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Bioinformatics Market Size 2025-2029

The bioinformatics market size is forecast to increase by USD 15.98 billion, at a CAGR of 17.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the reduction in the cost of genetic sequencing and the development of advanced bioinformatics tools for Next-Generation Sequencing (NGS) technologies. These advancements enable faster and more accurate analysis of genomic data, leading to new discoveries and applications in various industries, including healthcare, agriculture, and research. However, the market faces a major challenge: the shortage of trained laboratory professionals capable of handling and interpreting the vast amounts of data generated by these technologies.
This skills gap poses a significant obstacle to the full realization of the potential of bioinformatics, necessitating strategic investments in workforce development and training programs. Companies seeking to capitalize on the opportunities presented by the market must address this challenge while continuing to innovate and develop sophisticated tools to meet the evolving needs of their customers.

What will be the Size of the Bioinformatics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by advancements in genome editing, data mining, and sequence alignment, among other techniques. Molecular modeling and high-throughput screening are essential tools in drug discovery, while bioimage analysis and gene ontology play a pivotal role in systems biology. Metabolomics data and phylogenetic analysis contribute to a deeper understanding of biological processes.

Machine learning and artificial intelligence are increasingly being integrated into bioinformatics pipelines, enabling more accurate predictions of protein structures, disease modeling, and biomarker discovery. Next-generation sequencing and transcriptomics profiling have revolutionized genomic variation studies, leading to a wealth of new insights. For instance, a recent study employing single-cell sequencing and deep learning identified over 60 distinct cell types in the human brain, expanding our knowledge of neurobiology.

The market is expected to grow at a robust rate, with industry experts projecting a 15% annual increase in demand for these advanced analytical solutions. Genome sequencing, epigenomics studies, RNA interference, and proteomics analysis are just a few more applications of bioinformatics, continually pushing the boundaries of scientific discovery. From gene expression to network analysis, the potential applications of bioinformatics are vast and ever-expanding.

How is this Bioinformatics Industry segmented?

The bioinformatics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Molecular phylogenetics
  Transcriptomic
  Proteomics
  Metabolomics


Product

  Platforms
  Tools
  Services


End-user

  Pharmaceutical and biotechnology companies
  CROs and research institutes
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Application Insights

The molecular phylogenetics segment is estimated to witness significant growth during the forecast period.

In the dynamic and innovative realm of bioinformatics, various techniques and tools are propelling research forward. Molecular phylogenetics, a branch of bioinformatics, is a prime example of this progress. This technique, which uses molecular data to explore evolutionary relationships among species, has significantly advanced our understanding of living organisms in fields such as drug discovery, disease diagnosis, and conservation biology.

For instance, molecular phylogenetics plays a pivotal role in studying viral evolution. By analyzing the molecular data of distinct virus strains, researchers can trace their evolution and uncover their origins and transmission patterns. Furthermore, industry growth in bioinformatics is anticipated to expand by approximately 15% annually, as per recent estimates, underscoring the market's continuous evolution and impact.

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The Molecular phylogenetics segment was valued at USD 4.48 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 43% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the for

RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069). Subsequent statistical analysis determined differentially expressed transcripts ± 1.5-fold change from saline control with P ≤ 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools' predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article "Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling". Resources in this dataset:Resource Title: Supporting information as Excel spreadsheets and tables. File Name: Web Page, url: http://www.sciencedirect.com/science/article/pii/S2352340917304031?via=ihub#s0070

The COVID-19 pandemic has shown that bioinformatics--a multidisciplinary field that combines biological knowledge with computer programming concerned with the acquisition, storage, analysis, and dissemination of biological data--has a fundamental role in scientific research strategies in all disciplines involved in fighting the virus and its variants. It aids in sequencing and annotating genomes and their observed mutations; analyzing gene and protein expression; simulation and modeling of DNA, RNA, proteins and biomolecular interactions; and mining of biological literature, among many other critical areas of research. Studies suggest that bioinformatics skills in the Latin American and Caribbean region are relatively incipient, and thus its scientific systems cannot take full advantage of the increasing availability of bioinformatic tools and data. This dataset is a catalog of bioinformatics software for researchers and professionals working in life sciences. It includes more than 300 different tools for varied uses, such as data analysis, visualization, repositories and databases, data storage services, scientific communication, marketplace and collaboration, and lab resource management. Most tools are available as web-based or desktop applications, while others are programming libraries. It also includes 10 suggested entries for other third-party repositories that could be of use.

Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/.

