#SNP Microarray

[trendingreportz]

Genomics Market - Forecast(2024 - 2030)

Global Genomic Market Overview:

A genome is the genetic material of an organism. It includes both the genes and the noncoding DNA, as well as mitochondrial DNA and chloroplast DNA. The study of genomes is called genomics. The genomics market is gaining traction owing to its applications in various fields of study such as intragenomic phenomenon including epistasis, pleiotropy, heterosis, and other interactions between loci and alleles within the genome. In this era of medical and life science innovations shaping itself as an inevitable uptake for sustainability of mankind, the genomic research is poised for exponential growth owing to imperative genetic innovations feeding off it. Abundant potential has driven this arcade to reach a staggering market size of $16 billion - $16.5 billion as of 2018, and the demand is estimated to increment at formidable CAGR of 9.2% to 10.2% during the forecast period of 2019 to 2025.

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Global Genomic Market Outlook:

Genomics is extensively employed in healthcare, agriculture, biotechnology, DNA sequencing, and diagnostics. In the healthcare segment, genomics is used for the development of vaccines and drugs. This segment leads the application vertical and is growing with a CAGR of 10.1%-10.7 % through to 2025. Genomics plays a significant part in diagnosis of several genetic disorders. It has an ample scope in personalized medication as it can advocate a medical management constructed on the genetic face of a person with the help of clinical data and AI.  It is also applied in synthetic biology and bioengineering. Genomics research in agriculture is hired for plant breeding and genetics to cultivate crop production. The understanding of gene function and the accessibility of genomic maps along with an enhanced understanding of genetic variant will aid the plant breeders to identify the traits and then manipulate those traits to obtain a high yield. All these factors affecting the enormous medical and agricultural sector are all set to stroke the genomics market with abundant demand.

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Global Genomic Market Growth Drivers:

As per the National Center for Biotechnology Information, U.S, the progression in oncology (study and treatment of tumor) expenses is forecast to rise 7%–10% annually throughout 2020, with universal oncology cost exceeding $150 billion[1]. As per the WHO, cancer is a leading cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018[2]. And the total annual economic cost of cancer at the initial period of this decade was estimated at approximately $1.16 trillion. Thus the application of genomics in exploring cell-free circulating DNA by several R&D sectors as a potential biomarker for cancers is driving the market towards exponential growth. The genomics market with its current potential displays all the necessary traits it can adapt in the coming years to divert a huge chunk of traffic and revenue from the omnipresent cancer diagnostics.

As per the Food and Agriculture Organization of United Nations, between 1960 and 1990 the arable land increased by 1.5 billion ha, and in the recent past decades the elevation recorded is just 155 million ha[3]. With decreasing arable floor and the increasing global population augmenting the demand for food by 70% (by 2050), obtaining a high yield is a major trend in the agricultural sector. Genomics market is all set to capitalize on this unprecedented demand scenario. Genomics supplements the understanding of gene function and the accessibility of genomic maps along with an enhanced understanding of genetic variant, thus aiding the plant breeders to identify the traits and then manipulate those traits to obtain a high yield.

After an acute analysis of the regional insights of the global genomics market, North America is revealed to hold 39% to 40% of the entire global market size as of 2018. Such dominance can be attributed to several aspects such as cumulative investment on research by federal administrations, growing patient awareness, and accessibility of urbane healthcare facilities.

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Global Genomics Market Players Perspective:

Some of other key players profiled in this IndustryARC business intelligence report are Beckton Dickson, Synthetic Genomics Inc. (SGI) ,Cepheid, Inc., Affymetrix, Inc., Bio-Rad Laboratories, Inc., Agilent Technologies, GE Healthcare, Illumina, Inc., Danaher Corporation,F. Hoffmann-La Roche, QIAGEN, Thermo Fisher Scientific and PacBio (Pacific Biosciences of California). Majority of the companies mentioned are situated in North America augmenting the regional affluence in the global market.

Global Genomics Market Trends:

High overload owing to a wide range of reagents and consumables has propelled companies into approving different policies to endure in the market and stay ahead of the curve.

For instance, in January 2017, BD launched Precise WTA Reagents for precise and guileless quantification of hereditary data form single cell analysis. Moreover, in July 2016, SGI-DNA entered into a distribution agreement with VWR International, an American company involved in the distribution of research laboratory products, with over 1,200,000 items to more than 250,000 customers in North America and Europe.

Genomics Market Research Scope

The base year of the study is 2018, with forecast done up to 2025. The study presents a thorough analysis of the competitive landscape, taking into account the market shares of the leading companies. It also provides information on unit shipments. These provide the key market participants with the necessary business intelligence and help them understand the future of the Genomics Market. The assessment includes the forecast, an overview of the competitive structure, the market shares of the competitors, as well as the market trends, market demands, market drivers, market challenges, and product analysis. The market drivers and restraints have been assessed to fathom their impact over the forecast period. This report further identifies the key opportunities for growth while also detailing the key challenges and possible threats. The key areas of focus include the types of equipment in the Genomics Market, and their specific applications in different phases of industrial operations.

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Genomics Market Report: Industry Coverage

Types of Solutions Genomics Market:

By Product Types- Microarray chip, Sequencers.

By Application- Genotyping, SNP analysis.

By End-User- Anthropology, Diagnostics.

The Genomics Market report also analyzes the major geographic regions for the market as well as the major countries for the market in these regions. The regions and countries covered in the study include:

North America: The U.S., Canada, Mexico

South America: Brazil, Venezuela, Argentina, Ecuador, Peru, Colombia, Costa Rica

Europe: The U.K., Germany, Italy, France, The Netherlands, Belgium, Spain, Denmark

APAC: China, Japan, Australia, South Korea, India, Taiwan, Malaysia, Hong Kong

Middle East and Africa: Israel, South Africa, Saudi Arabia

[anujmrfr]

Gene Chip Market Size, Growth Outlook 2035

The global Gene Chip Market Size was estimated at 1.97 (USD Billion) in 2024. The Gene Chip Market Industry is expected to grow from 2.11 (USD Billion) in 2025 to 3.94 (USD Billion) till 2034, at a CAGR (growth rate) is expected to be around 7.17% during the forecast period (2025 - 2034).

Market Overview The Gene Chip Market is witnessing significant growth due to the rising adoption of genomics in disease research, personalized medicine, and drug discovery. Gene chips, also known as DNA microarrays, are widely used for gene expression profiling, mutation detection, and genotyping applications. The increasing prevalence of genetic disorders, cancer, and infectious diseases, coupled with advancements in bioinformatics and next-generation sequencing (NGS) technologies, is driving market expansion. Furthermore, growing investments in genomic research and precision medicine are accelerating the demand for gene chip technologies.

