Wide application of computational biology in genomics, epigenomics, proteomics, and meta-genomics to understand 3D protein structural analysis, protein-protein interactions, and gene sequencing and expression along with increasing R&D in drug designing and disease modeling are key factors contributing to high CAGR of Computational Biology during the forecast period.

Market Size – USD 3.15 billion in 2019, Market Growth - CAGR of 21.7%, Market Trends –technological advancements, research and development of advanced computational tools

According to the current analysis of Reports and Data, the global Computational Biology market was valued at USD 2.86 billion in 2019 and is expected to reach USD 14.54 billion by the year 2027, at a CAGR of 21.7%. Science is massively benefitted from data processing, such as computational biology. Computational biology is an interdisciplinary field of biology that applies computational methods for analyzing biological data, such as genetic sequences, cell populations, and protein samples, to discover new predictions. The computational techniques used in computational biology include analytical methods, mathematical modeling, and simulation. Moreover, new technologies such as sequencing, and high-throughput experimental methods like microarray, yeast two-hybrid, and chip-chip assays are creating enormous and increasing amounts of data that can be analyzed and processed effectively and hassle-free using computational techniques.

The drive-in technological advancements have now opened the door to a world of innovation in the field of healthcare. Computational genetics is disciplinary of computational biology where homology and internal biological mechanism are studied using genome sequencing. The Human Genome Project is a classic example where the whole human genome was sequenced successfully. Computational biology also finds application in neurology, in which it is used to map complex interlinked pathways to visualize 3D simulation models of the brain. The medical advantage of computational biology is anticipated to boost the market during the forecast period. Additionally, computational pharmacology also uses tools of computational biology to visualize and simulate advanced drug-drug interactions in the drug designing process.

Key companies profiled in the report include

Chemical Computing Group, Compugen, Simulation Plus, Genedata, Certara, Insilico Biotechnology, Accelrys, Rhenovia Pharma, Entelos, Nimbus Discovery, and Rhenovia Pharma

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The report is an investigative study that determines market growth and market scope on the basis of market trends, consumer behavior shifts, consumption and production patterns, product portfolio offered by the market, growth rate, drivers and constraints, financial positions, and existing challenges and limitations of the Computational Biology market.

The report discusses in detail the global production capacity, demand and supply ratio, market dynamics, and comprehensive analysis of the competitive landscape. It provides an industry-wide analysis of the market share of each players along with their business portfolio, production and manufacturing capacity, product portfolio, business expansion plans, financial standing, and strategic alliances such as mergers and acquisitions, joint ventures, and collaborations, among others.

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The regional bifurcation of the market analyzes key market segments such as North America, Latin America, Europe, Asia Pacific, and Middle East & Africa. The report discusses in detail the market growth, market size, revenue growth, market share, production and consumption, demand and supply, current and emerging trends, and technological developments in each region.

The key geographical regions analyzed in the market report are:

  • North America (U.S.A., Canada)
  • Europe (U.K., Italy, Germany, France, Rest of EU)
  • AsiaPacific (India, Japan, China, South Korea, Australia, Rest of APAC)
  • Latin America (Chile, Brazil, Argentina, Rest of Latin America)
  • Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)

Computational Biology Market Segmentation based on Types:

Service Type (Revenue, USD Million; 2017–2027)

  • In-house
  • Contract

Application Type (Revenue, USD Million; 2017–2027)

  • Cellular & Biology Simulation
    • Computational Genomics
      • Database
      • Infrastructure / Hardware
      • Software & Services
    • Computational Proteomics
    • Pharmacogenomics
    • Others
  • Drug discovery and disease modeling
    • Target identification
    • Target Validation
    • Lead Discovery
    • Lead Optimization
  • Pre-clinical drug development
    • Pharmacokinetics
    • Pharmacodynamics
  • Clinical trials
    • Phase I
    • Phase II
    • Phase III
  • Human Body Simulation Software

End Use (Revenue, USD Million; 2017–2027)

  • Academics
  • Industry
  • Commercial

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 Further key findings from the report suggest

  • Computational Biology market is growing at a CAGR of 2% in Asia-Pacific due to owing to increased spending on research works in pharmacogenomics and pharmacokinetics in clinical studies for new drugs in the region.
  • In-house services are expected to be the fastest growing service segment during the forecast period 2019-2027. Several funding and R&D initiatives are undertaken by private institutions, and biopharmaceutical companies for the detection of a biomarker for drug development and disorder are driving the market growth.
  • North America region accounted for nearly 45% of the market share in 2019 owing to increasing R&D activities for drug discovery processes and development of new biological computation tools.
  • Several funding and R&D initiatives are undertaken by private institutions, and biopharmaceutical companies for the detection of a biomarker for drug development and disorder are driving the market growth.
  • Computational Genomics segment is expected to witness lucrative growth attributing to the recent technological advancements in cloud computing and other IT technologies. For instance, the Epidemiology and Genomics Research Program (EGRP) grants endowment to research-related activities and related need for personalization in healthcare owing to genetic variations, expanding application in non-oncology diseases,

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