Bioinformatics Market Outlook

According to our latest research, the global bioinformatics market size reached USD 16.2 billion in 2024, reflecting robust industry momentum. The market is exhibiting a healthy compound annual growth rate (CAGR) of 13.1% and is projected to attain a value of USD 42.7 billion by 2033. This vigorous expansion is driven by the rapid integration of computational tools in life sciences, accelerating advancements in genomics, proteomics, and drug discovery. The increasing demand for personalized medicine and the surge in big data analytics within biological research are pivotal growth factors shaping the bioinformatics landscape.

One of the principal growth factors fueling the bioinformatics market is the explosive rise in genomics research, particularly in the context of next-generation sequencing (NGS) technologies. The cost of sequencing has plummeted over the past decade, making large-scale genomic projects more accessible to both public and private sector entities. This democratization of sequencing technology has led to a significant influx of biological data, necessitating sophisticated bioinformatics tools for analysis, interpretation, and storage. The development of cloud-based bioinformatics platforms further enables researchers to manage and analyze vast datasets efficiently, fostering greater collaboration and innovation in genomics-driven healthcare, agriculture, and environmental sciences.

Another critical driver is the increasing adoption of bioinformatics in drug discovery and development. Pharmaceutical and biotechnology companies are leveraging bioinformatics solutions to accelerate target identification, drug candidate screening, and biomarker discovery. The integration of artificial intelligence (AI) and machine learning algorithms within bioinformatics workflows is enhancing the predictive accuracy of drug response models and facilitating the identification of novel therapeutic targets. This not only shortens the drug development lifecycle but also reduces costs and improves the likelihood of clinical success. As precision medicine gains traction, bioinformatics is becoming indispensable in tailoring treatments based on individual genetic profiles, further propelling market growth across the healthcare sector.

The expanding application of bioinformatics beyond human health is another significant growth factor. In agriculture, bioinformatics is instrumental in crop improvement, pest resistance, and livestock management through the analysis of genomic and phenotypic data. Environmental biotechnology also benefits from bioinformatics in monitoring biodiversity, tracking pathogen outbreaks, and assessing ecosystem health. Moreover, forensic biotechnology utilizes bioinformatics for DNA profiling and criminal investigations. These diverse applications underscore the versatility and critical importance of bioinformatics across multiple sectors, driving sustained investment and innovation in the market.

From a regional perspective, North America continues to dominate the global bioinformatics market, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of major industry players, significant government funding for genomics research, and a well-established healthcare infrastructure. Europe follows closely, supported by strong academic research and collaborative initiatives such as the European Bioinformatics Institute. Meanwhile, the Asia Pacific region is witnessing the fastest growth, fueled by rising investments in life sciences, expanding biotechnology industries, and increasing adoption of digital health solutions. Latin America and the Middle East & Africa are also emerging as promising markets, albeit at a comparatively nascent stage, driven by growing awareness and infrastructural improvements.

Product & Service Analysis

The bioinformatics market by product & service is segmented into software, hardware, and services, each playing a pivotal role in driving the

The Bioinformatics Data Analysis Services market is experiencing robust growth, driven by the exponential increase in biological data generated through next-generation sequencing (NGS) and other high-throughput technologies. The market's expansion is fueled by the rising demand for personalized medicine, precision oncology, drug discovery, and agricultural biotechnology. Advancements in cloud computing and artificial intelligence (AI) are further accelerating the adoption of these services, enabling faster and more efficient analysis of complex datasets. Key players like Illumina, Thermo Fisher Scientific, and QIAGEN are strategically investing in R&D and acquisitions to strengthen their market positions and offer comprehensive solutions. The market is segmented based on service type (e.g., genomics, transcriptomics, proteomics), application (e.g., drug discovery, diagnostics), and deployment mode (cloud-based, on-premise). Competitive landscape is characterized by both large established players and smaller specialized companies focusing on niche applications. While the market faces challenges such as data security concerns and the need for skilled bioinformaticians, the overall growth trajectory remains positive. Looking ahead to 2033, the market is projected to maintain a significant Compound Annual Growth Rate (CAGR), fueled by continuous technological innovation and expanding applications. The increasing accessibility of bioinformatics tools and services, coupled with government initiatives promoting genomic research, will further propel market expansion. The integration of big data analytics and AI will play a critical role in unlocking valuable insights from complex biological datasets, leading to breakthroughs in various healthcare and research domains. Furthermore, strategic partnerships and collaborations between bioinformatics companies and research institutions will contribute to the market's continued growth. Despite potential restraints like regulatory hurdles and the high cost of advanced analytical tools, the long-term outlook for the Bioinformatics Data Analysis Services market remains highly promising.