Market Size and Share The global Gene Chip MarketSize was estimated at 1.97 (USD Billion) in 2024. The Gene Chip Market Industry is expected to grow from 2.11 (USD Billion) in 2025 to 3.94 (USD Billion) till 2034, at a CAGR (growth rate) is expected to be around 7.17% during the forecast period (2025 - 2034). North America dominates the market due to the presence of major biotechnology firms, well-established research institutions, and high investments in precision medicine. The Asia-Pacific gene chip market is expected to witness the fastest growth, driven by government initiatives in genomics, expanding healthcare infrastructure, and increasing demand for personalized medicine.

Market Drivers

Increasing Prevalence of Genetic and Chronic Diseases: Rising cases of cancer, hereditary disorders, and infectious diseases are boosting demand for DNA microarrays in diagnostic applications.

Advancements in Genomics and Bioinformatics: Integration of artificial intelligence (AI) in gene expression analysis is enhancing the accuracy of gene chip technology.

Growing Adoption of Personalized Medicine: The demand for customized treatment plans based on genetic profiling is fueling market growth.

Rising Investments in Drug Discovery and Development: Pharmaceutical companies are increasingly using gene chip assays for target identification and biomarker discovery.

Challenges and Restraints

High Cost of Gene Chip Technology: DNA microarray platforms can be expensive, limiting accessibility in low-income regions.

Data Complexity and Interpretation Challenges: The vast amount of genetic data generated by microarrays requires advanced bioinformatics tools and expertise.

Competition from Next-Generation Sequencing (NGS): The emergence of NGS technologies is challenging the market share of traditional gene chip platforms.

Market Trends

Miniaturization and Portability of Gene Chips: Development of lab-on-a-chip technologies is enhancing accessibility for point-of-care testing.

Integration of AI in Genomic Data Analysis: AI-powered gene expression analysis is improving accuracy in disease diagnosis and drug response prediction.

Increased Adoption of High-Density Microarrays: Researchers are leveraging high-throughput gene chips for cancer genomics and pharmacogenomics.

Regional Analysis

North America: The largest market due to high R&D investments, government funding for genomics, and strong presence of biotechnology firms.

Europe: Significant market growth driven by precision medicine initiatives and increasing applications in rare disease diagnostics.

Asia-Pacific: Fastest-growing region due to rising demand for personalized medicine, expanding research in genetics, and increasing adoption of gene chip technology.

Rest of the World: Moderate growth, particularly in Latin America and the Middle East, where genomics research is gradually expanding.

Segmental Analysis

By Type:

cDNA Microarrays

Oligonucleotide Microarrays

SNP Microarrays

By Application:

Gene Expression Analysis

Cancer Diagnostics

Pharmacogenomics

Pathogen Detection

Agricultural Genomics

By End-User:

Biotechnology & Pharmaceutical Companies

Academic & Research Institutes

Diagnostic Laboratories

Key Market Players

GE Healthcare

HoffmannLa Roche Ltd

Illumina, Inc.

Danaher Corporation

Siemens Healthineers

Thermo Fisher Scientific

BD (Becton, Dickinson and Company)

Recent Developments

Launch of AI-Based Gene Expression Profiling Platforms: Enhancing the efficiency of genomic data interpretation.

Advancements in Multiplex Microarray Technologies: Improving the sensitivity and specificity of gene chip assays.

Strategic Partnerships Between Pharma and Genomics Firms: Accelerating the development of biomarker-driven drug discovery.

For more information, please visit us at marketresearchfuture.

[globalinsightblog]

"Genetic Mutation Analysis: Unlocking the Secrets of DNA 🧬, $11.3 Billion Market by 2034"

Genetic Mutation Analysis Market is dedicated to identifying and characterizing genetic alterations, offering insights into disease mechanisms, diagnosis, and treatment strategies. Utilizing advanced technologies such as Next-Generation Sequencing (NGS), PCR, and microarrays, this market plays a pivotal role in sectors like healthcare, pharmaceuticals, and research, driving innovations in personalized medicine and genomics.

To Request Sample Report: https://www.globalinsightservices.com/request-sample/?id=GIS10968 &utm_source=SnehaPatil&utm_medium=Article

The market is witnessing robust growth, fueled by the rise of genomics and precision medicine. Oncology leads the market, spurred by the growing prevalence of cancer and the increasing need for targeted therapies. Following closely is the infectious diseases segment, driven by research into viral mutations and the global focus on pandemic preparedness. Regionally, North America dominates the market, supported by strong investments in biotechnology and a well-established healthcare infrastructure. Europe is the second-highest performing region, benefiting from governmental support for genomic research. The United States stands at the forefront, with its advanced technological capabilities and significant research funding. Meanwhile, China is rapidly emerging, bolstered by government initiatives and growing investments in healthcare.

Market Segmentation:

Type: SNP Analysis, CNV Analysis, Large-Scale Mutation Analysis

Technology: Next-Generation Sequencing, PCR, Microarray, Sanger Sequencing, CRISPR

Application: Oncology, Infectious Diseases, Neurological Disorders, Pharmacogenomics

End User: Hospitals, Research Institutes, Pharmaceutical Companies, Diagnostic Labs

In 2023, the market reached 300 million analyses globally, with NGS dominating, capturing 45% of the market share. This growth is attributed to NGS’s cost-effectiveness and high throughput, revolutionizing diagnostics and genetic research.

Key players like Illumina, Thermo Fisher Scientific, and Qiagen are leading market innovations. With projections indicating a 15% CAGR through 2033, the future of genetic mutation analysis is bright, driven by the integration of AI and machine learning for enhanced diagnostic accuracy.

#GeneticMutationAnalysis #Genomics #PersonalizedMedicine #NGS #PCR #Microarrays #CancerTherapies #TargetedTreatments #GeneticResearch #GeneticTesting #HealthcareInnovation #OncologyResearch #InfectiousDiseases #Pharmacogenomics #DataAnalysis #CloudBased #GeneticDiagnostics #AIInHealthcare #PrecisionMedicine #Biotechnology

[farmacuticals]

Competitive Landscape and Key Players in SNP Genotyping Market

The SNP genotyping and analysis market is witnessing remarkable growth, driven by advancements in genomics and an increasing focus on personalized medicine. SNP (single nucleotide polymorphism) genotyping identifies variations in a single nucleotide in a genome, aiding in the study of genetic predispositions to various diseases, drug responses, and genetic traits. This market includes the technologies, tools, and services used to genotype SNPs and conduct analysis, which has widespread applications in research, diagnostics, and drug development. The demand for SNP genotyping and analysis is particularly high in the fields of oncology, pharmacogenomics, and agricultural research, as it enables deeper insights into genetic variations and their impact on individual and population-level health outcomes.

