
Gene expression software refers to specialized computer programs and tools designed for the analysis and interpretation of gene expression data. It enables researchers to extract meaningful insights from transcriptomic data generated through techniques like microarrays or high-throughput sequencing. Gene expression software facilitates data preprocessing, normalization, statistical analysis, differential gene expression analysis, pathway enrichment analysis, and visualization of gene expression patterns. It aids in understanding the activity levels of genes, identifying differentially expressed genes between conditions, elucidating molecular mechanisms, and uncovering potential biomarkers or therapeutic targets associated with various biological processes, diseases, or drug responses.
The global Gene Expression Software market was valued at US$ 122 million in 2023 and is anticipated to reach US$ 207.3 million by 2030, witnessing a CAGR of 7.8% during the forecast period 2024-2030.
The industry trend in gene expression software revolves around several key aspects. Firstly, there is a growing focus on integrating multiple analysis techniques within a single software platform, allowing researchers to perform comprehensive transcriptomic analyses, including differential expression, co-expression, and network analyses. Secondly, there is an increasing demand for user-friendly interfaces and intuitive workflows to cater to researchers with varying levels of expertise. Thirdly, the industry is witnessing advancements in data visualization techniques and interactive graphical representations to facilitate the exploration and interpretation of complex gene expression datasets. Additionally, with the rise in multi-omics studies, there is a trend towards integrating gene expression software with other -omics data, such as genomics or proteomics, to enable integrative analyses and a deeper understanding of biological systems. Lastly, there is an increasing focus on cloud-based or web-based solutions that offer scalable data storage, collaboration, and efficient computational resources, making gene expression software more accessible and efficient for researchers globally.
This report aims to provide a comprehensive presentation of the global market for Gene Expression Software, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Gene Expression Software.
Report Scope
The Gene Expression Software market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Gene Expression Software market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Gene Expression Software companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Agilent Technologies
QIAGEN Digital Insights
SAS (JMP Genomics)
DNASTAR, Inc
Illumina
Qlucore
Segment by Type
Web-based
Cloud-based
Segment by Application
Hospitals and Health Systems
Research Organizations
Others
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Gene Expression Software companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Gene Expression Software Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Web-based
1.2.3 Cloud-based
1.3 Market by Application
1.3.1 Global Gene Expression Software Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Hospitals and Health Systems
1.3.3 Research Organizations
1.3.4 Others
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Gene Expression Software Market Perspective (2019-2030)
2.2 Gene Expression Software Growth Trends by Region
2.2.1 Global Gene Expression Software Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Gene Expression Software Historic Market Size by Region (2019-2024)
2.2.3 Gene Expression Software Forecasted Market Size by Region (2025-2030)
2.3 Gene Expression Software Market Dynamics
2.3.1 Gene Expression Software Industry Trends
2.3.2 Gene Expression Software Market Drivers
2.3.3 Gene Expression Software Market Challenges
2.3.4 Gene Expression Software Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Gene Expression Software Players by Revenue
3.1.1 Global Top Gene Expression Software Players by Revenue (2019-2024)
3.1.2 Global Gene Expression Software Revenue Market Share by Players (2019-2024)
3.2 Global Gene Expression Software Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Gene Expression Software Revenue
3.4 Global Gene Expression Software Market Concentration Ratio
3.4.1 Global Gene Expression Software Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Gene Expression Software Revenue in 2023
3.5 Gene Expression Software Key Players Head office and Area Served
3.6 Key Players Gene Expression Software Product Solution and Service
3.7 Date of Enter into Gene Expression Software Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Gene Expression Software Breakdown Data by Type
4.1 Global Gene Expression Software Historic Market Size by Type (2019-2024)
4.2 Global Gene Expression Software Forecasted Market Size by Type (2025-2030)
5 Gene Expression Software Breakdown Data by Application
5.1 Global Gene Expression Software Historic Market Size by Application (2019-2024)
5.2 Global Gene Expression Software Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Gene Expression Software Market Size (2019-2030)
6.2 North America Gene Expression Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Gene Expression Software Market Size by Country (2019-2024)
6.4 North America Gene Expression Software Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Gene Expression Software Market Size (2019-2030)
7.2 Europe Gene Expression Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Gene Expression Software Market Size by Country (2019-2024)
7.4 Europe Gene Expression Software Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Gene Expression Software Market Size (2019-2030)
8.2 Asia-Pacific Gene Expression Software Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Gene Expression Software Market Size by Region (2019-2024)
8.4 Asia-Pacific Gene Expression Software Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Gene Expression Software Market Size (2019-2030)
9.2 Latin America Gene Expression Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Gene Expression Software Market Size by Country (2019-2024)
9.4 Latin America Gene Expression Software Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Gene Expression Software Market Size (2019-2030)
10.2 Middle East & Africa Gene Expression Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Gene Expression Software Market Size by Country (2019-2024)
10.4 Middle East & Africa Gene Expression Software Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Agilent Technologies
11.1.1 Agilent Technologies Company Detail
11.1.2 Agilent Technologies Business Overview
11.1.3 Agilent Technologies Gene Expression Software Introduction
11.1.4 Agilent Technologies Revenue in Gene Expression Software Business (2019-2024)
11.1.5 Agilent Technologies Recent Development
11.2 QIAGEN Digital Insights
11.2.1 QIAGEN Digital Insights Company Detail
11.2.2 QIAGEN Digital Insights Business Overview
11.2.3 QIAGEN Digital Insights Gene Expression Software Introduction
11.2.4 QIAGEN Digital Insights Revenue in Gene Expression Software Business (2019-2024)
11.2.5 QIAGEN Digital Insights Recent Development
11.3 SAS (JMP Genomics)
11.3.1 SAS (JMP Genomics) Company Detail
11.3.2 SAS (JMP Genomics) Business Overview
11.3.3 SAS (JMP Genomics) Gene Expression Software Introduction
11.3.4 SAS (JMP Genomics) Revenue in Gene Expression Software Business (2019-2024)
11.3.5 SAS (JMP Genomics) Recent Development
11.4 DNASTAR, Inc
11.4.1 DNASTAR, Inc Company Detail
11.4.2 DNASTAR, Inc Business Overview
11.4.3 DNASTAR, Inc Gene Expression Software Introduction
11.4.4 DNASTAR, Inc Revenue in Gene Expression Software Business (2019-2024)
11.4.5 DNASTAR, Inc Recent Development
11.5 Illumina
11.5.1 Illumina Company Detail
11.5.2 Illumina Business Overview
11.5.3 Illumina Gene Expression Software Introduction
11.5.4 Illumina Revenue in Gene Expression Software Business (2019-2024)
11.5.5 Illumina Recent Development
11.6 Qlucore
11.6.1 Qlucore Company Detail
11.6.2 Qlucore Business Overview
11.6.3 Qlucore Gene Expression Software Introduction
11.6.4 Qlucore Revenue in Gene Expression Software Business (2019-2024)
11.6.5 Qlucore Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Agilent Technologies
QIAGEN Digital Insights
SAS (JMP Genomics)
DNASTAR, Inc
Illumina
Qlucore
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*If Applicable.