Detailed Output of 52 Drugs' Pathway EnrichmentEnriched KEGG pathways, DEGs , their respective logfc and p-values can be seen for the comparison of resistant cell lines gene expression versus sensitive cell lines' gene expression to interested and indicated certain drug.

The Bioinformatics Services Market is Segmented by Service Type (Data Analysis, Database Management, and More), Application (Drug Design & Discovery, Genomics & Proteomics, and More), End User (Pharmaceutical & Biotechnology Companies, and More), Deployment Model (On-Premise and Cloud-Based), and Geography (North America, Europe, Asia-Pacific, and More). The Market Sizes and Forecasts are Provided in Terms of Value (USD).

The global Biological Data Analysis Services market is experiencing robust growth, driven by the increasing volume of biological data generated from high-throughput technologies like next-generation sequencing and advanced imaging techniques. The market's expansion is further fueled by the rising demand for personalized medicine, the growing adoption of bioinformatics tools and cloud-based solutions, and increasing investments in research and development across various sectors including pharmaceutical, biotechnology, and academic research. Key application areas such as biomarker identification, biological modeling, and image analysis are witnessing significant traction, contributing substantially to the market's overall growth. The diverse range of services offered, encompassing statistical data analysis and programming, data visualization, and structural biology, caters to the varied needs of researchers and organizations. Segments like biomarker identification and biological modeling are anticipated to exhibit faster growth compared to others owing to their crucial role in drug discovery and development. North America and Europe currently dominate the market, owing to established research infrastructure and higher healthcare expenditure, but the Asia-Pacific region is projected to show rapid growth due to increasing investments in life sciences research and development, and the expanding biotechnology sector. Competitive landscape analysis reveals a mix of large multinational corporations and specialized service providers. While established players like Eurofins Scientific leverage their extensive network and resources, smaller specialized companies are focusing on niche areas such as specific bioinformatics solutions or particular biological data types, offering innovative and tailored services. This competition is driving innovation and improvement in the quality and accessibility of biological data analysis services. Restraints to market growth include the high cost of advanced analytical tools and the need for specialized expertise to handle complex datasets. However, ongoing technological advancements and the development of user-friendly software are mitigating these challenges. Over the forecast period (2025-2033), continued innovation, particularly in AI and machine learning driven analysis, is expected to further fuel market expansion, leading to improved efficiency and affordability of biological data analysis.

Developing bioinformatics for analysis of sequence data from the environment.

The genome sequence of more than 100 Pseudomonas syringae strains has been sequenced to date; however only few of them have been fully assembled, including P. syringae pv. syringae B728a. Different strains of pv. syringae cause different diseases and have different host specificities; so, UMAF0158 is a P. syringae pv. syringae strain related to B728a but instead of being a bean pathogen it causes apical necrosis of mango trees, and the two strains belong to different phylotypes of pv.syringae and clades of P. syringae. In this study we report the complete sequence and annotation of P. syringae pv. syringae UMAF0158 chromosome and plasmid pPSS158. A comparative analysis with the available sequenced genomes of other 25 P. syringae strains, both closed (the reference genomes DC3000, 1448A and B728a) and draft genomes was performed. The 5.8 Mb UMAF0158 chromosome has 59.3% GC content and comprises 5017 predicted protein-coding genes. Bioinformatics analysis revealed the presence of genes potentially implicated in the virulence and epiphytic fitness of this strain. We identified several genetic features, which are absent in B728a, that may explain the ability of UMAF0158 to colonize and infect mango trees: the mangotoxin biosynthetic operon mbo, a gene cluster for cellulose production, two different type III and two type VI secretion systems, and a particular T3SS effector repertoire. A mutant strain defective in the rhizobial-like T3SS Rhc showed no differences compared to wild-type during its interaction with host and non-host plants and worms. Here we report the first complete sequence of the chromosome of a pv. syringae strain pathogenic to a woody plant host. Our data also shed light on the genetic factors that possibly determine the pathogenic and epiphytic lifestyle of UMAF0158. This work provides the basis for further analysis on specific mechanisms that enable this strain to infect woody plants and for the functional analysis of host specificity in the P. syringae complex.

The North America Bioinformatics Market report provides a detailed analysis of emerging investment pockets, highlighting current and future market trends. It offers strategic insights into capital flows and market shifts, guiding investors toward growth opportunities in key industry segments and regions.