The SNP Genotyping and Analysis Market Size was projected to reach $13.7 billion (USD billion) in 2022 based on MRFR analysis. It is anticipated that the market for SNP genotyping and analysis will increase from 15.11 billion USD in 2023 to 36.6 billion USD in 2032. During the forecast period (2024-2032), the SNP Genotyping and Analysis Market is anticipated to develop at a CAGR of approximately 10.33%.

SNP Genotyping and Analysis Market Share

The SNP genotyping and analysis market share is primarily held by leading companies like Illumina, Thermo Fisher Scientific, and Bio-Rad Laboratories, which offer state-of-the-art genotyping tools, reagents, and software solutions. These companies dominate the market due to their advanced platforms, broad research capabilities, and established partnerships with research and clinical institutions. New market entrants, however, are gaining a foothold by focusing on cost-effective, high-throughput genotyping solutions. The market share is also geographically diverse, with North America and Europe holding prominent shares due to extensive research funding and a large base of biotech companies, while Asia-Pacific is rapidly growing due to expanding healthcare and research infrastructure.

SNP Genotyping and Analysis Market Analysis

SNP genotyping and analysis market analysis indicates significant growth potential due to the rising prevalence of chronic diseases and the increasing demand for genomic data in clinical and research settings. The analysis also shows that innovations in high-throughput sequencing and bioinformatics are facilitating more efficient, cost-effective SNP genotyping. Technologies like microarray analysis and next-generation sequencing (NGS) are key drivers, providing rapid and accurate SNP data at a fraction of traditional costs. This market analysis highlights the impact of growing awareness of genetic testing among patients and healthcare providers, as well as increasing investments by governments and private entities in genomic research. The focus on personalized medicine, where treatments are tailored to individual genetic profiles, is expected to drive continuous demand in the SNP genotyping and analysis market.

SNP Genotyping and Analysis Market Trends

Key SNP genotyping and analysis market trends include the adoption of automation and AI in genomics. AI-powered data analysis helps interpret large datasets generated by SNP genotyping, enabling faster and more accurate insights into genetic associations. Another trend is the increased use of SNP genotyping in non-invasive prenatal testing (NIPT) and newborn screening, which has become an essential aspect of early disease diagnosis and prevention. Furthermore, the integration of genotyping and bioinformatics platforms enables researchers to conduct more comprehensive analyses, streamlining the identification of disease-related SNPs. The growing interest in consumer genomics, where individuals can gain insights into their ancestry and health risks through direct-to-consumer (DTC) testing kits, is also impacting the SNP genotyping and analysis market.

Reasons to Buy the Reports

Market Insights and Forecasts: Detailed projections on the SNP genotyping and analysis market, including future opportunities and growth drivers.

Competitive Landscape: Comprehensive information on market share and strategic positioning of key players, enabling informed decision-making.

Technological Trends: Insights into the latest technological advancements, such as AI integration, next-generation sequencing, and bioinformatics tools in SNP genotyping.

Regional Analysis: Regional breakdowns and growth potential insights to help investors and companies identify high-opportunity areas globally.

Personalized Medicine Focus: Analysis of the expanding role of SNP genotyping in personalized medicine, highlighting its applications in oncology, pharmacogenomics, and genetic testing.

Recent Developments

Recent developments in the SNP genotyping and analysis market reflect a focus on expanding applications and improving technology. In 2023, Thermo Fisher Scientific launched a new NGS-based genotyping platform designed for high-accuracy pharmacogenomic research, enhancing its utility in personalized medicine. Illumina introduced a cost-effective array platform targeting SNP genotyping for agricultural genomics, providing a tailored solution for crop and livestock breeding. Additionally, Bio-Rad Laboratories announced a strategic collaboration to integrate its genotyping software with AI-powered bioinformatics tools, improving analysis speed and accuracy. Advancements in point-of-care (POC) genotyping devices have also been significant, allowing for rapid SNP analysis in clinical settings and contributing to the increased demand in the SNP genotyping and analysis market.

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[coherentmarketupdates]

Demand For Snp Genotyping And Analysis Will Increase As The Prevalence Of Genetic Disorders Rises And New Products Are Published

Single Nucleotide Polymorphism (SNP) addresses the most widely recognized kind of change in genomes of all living things. As an individual DNA test is run in a research center, explicit hereditary variations are recognized by DNA grouping variety tests. Variety is appeared as contrasts in arrangement between various cells. The point of genotyping is to distinguish hereditary varieties that might actually influence an illness or attribute. As a rule, a couple of qualities have numerous varieties, prompting variable quantities of DNA variations (SNPs.) Hence, various tests can be run on similar examples to distinguish contrasts and subsequently acquire data on the genotype of the individual.

For SNP genotyping and analysis, various arrangements of DNA are utilized for every person. Commonly, the whole arrangement of human DNA is utilized for analysis. At times, more limited inclusions and cancellations are made, bringing about minor changes in the succession of the hereditary material. For instance, an individual could have numerous distinctions in the four arrangements of DNA simultaneously however just one single-nucleation change, bringing about a befuddle at the hereditary area.

In the research center setting, SNP genotyping and analysis requires DNA disengagement from a solitary parent of obscure beginning utilizing PCR enhancement of a groundwork and layout got from the person's genome. Preliminary arrangements can be built from amplicons of known changes in the genome. There are three kinds of preliminary utilized for this methodology. These are genotype explicit genomics preliminaries, intergenic preliminary and non-hereditary layout groundwork. Since the areas of transformations are known in people, these groupings are called interchangeable.

Read More : https://bit.ly/3ymU3Te

[orgy-of-nerdiness]

It’s only been 3 weeks and I know it takes 7-9 weeks but I’m already getting impatient about receiving my sequencing results. Like actually it’s kind of ridiculous that it only takes 2 months to get your entire genome sequenced, but I am not a patient person.

[fmi-reports]

Nucleotide Market Key Players, End User, Demand and Consumption by 2030

A recent market study published by Future Market Insights on the Nucleotides market offers global industry analysis for 2014-2018 & opportunity assessment for 2019–2029. The study offers a comprehensive assessment of the most important market dynamics. After conducting a thorough research on the historical, as well as current growth parameters of the Nucleotides market, the growth prospects of the market are obtained with maximum precision.

 Market Segmentation

The global Nucleotides market is segmented in detail to cover every aspect of the market and present complete market intelligence to readers.

Technology 

·         TaqMan allelic discrimination

·         Gene chips & microarrays

·         SNP by pyrosequencing

·         Others

Application 

·         Pharmaceuticals

·         Diagnostics research

·         Food & beverage additive

·         Animal feed additive

·         Others

Region

·         North America

·         Latin America

·         Europe

·         East Asia

·         South Asia

·         Oceania

·         MEA

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Report Chapters

Chapter 01 - Executive Summary

The executive summary of the Nucleotides market includes the market proprietary wheel of fortune, demand-side and supply-side trends, opportunity assessment, and recommendations on the global Nucleotides market.

