genomics team are excited by what it means for us. More public data means even better data landscaping results for our clients. We use data landscaping to inform our clients of the most relevant publicly available data sets to further their research. This can reduce the time and costs associated with wet lab experimentation and data generation. Also, it can help with hypothesis generation and validation of in-house findings.
More publicly available data sets also give us more options for creating sample bioinformatics reports, to share with you. You can learn more about these below.
Sample Bioinformatics Reports
We have several sample data analysis reports to demonstrate our analysis capabilities across different research areas. These sample reports also showcase the user-friendly and interactive reporting infrastructure we use at Fios Genomics. This is the same report style your bioinformatics analysis results will be provided in when you work with us. To receive a sample bioinformatics data analysis report relevant to your research area, just complete the form below!
Request our Sample Reports