Quorum sensing peptides (QSPs) are the signaling molecules used by the Gram-positive bacteria in orchestrating cell-to-cell communication. In spite of their enormous importance in signaling process, their detailed bioinformatics analysis is lacking. In this study, QSPs and non-QSPs were examined according to their amino acid composition, residues position, motifs and physicochemical properties. Compositional analysis concludes that QSPs are enriched with aromatic residues like Trp, Tyr and Phe. At the N-terminal, Ser was a dominant residue at maximum positions, namely, first, second, third and fifth while Phe was a preferred residue at first, third and fifth positions from the C-terminal. A few motifs from QSPs were also extracted. Physicochemical properties like aromaticity, molecular weight and secondary structure were found to be distinguishing features of QSPs. Exploiting above properties, we have developed a Support Vector Machine (SVM) based predictive model. During 10-fold cross-validation, SVM achieves maximum accuracy of 93.00%, Mathew’s correlation coefficient (MCC) of 0.86 and Receiver operating characteristic (ROC) of 0.98 on the training/testing dataset (T200p+200n). Developed models performed equally well on the validation dataset (V20p+20n). The server also integrates several useful analysis tools like “QSMotifScan”, “ProtFrag”, “MutGen” and “PhysicoProp”. Our analysis reveals important characteristics of QSPs and on the basis of these unique features, we have developed a prediction algorithm “QSPpred” (freely available at: http://crdd.osdd.net/servers/qsppred).

Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.

Global Bioinformatics Services market size was USD 3.12 billion in 2023 and is grow to around USD 10.87 billion by 2032 with a CAGR of roughly 14.86%.

In the last decade, High-Throughput Sequencing (HTS) has revolutionized biology and medicine. This technology allows the sequencing of huge amount of DNA and RNA fragments at a very low price. In medicine, HTS tests for disease diagnostics are already brought into routine practice. However, the adoption in plant health diagnostics is still limited. One of the main bottlenecks is the lack of expertise and consensus on the standardization of the data analysis. The Plant Health Bioinformatic Network (PHBN) is an Euphresco project aiming to build a community network of bioinformaticians/computational biologists working in plant health. One of the main goals of the project is to develop reference datasets that can be used for validation of bioinformatics pipelines and for standardization purposes.

Semi-artificial datasets have been created for this purpose (Datasets 1 to 10). They are composed of a "real" HTS dataset spiked with artificial viral reads. It will allow researchers to adjust their pipeline/parameters as good as possible to approximate the actual viral composition of the semi-artificial datasets. Each semi-artificial dataset allows to test one or several limitations that could prevent virus detection or a correct virus identification from HTS data (i.e. low viral concentration, new viral species, non-complete genome).

Eight artificial datasets only composed of viral reads (no background data) have also been created (Datasets 11 to 18). Each dataset consists of a mix of several isolates from the same viral species showing different frequencies. The viral species were selected to be as divergent as possible. These datasets can be used to test haplotype reconstruction software, the goal being to reconstruct all the isolates present in a dataset.

A GitLab repository (https://gitlab.com/ilvo/VIROMOCKchallenge) is available and provides a complete description of the composition of each dataset, the methods used to create them and their goals.

Ameloblastoma is a highly aggressive odontogenic tumor, and its pathogenesis is associated with multiple participating genes. Objective: Our aim was to identify and validate new critical genes of conventional ameloblastoma using microarray and bioinformatics analysis. Methods: Gene expression microarray and bioinformatic analysis were performed to use CHIP H10KA and DAVID software for enrichment. Protein-protein interactions (PPI) were visualized using STRING-Cytoscape with MCODE plugin, followed by Kaplan-Meier and GEPIA analysis that were employed for the candidate's postulation. RT-qPCR and IHC assays were performed to validate the bioinformatic approach. Results: 376 upregulated genes were identified. PPI analysis revealed 14 genes that were validated by Kaplan-Meier and GEPIA resulting in PDGFA and IL2RA as candidate genes. The RT-qPCR analysis confirmed their intense expression. Immunohistochemistry analysis showed that PDGFA expression is parenchyma located. Conclusion: With bioinformatics methods, we can identify upregulated genes in conventional ameloblastoma, and with RT-qPCR and immunoexpression analysis validate that PDGFA could be a more specific and localized therapeutic target.

Bioinformatics Service Market is will grow to reach USD 12.5 Billion by 2035 and compound yearly growth rate CAGR of 14.70% over the course of the forecast period.

Bioinformatics Market, valued at USD 181.47 Billion in 2020, is projected to grow at a compound annual growth rate (CAGR) of 8.9%, reaching approximately USD 869.6 Billion by 2030.

Summary of the skill sets of a bioinformatician, identified by surveying bioinformatics core facility directors and examining bioinformatics career opportunities.