Chapter 02 – Market Introduction

Readers can find the detailed segmentation and definition of the Nucleotides market in this chapter, which will help them understand basic information about the Nucleotides market. This section also highlights the inclusions and exclusions, which help the reader understand the scope of the Nucleotides market report.

Chapter 03 – Market Background

The associated industry assessment of the Nucleotides market is carried out in this section. The macroeconomic factors affecting growth of the Nucleotides market are provided in this section and the impact of these macroeconomic indicators on the Nucleotides market is analyzed. The processing overview and technological advancements in the Nucleotides market is also provided.

Chapter 04 - Global Nucleotides Market Value Chain

Profit margins at each level of the Nucleotides market are analyzed and readers can find detailed information on top importers and exporters as well as the value chain of the Nucleotides market.

Chapter 05 – Market Dynamics

The drivers and restraints impacting the growth of the Nucleotides market are explained in this chapter. Opportunities and ongoing trends in the Nucleotides market are also comprehensively discussed.

Chapter 06 – Global Nucleotides Market Analysis and Forecast 2014-2029

This chapter includes detailed analysis of the historical Nucleotides market (2014-2018), along with an opportunity analysis for the forecast period (2019-2029). Readers can also find the absolute $ opportunity for the current year (2019 – 2020) and incremental opportunity for the forecast period (2019-2029).

Chapter 07 – Global Nucleotides market Analysis 2014-2018 & Forecast 2019-2029 by Technology

Based on Technology, the Nucleotides market is segmented into TaqMan allelic discrimination, gene chips & microarrays, SNP by pyrosequencing, and others. In this chapter, readers can find information about key trends and developments in the Nucleotides market and market attractiveness analysis based on raw material.

Chapter 08 – Global Nucleotides market Analysis 2014-2018 & Forecast 2019-2029 by Application

Based on Application, the Nucleotides market is classified into pharmaceuticals, diagnostics research, food & beverage additive, animal feed additive, and others. This part also offers market attractiveness analysis based on Application.

Chapter 09 – Global Nucleotides market Analysis 2014-2018 & Forecast 2019-2029 by Region

This chapter explains how the Nucleotides market is anticipated to grow across various geographic regions such as North America, Latin America, Europe, South Asia, East Asia, Oceania, and Middle East and Africa.

Chapter 10 – North America Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

This chapter includes a detailed analysis of the growth of the Nucleotides market in North America, along with a country-wise assessment that includes the U.S. and Canada. Readers can also find regional trends, regulations, and market growth based on end users and countries in the North America region.

For more insights into the market, request a sample of this report@ https://www.futuremarketinsights.com/reports/sample/rep-gb-11035

Chapter 11 – Latin America Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

Readers can find detailed information about several factors, such as the pricing analysis and regional trends, which are impacting growth of the Nucleotides market in Latin America. This chapter also includes growth prospects of the Nucleotides market in leading LATAM countries such as Brazil, Mexico, and the Rest of Latin America.

Chapter 12 –Europe Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

Important growth prospects of the Nucleotides market based on its end users in several countries such as Germany, U.K., France, Italy, Spain, BENELUX, Nordic, Russia, Poland, and the Rest of Western Europe are included in this chapter.

Chapter 13 – South Asia Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

In this chapter, readers can find information about key trends and developments in the key countries of South Asia such as India, Thailand, Malaysia, Indonesia, Singapore, and Rest of South Asia Nucleotides market.

Chapter 14 – East Asia Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

This chapter includes a detailed analysis of the growth of the Nucleotides market in the East Asia region, along with a country-wise assessment that includes, Japan, China, and South Korea. Readers can also find regional trends, regulations, and market growth based on end users and countries in the APEJ region.

Chapter 15 – Oceania Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

This chapter offers insights into how the Nucleotides market is expected to grow in major countries in the Middle East region such as Australia and New Zealand, during the forecast period 2019-2029.

Chapter 16 – Middle East & Africa Nucleotides market Analysis 2014-2018 & Forecast 2019-2029

This chapter contains information about the market growth of Nucleotides in Middle East region such as GCC Countries, South Africa, North Africa, and the Rest of Middle East, during the forecast period 2019-2029.

Chapter 17 – Competition Assessment

In this chapter, readers can find detailed information about tier analysis and market concentration of the key players in the Nucleotides market along with their market presence analysis by region and product portfolio.

Chapter 18 – Competition Deep-Dive

In this chapter, readers can find a comprehensive list of leading manufacturers in the Nucleotides market, along with detailed information about each company, which includes company overview, revenue shares, strategic overview, and recent company developments. Some of the market players featured in the report are Ohly GmbH, Nanjing Bio Together Co., Ltd., Agilent Technologies Inc., PR Omega Corporation, Biorigin, Meihua Group, Star Lake Bioscience Co., NuEra Nutrition, Lallemand Inc., Affymetrix Inc., DSM Nutritional Products Ltd., F. Hoffmann-La Roche Ltd., ThermoFisher Scientific Inc., and CJ CheilJedang Corporation.

Chapter 19 – Assumptions and Acronyms

This chapter includes a list of acronyms and assumptions that provide a base to the information and statistics included in the Nucleotides report.

Chapter 20 – Research Methodology

This chapter helps readers understand the research methodology followed to obtain various conclusions, as well as important qualitative and quantitative information, on the Nucleotides market.

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 About FMI

Future Market Insights (FMI) is a leading provider of market intelligence and consulting services, serving clients in over 150 countries. FMI is headquartered in Dubai, the global financial capital, and has delivery centers in the U.S. and India. FMI’s latest market research reports and industry analysis help businesses navigate challenges and make critical decisions with confidence and clarity amidst breakneck competition. Our customized and syndicated market research reports deliver actionable insights that drive sustainable growth. A team of expert-led analysts at FMI continuously tracks emerging trends and events in a broad range of industries to ensure that our clients prepare for the evolving needs of their consumers.

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[perfectlytinyworkspace]

DNA polymorphisms

DNA polymorphism (DNAPM) – segment of genomic DNA that differs from others in an individual

DNAPMs can be single nucleotide variations, small insertions or deletions, duplications / number of duplications in or of a segment

most are anonymous DNA polymorphisms which are not phenotypically reflected in any way

5000 out of millions of DNAPMs actually alter amino acid sequences in humans 

context: less than 2% of human gDNA makes expressed codons out of 3E9 bp total haploid h-genome | 5% are coding sequences

also, codons can be spliced out and are degenerate anyway - so majority of human genome is non-expressed

still, non-expressed anonymous DNAPMs are experimentally useful – serve as markers for locating linked, co-inherited disease mutations

types of DNA polymorphisms

1. single nucleotide polymorphism (SNP) – difference in one sole base pair between individuals and populations

in a bi-allelic SNP, changed allele is the derived allele and unchanged allele is the ancestral allele | most SNPs thus show low heterozygosity

SNPs occur with low frequency and thus can reflect relative timing of a SNP group’s divergence from a common ancestor species or ancestral population

when using SNPs to order ancestral diversion events, careful of reversion derived mutation that seems to indicate a doubly-derived individual or population’s closer relation to the ancestral group 

RFLPs are SNPs that specifically affect particular RE recognition sites, altering recog. sequence and losing the cut spot or creating new recog. sequence

2. deletion-insertion polymorphism (DIP) – difference in number of base pairs present

less frequent due to tendency to more heavily alter coded information in DNA sequence

often 1-2 bp only, resulting from DNA replication or recombination mistakes or breaks in DNA

in promoter and coding regions, DIPs cause frameshift mutations unless in multiples of 3 for trinucleotidic codon-based reading frames

3. simple sequence repeat (SSR) – aka microsatellite, difference number of tandem duplicates of a basic repeated sequence (≤ 10 bp)

SSR occurrence = most often silent and in non-coding areas 

SSRs in coding regions have dire consequences on phenotype and are generally lethal or severely debilitating

initial creation of repeated sequence is infrequent, but once created the SSR causes DNAP to slip and generate more repeats during replicative synthesis → so, many SSRs = highly polymorphic on an individual or population level

stability + high polymorphism rate (high heterozygosity) = good marker for linked disease alleles (i.e., disease allele is linked to n repeat number at SSR | non-disease allele linked to n+a repeat number)

4. copy number variant (CNV) – difference in number of tandem duplicates of a larger repeated sequence (≥ 10 bp)

mostly stable and inherited rather than newly mutated in an individual | serves as a good pedigree marker for a linked disease allele in a family

CNVs increase possibility of unequal crossing over between homologs that results in larger or smaller number of repeats

genotype anonymous DNA polymorphisms to:

1. map regions in the physical genome and locate linked disease gene loci

» requirements for assessed individuals 

different phenotypes in a single relevant gene

heterozygous individuals to assess recombination in

many individuals to test for recombination frequencies

» requirements for isolated DNAPM marker

1 DNAPM occurs every 1kb » can calculate number of DNAPMs available for mapping along gene via number of possible DNAPMs for mapping = gene length • 1 DNAPM / 1000 bp

must be unique and detectable in individual’s genome to work as a marker, as indicated by name

direct detection: if DNAPM is the disease-causing mutation, then DNAPM shows perfect linkage to disease gene

indirect detection: if DNAPM is not the disease-causing mutation but only closely linked to it, then DNAPM-disease allele recombination must be taken into account when assessing individual genotypes

» determining marker SNP original and variant allele sequences

use restriction fragment length polymorphisms (RFLPs)

RFLPs are relatively rare, but very detectable via probe bind, RE cut, and Southern Blot

added or removed site results in differing sizes of fragments hybridized to the probe

location of probe can indicate varied RE site location + reasons for why fragment lengths are or are not visualized

use allele-specific oligonucleotides (ASOs) in a DNA microarray

attach an ASO – oligonucleotide strand with specific SNP allele – to a fluorescence-detecting chip

fragment genomic DNA into probe-like pieces, amplify, and place on replica nylon membranes for each SNP allele

hybridize gDNA to ASO in high-stringency conditions on each membrane and measure degree of fluorescence to determine whether specific SNP allele is present

use single nucleotide primer extensions with specific primers and ddNTPs

less time-consuming than ASOs, so SNPE is a high-throughput technique, many samples at fast pace

sequence a primer for segment preceding location of SNP, so that primer ends on the base pair immediately before the SNP base

mix with sample in four different wells/tubes and add a different non 3′OH ddNTP to each so that primer is terminated after 1 base addition

if ddNTP complements allelic base at the SNP locus, the sample is visualized to be 1bp longer under gel electrophoresis 

» detection of DNAPMs and associated disease alleles take place across Southern Blotting of family pedigrees

determine the following before labelling which DNAPM fragments are associated with mutant or WT disease alleles:

disease gene dominance, DNAPM linkage to disease gene, and individuals’ disease genotypes

more informative markers determine P(diseased), less informative markers assess P(non-diseased)

disease probabilities derived from less tightly-linked DNAPM markers must take linkage RFs into account

2. identify individuals for forensic purposes

» use SSR-allele combinations to identify specific individuals by their DNA fingerprint

probability of unique SSR repeat-number combination at multiple SSR loci = extremely small, so individual’s multi-SSR (13) genotype ≈ a DNA fingerprint

to determine individual’s multi-SSR (13) genotype, use PCR amplification of DNA sample with each SSR primer differentially fluorescent-labeled

using gel electrophoresis, assess fragment sizes for allele present at each color-distinct locus

» moral question: family members’ DNA can be utilized to identify criminals forensically, but the strategy places relatives under constant surveillance

[deez-no-relation]

"DNA testing can be done as early as the end of the first trimester of pregnancy, starting any time after the 8th week with the SNP microarray procedure, or during the 10th week through the CVS procedure."

So they had more than enough time to get that done before announcing. Good to know, thank you!

[odohring-blog]

Previous academic work and contributions to pharmaceutical conferences

I am Orlando Dohring. This page lists previous academic work and contributions to pharmaceutical conferences. Firstly, links to those documents are provided. Then, further down, I list the abstracts for those documents. Academic work: - PhD Thesis: Identification of breed contributions in crossbred dogs

  - MPhil Thesis: Peak selection in metabolic profiles using functional data analysis

  Contributions to Statisticians in the Pharmaceutical Industry (PSI) conference: - Talk PSI 2018: Introduction to Machine Learning for Longitudinal Medical Data

- Poster PSI 2017: Big Data Meets Pharma

- Poster PSI 2016: Sparse Principal Component Analysis for clinical variable selection in longitudinal data

- PhD Thesis Abstract: Identification of breed contributions in crossbred dogs: There has been a strong public interest recently in the interrogation of canine ancestries using direct-to-consumer (DTC) genetic ancestry inference tools. Our goal is to improve the accuracy of the associated computational tools, by developing superior algorithms for identifying the breed composition of mixed breed dogs. Genetic test data has been provided by Mars Veterinary, using SNP markers. We approach this ancestry inference problem from two main directions. The first approach is optimized for datasets composed of a small number of ancestry informative markers (AIM). Firstly, we compute haplotype frequencies from purebred ancestral panels which characterize genetic variation within breeds and are utilized to predict breed compositions. Due to a large number of possible breed combinations in admixed dogs we approximately sample this search space with a Metropolis-Hastings algorithm. As proposal density we either uniformly sample new breeds for the lineage, or we bias the Markov Chain so that breeds in the lineage are more likely to be replaced by similar breeds. The second direction we explore is dominated by HMM approaches which view genotypes as realizations of latent variable sequences corresponding to breeds. In this approach an admixed canine sample is viewed as a linear combination of segments from dogs in the ancestral panel. Results were evaluated using two different performance measures. Firstly, we looked at a generalization of binary ROC-curves to multi-class classification problems. Secondly, to more accurately judge breed contribution approximations we computed the difference between expected and predicted breed contributions. Experimental results on a synthetic, admixed test dataset using AIMs showed that the MCMC approach successfully predicts breed proportions for a variety of lineage complexities. Furthermore, due to exploration in the MCMC algorithm true breed contributions are underestimated. The HMM approach performed less well which is presumably due to using less information of the dataset. - MPhil Thesis Abstract: Peak selection in metabolic profiles using functional data analysis: In this thesis we describe sparse principal component analysis (PCA) methods and apply them to the analysis of short multivariate time series in order to perform both dimensionality reduction and variable selection. We take a functional data analysis (FDA) modelling approach in which each time series is treated as a continuous smooth function of time or curve. These techniques have been applied to analyse time series data arising in the area of metabonomics. Metabonomics studies chemical processes involving small molecule metabolites in a cell. We use experimental data obtained from the COnsortium for MEtabonomic Toxicology (COMET) project which is formed by six pharmaceutical companies and Imperial College London, UK. In the COMET project repeated measurements of several metabolites over time were collected which are taken from rats subjected to different drug treatments. The aim of our study is to detect important metabolites by analysing the multivariate time series. Multivariate functional PCA is an exploratory technique to describe the observed time series. In its standard form, PCA involves linear combinations of all variables (i.e. metabolite peaks) and does not perform variable selection. In order to select a subset of important metabolites we introduce sparsity into the model. We develop a novel functional Sparse Grouped Principal Component Analysis (SGPCA) algorithm using ideas related to Least Absolute Shrinkage and Selection Operator (LASSO), a regularized regression technique, with grouped variables. This SGPCA algorithm detects a sparse linear combination of metabolites which explain a large proportion of the variance. Apart from SGPCA, we also propose two alternative approaches for metabolite selection. The first one is based on thresholding the multivariate functional PCA solution, while the second method computes the variance of each metabolite curve independently and then proceeds to these rank curves in decreasing order of importance. To the best of our knowledge, this is the first application of sparse functional PCA methods to the problem of modelling multivariate metabonomic time series data and selecting a subset of metabolite peaks. We present comprehensive experimental results using simulated data and COMET project data for different multivariate and functional PCA variants from the literature and for SGPCA. Simulation results show that that the SGPCA algorithm recovers a high proportion of truly important metabolite variables. Furthermore, in the case of SGPCA applied to the COMET dataset we identify a small number of important metabolites independently for two different treatment conditions. A comparison of selected metabolites in both treatment conditions reveals that there is an overlap of over 75 percent. - Talk PSI 2018 Abstract: Introduction to Machine Learning for Longitudinal Medical Data: In the era of big data, there has been a surge in collected biomedical data, which has provided ample challenges for distributed computing but also posed novel inference questions. Application areas range from Bioinformatics (disease diagnosis from microarray data, drug discovery from molecular compounds), medical imaging (brain reconstruction, organ segmentation, tumour detection from MRI/CT/X-Ray images), sensing (anomaly detection, human activity recognition from images, wearable devices), public health (prediction of epidemic alerts from social media data and meta-information in mobile devices) to healthcare informatics (inference regarding length of hospital stay, readmission probability within next days, mortality prediction from electronic health records). Classical machine learning techniques, such as logistic regression, neural networks, support vector machine and Gaussian processes performed very well in non-temporal prediction tasks but typically relied on the independence assumption. However, many recent application have longitudinal context in the form of short- and long-term dependencies, e.g. local spatial features in brain images, sentiment in medical reports and summaries of medical research. Hidden Markov Models proved popular to model longitudinal data but increasingly become less computationally feasible for a large number of hidden states. Recently, advances in parallel computing led to widespread use of deep learning approaches, such as recurrent neural networks and convolutional networks, and attracted attention due to their impressive results on sequence data. Finally, we will look in more detail at a case study from healthcare analytics which infers disease type from multiple irregularly sampled longitudinal observations, such as blood pressure, heart rate and blood oxygen saturation. - Poster PSI 2017 Abstract: Big Data Meets Pharma: In this work we present a tutorial introduction to show how SAS can be leveraged for large datasets in the pharmaceutical sector: Big data plays an increasingly important role within drug compound discovery, genomic data analysis in clinical trials and real-time streaming data from wearable devices or sensors which monitor patients’ health and treatment compliance. SAS adopted Hadoop as highly scalable data platform for data warehouse operations, descriptive statistics and statistical analysis with a bias towards machine learning approaches. However, Hadoop’ MapReduce framework is slow and batch-oriented which is not very suitable for iterative, multi-step parallel algorithms with a focus on in-memory computations. To address these limitations SAS added layers for in-memory computation, interactive data queries using a SQL variant, support for streaming analytics and predictive models implemented in SAS Visual Statistics/ Analytics. In the data science sector, the similar open-source Apache Spark project with its machine learning library MLlib is commonly used. Both Visual Statistics and MLlib have implementations for linear/logistic regression, decision-tree based classifiers, and clustering. Furthermore, SAS focusses on group-by processing and GLMs while MLlib has methods for feature extraction, dimensionality reduction, SVM classifiers, matrix completion and basic hypothesis tests. At the moment the SAS Hadoop implementation is a good selection for data management and dataset derivations which often can be parallelized. However, currently there is lack of procedures typically in pharmaceutical statistics, such as mixed effect models for repeated measurements analysis or survival analysis models. - Poster PSI 2016 Abstract: Sparse Principal Component Analysis for clinical variable selection in longitudinal data: Background: Data collection is a time-consuming and expensive process. To minimise costs and reduce time, statistical methods can be applied to determine which variables are required for a clinical trial. Principal component analysis (PCA) is a popular exploratory technique to select a subset of variables at one timepoint. For multiple timepoints, typically each variables’ measurements are aggregated, which ignores temporal relationships. An alternative method is Sparse Grouped Principal Component Analysis (SGPCA), which also incorporates the temporal relationship of each variable. ��SGPCA is based on ideas related to Least Absolute Shrinkage and Selection Operator (LASSO), a regularised regression technique, with grouped variables. SGPCA selects a sparse linear combination of temporal variables where each patient is represented as short multivariate time series which are modelled as a continuous smooth function of time using functional data analysis (FDA). Aim: Compare the ability of the PCA and SGPCA to identify required variables for clinical trials. Methods PCA and SGPCA will be applied to a longitudinal clinical dataset to select required variables.  We will compare the required variables, and the amount of variability retained for each technique under the SGPCA model. Conclusion This research will provide awareness of techniques to identify required variables in clinical trials, and aims to demonstrate the potential benefit of incorporating the temporal relationships in variable selection.

[healthcaredbmrnews]

Deoxyribonucleic acid (DNA) and gene chip (microarrays) market is expected to gain market growth in the forecast period of 2021 to 2028. Data Bridge Market Research analyses the market to account to grow at a CAGR of 13.40% in the above mentioned forecast period.

[wemresearch]

Genomics Market 2022 Key Players Data and Industry Analysis.

The Genomics Market is set to demonstrate a substantial upswing of a CAGR of 19.40% during the forecasted period of 2021 to 2030. The Genomics Market was valued at USD 23.5 billion in 2021 and is estimated to display a significant improvement to reach USD 137.16 billion by 2030.

The study of individual organisms' genomes is covered under the branch of genetics known as genomics. Fine-scale genetic mapping projects and extensive efforts to discover the complete DNA sequence of organisms are both included in this field. The field also includes research on intragenomic phenomena such as pleiotropy (when a single gene influences multiple phenotypic traits), epistasis (where the effects of one gene are modified by one or more other genes, sometimes referred to as modifier genes), heterosis (outbreeding enhancement), and other interactions between loci and alleles within the genome.

The application of artificial intelligence (AI) in genomics focuses on the creation of computer systems that are capable of carrying out tasks like genome mapping. Additionally, AI makes it possible to investigate genetic material's structure, evolution, and function more quickly than with human interaction. While clinical genomics is designed to perform genomic analysis, which includes genome annotation, variant calling, phenotype-to-genotype correspondence, and genome annotation, the primary goal of AI algorithms is to emulate human intelligence. Furthermore, with minimal feature hand-crafting, AI techniques can directly predict DNA or protein structure. The field of customised medicine greatly benefits from the uses of genomics. AI can speed up the production of medications in this area.

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Genomics Market: Segmentation Analysis

Genomics Market based on Products and Services

Among the deliverable’s segment the products category was dominant factor with a revenue share of 69.3%.

Products

Instruments/Systems/Software

Consumables & Reagents

Services

NGS-based Services

Core Genomics Services

Biomarker Translation Services

Computational Services

Others

Genomics Market by Application & Technology:

Of all types of applications and technologies, functional genomics held the largest share in terms of revenue, a share of 32% in the global market. Following functional genomics, the Real-time PCR was a dominant revenue generator of the market.

Functional Genomics

Real-time PCR

Transfection

SNP Analysis

Mutational Analysis

Microarray Analysis

RNA Interference

Pathway Analysis

Microarray Analysis

Bead-based Analysis

Proteomics Tools (2-D PAGE; yeast 2-hybrid studies)

Real-time PCR

Biomarker Discovery

DNA Sequencing

Microarray Analysis

Real-time PCR

Mass Spectrometry

Statistical Analysis

Bioinformatics

Epigenetics

Bisulfite Sequencing

Microarray Analysis

Chromatin Immunoprecipitation (ChIP & ChIP-Seq)

Methylated DNA Immunoprecipitation (MeDIP)

High Resolution Melt (HRM)

Chromatin Accessibility Assays

Others

Top Key Players:-

Thermo Fisher Scientific

QIAGEN N.V.

Agilent Technologies, Inc.

F. Hoffmann-La Roche Ltd.

Bio-Rad Laboratories, Inc.

Oxford Nanopore technologies

Danaher corporation

BGI (Beijing Genomics Institute)

IntegraGen

GE HEalthcare

Pacific Bioscience of california, Inc

Quest Diagnostics

Myriad Genetics, Inc.

Eppendorf AG

Eurofins Scientific

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Frequently Asked Questions (FAQ):

What is the forecast for the AI in genomics market in 2030?

What is the key application in the AI in genomics industry?

How did COVID-19 impact the AI in genomics market?

Which region holds the largest AI in genomics industry share?

Which is the most-significant development in the AI in genomics market?

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Our strategic market analysis and capability to comprehend deep cultural, conceptual and social aspects of various tangled markets has helped us make a mark for ourselves in the industry. WE MARKET RESEARCH is a frontrunner in helping numerous companies; both regional and international to successfully achieve their business goals based on our in-depth market analysis. Moreover, we are also capable of devising market strategies that ensure guaranteed customer bases for our clients.

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[drmanjushrikothekar]

What types of chromosome abnormalities does PGT-A screen for? | Dr. Manjushri Kothekar | IVF specialist in chembur

To conduct PGT-A, the laboratory most often uses a single nucleotide polymorphism (SNP) microarray and DNA samples from the individuals who contributed the eggs and sperm. Its primary purpose is to ensure that an embryo has the right amount of chromosomes (euploidy). PGT-A looks for full missing chromosomes (monosomy), whole additional chromosomes (trisomy), or a whole extra set of 23 chromosomes in embryos (triploidy). Second, PGT-A looks for missing or additional chromosomes (deletions or duplications). To be detected, these deletions and duplications must be significant, accounting for 15% of the overall length of that chromosome. Finally, PGT-A looks for uniparental disomy (UPD) of chromosomes 6, 7, 11, 14, and 15. When an embryo obtains two copies of a chromosome from one biological parent but no copies from the other, UPD develops. Poor pregnancy outcomes or a child with major health concerns may arise from UPD of these five chromosomes.

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Biochips Market Growth, Analysis, Latest Trends and Forecast till 2027

Market Highlights:

The Global Biochips Market Demand held a market value of USD 7,300 million in 2017 and is projected to grow at a CAGR of 16.6% over the forecast period.

Growth Drivers and Challenges

Microfluidics and Microarray technology have revolutionized the field of scientific research by reducing costs as well as time required for conventional laboratory-based approach of research. Microfluidics provide various benefits like reduced assay costs owing to need for less amount of sample in nano-liter or pico liter volume, increased sensitivity, accuracy, and throughput as compared to traditional laboratory procedures and also reduced labor cost. The products that are based on DNA microarrays, lab-on-a-chip, protein chips, as well as organ-on-a-chip technologies have managed to alleviate the existing problems associated with time and costs in their respective fields. Also, the research and development activities are underway at present, regarding the microarray and microfluidic technologies for numerous applications. This factor will turn out to be a high point for the market growth in the coming years. For instance, in the year 2017, Griffith Institute for Drug Discovery (GRIDD) started the process of developing microfluidic platform to further decrease time and costs needed for research.

To sum it up, extensive research and development in the field is expected to eventually elevate the adoption rate of these technologies. Case in point is the successful demonstration by scientists at Harvard University, which used the paper and threads as an ideal option for cheap microfluidic devices. moreover, integrating electrodes and electrical textile valves into such devices will make it even more useful.

Regional Analysis: Regionally, the global biochips market is split into the key regions of Europe, Asia Pacific, the Americas, along with the Middle East & Africa.

The biochips market, in the Americas, is flourishing in the regions of North America and South America, wherein the North America market is further split into the United States (US) and Canada.  The humongous share belonging to the region can be credited to the expanding geriatric population; growing prevalence of lifestyle diseases like asthma, diabetes, and cardiac disorders; increasing adoption of biochips; and a substantial number of ongoing research activities and discoveries taking place related to biochips.

The Europe biochips market is divided into Western Europe and Eastern Europe. The Western Europe biochips market is spread across the countries of France, Germany, the United Kingdom (UK), Spain, Italy, and the rest of Western Europe.

The biochips market in Asia Pacific is thriving in the countries like India, China, Japan, Australia, South Korea, and the rest of Asia Pacific. Easy access to modern and latest technologies along with growing government initiatives and cost advantage of the technology is set to benefit the regional market to a large extent.

Lastly, the biochips market in the Middle East & Africa has is spread across the main regions of Middle East and Africa.    

Market Segmentation: The Global Biochips Market has been segmented into type, technology, and end user.

By type, the market has been segmented into DNA chips, lab-on-a-chip, protein chips, cell arrays, and tissue arrays. DNA chips is further segmented into gene expression, SNP genotyping, cancer diagnosis & treatment, genomics, drug discovery, agricultural biotechnology, and others. Lab-on-a-chip is further segmented into clinical diagnostics, genomics, IVD (In-Vitro Diagnostic) & POC (Point of care), Proteomics, Drug Discovery, and others. Protein chips is further segmented into proteomics, expression profiling, diagnostics, high-throughput screening, drug discovery, others.

Based on technology, the market has been segmented into microarrays and microfluidics.

The biochips market, by end user, has been segmented into biotechnology and pharmaceutical companies, hospitals and diagnostics centers, academic & research institutes, and others.

Key Players Some of the prominent players in the global biochips market are Perkinelmer, Inc., Fluidigm Corporation, Agilent Technologies, Inc., Abbott Laboratories, Bio-Rad Laboratories Inc., Cepheid Inc., Illumina, Inc., GE Healthcare, Thermo Fisher Scientific, Inc, Roche Diagnostics, and others. About Market Research Future:

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Genomics Market 2022 by Manufacturers, Regions, Type and Application, Forecast to 2030

Genomics Market is appreciated to demonstrate a substantial upswing of a CAGR of 19.40% during the forecasted period of 2021 to 2030. The Genomics Market was valued at USD 23.5 billion in 2021 and is estimated to display a significant improvement to reach USD 137.16 billion by 2030.

Genomics is the study of genomes, and it includes DNA sequencing, recombinant DNA, and bioinformatics for sequencing, assembling, and analysing genome structure and functions. The growing use of NGS (Next-Generation Sequencing) in cancer research, as well as the entrance of new businesses and start-ups, will fuel the industry's revenue growth.

In terms of technology, the sequencing segment's genomics market share will grow due to their increased involvement in research in animal breeding, agriculture, and human genomes. Sequencing technologies are widely employed in scientific research, modern molecular biology, and diagnostic medicine due to their advantages such as fast speed, scalability, and ultra-high throughput.

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The rise in use of genomics in drug R&D, increased competition in the global pharmaceutical industry, surge in demand for genetically modified animals and plants, constantly lowering prices of genetic procedures, market growth initiatives taken by private and public organisations, rise in demand for nucleic acid sequencing, and entry of new players into the genomics market are the key factors driving the market's growth. Furthermore, the rising popularity of customised medicine and the growing popularity of alliances between research institutes and companies are likely to provide new growth prospects for genomics market players. However, the shortage of experienced specialists, the high costs of genomics equipment, and a lack of awareness in some countries are expected to limit the industry's expansion.

Global Genomics Market- Segment Analysis

Genomics Market based on Drugs: Deliverable

Among the deliverable’s segment the products category was dominant factor with a revenue share of 69.3%.

Products

• Instruments/Systems/Software

• Consumables & Reagents

Services

• NGS-based Services

• Core Genomics Services

• Biomarker Translation Services

• Computational Services

• Others

Genomics Market by Application & Technology:

Functional Genomics

• Real-time PCR

• Transfection

• SNP Analysis

• Mutational Analysis

• Microarray Analysis

• RNA Interference

Pathway Analysis

• Microarray Analysis

• Bead-based Analysis

• Proteomics Tools (2-D PAGE; yeast 2-hybrid studies)

• Real-time PCR

Biomarker Discovery

• DNA Sequencing

• Microarray Analysis

• Real-time PCR

• Mass Spectrometry

• Statistical Analysis

• Bioinformatics

Epigenetics

• Bisulfite Sequencing

• Microarray Analysis

• Chromatin Immunoprecipitation (ChIP & ChIP-Seq)

• Methylated DNA Immunoprecipitation (MeDIP)

• High Resolution Melt (HRM)

• Chromatin Accessibility Assays

• Others

Genomics Market by End use:

• Pharmaceutical and Biotechnology Companies

• Hospitals and Clinics

• Academic and Government Institutes

• Clinical Research

• Other

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Genomics Market: Competitive Landscape

Companies are focusing on development and inauguration of new products and collaboration with other entities to rise the market share. The main purpose of this collaboration is to manage the work flows. Some of the prominent companies are as follows Thermo Fisher Scientific, Inc.; Agilent Technologies; Beijing Genomics Institute (BGI); Bio-Rad Laboratories; Oxford Nanopore Technologies; Pacific Biosciences of California, Inc.; QIAGEN N.V.; Quest diagnostics; Myriad Genetics, Inc.; Eppendorf AG; Eurofins Scientific; Color; 23andMe, Inc. Danaher Corporation; F. Hoffmann-La Roche Ltd.; GE Healthcare; Illumina, Inc.

FAQs

1)What is the Genomics market growth?

2) Which product segment accounts for the highest market share in the Genomics market?

3) Does the Genomics market company is profiled in the report?

4) Which are the top companies hold the market share in Genomics market?

5) How can I get sample reports/company profiles for the Genomics market?

About We Market Research

WE MARKET RESEARCH is an established market analytics and research firm with a domain experience sprawling across different industries. We have been working on multi-county market studies right from our inception. Over the time, from our existence, we have gained laurels for our deep rooted market studies and insightful analysis of different markets.

Our strategic market analysis and capability to comprehend deep cultural, conceptual and social aspects of various tangled markets has helped us make a mark for ourselves in the industry. WE MARKET RESEARCH is a frontrunner in helping numerous companies; both regional and international to successfully achieve their business goals based on our in-depth market analysis. Moreover, we are also capable of devising market strategies that ensure guaranteed customer bases for our clients.

Contact Us:

We Market Research

Phone: +1(929)-450-2887

Email: sales@wemarketresearch.com

Web:

https://wemarketresearch.com/