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市場調查報告書
商品編碼
1423574
到 2030 年的基因預測工具市場預測:按組件、應用、最終用戶和地區進行的全球分析Gene Prediction Tools Market Forecasts to 2030 - Global Analysis By Component (Software and Service), Application, End User and By Geography |
根據Stratistics MRC預測,2023年全球基因預測工具市場規模將達到1,273億美元,預計2030年將達到4,641億美元,預測期內複合年成長率為20.3%。
基因預測工具是一種計算演算法,用於識別和註釋 DNA 序列中潛在的蛋白質轉錄區。這些工具使用統計模型、隱馬可夫模型或機器學習技術來分析基因序列並預測基因的位置、編碼區、外顯子-內含子邊界和調控元件。這些工具有助於了解基因結構,促進各種生物體的基因註釋、功能分析和基因組註釋,為基因組學和分子生物學研究做出巨大貢獻。
根據 2021 年生物資訊簡報,一個名為 TSSFinder 的程式被用來說明真核物種的啟動子序列。使用基於線性鏈條件隨機場(LCCRF)的隨機模型的轉錄起始位點(TSS)預測方法是TSSFinder,其最初在文獻中公開。
個人化醫療需求不斷成長
對個人化醫療日益成長的需求正在推動基因預測工具的進步。這些工具使用遺傳資訊來預測個體患某些疾病的可能性、對某些藥物的反應以及潛在的副作用。遺傳預測工具透過分析個體的遺傳資料並識別與疾病和藥物代謝相關的突變來幫助客製化治療計劃。
資料品質和複雜性
由於基因組序列變異,基因預測工具面臨資料品質挑戰,導致預測錯誤。基因結構的複雜性,包括選擇性剪接和重複基因,增加了影響準確性的複雜性。此外,大量可用的基因組資料帶來了計算挑戰,需要強大的演算法來處理不同的基因組特徵。因此,資料品質的限制和複雜性阻礙了準確的遺傳預測,影響了生物學解釋和下游分析。
擴大生物資訊學的採用
生物資訊學在遺傳預測工具的進步中發揮著至關重要的作用,並正在推動其廣泛普及。生物資訊學利用計算演算法和生物資料,實現準確的基因辨識、註釋和功能分析。其整合採用序列分析、機器學習和統計方法來最佳化預測模型並破解遺傳密碼。對生物資訊學的日益依賴確保了各個生物研究領域基因預測工具的準確性、擴充性和可訪問性的提高。
嚴格的法規核准流程
基因預測工具嚴格的法規核准流程有幾個缺點。它通常會導致更長的開發時間並延遲基因研究和臨床應用的重要創新。高監管障礙限制了可近性和可負擔性,並阻止小型研究團體和公司提供新穎的解決方案。此外,如此嚴格的流程可能會因為偏向既定工具而扼殺創新,阻礙更有效和突破性技術的出現。
遺傳預測工具在識別病毒基因、突變和功能成分方面發揮了重要作用。研究人員使用這些工具不僅可以識別潛在的候選疫苗,還可以評估其安全性和有效性。然而,隨著疫情蔓延,由於資源重新分配、封鎖和研究活動中斷,許多與 COVID-19 無關的研究計劃被迫取消或推遲。因此,基因預測儀器在COVID-19以外的研究領域的接受和應用已經放緩。
軟體部分預計將在預測期內成為最大的部分
預計軟體部門將成為預測期內最大的部門。這些工具使用複雜的演算法來分析基因組資料並準確預測基因位置、結構和功能。該市場的主要參與者提供方便用戶使用的介面,並確保研究人員和臨床醫生的可訪問性。軟體提高基因預測準確性的能力極大地促進了基因組研究和個人化醫療的進步,並正在推動市場擴張。隨著基因組資料的不斷增加,對高效可靠的基因預測工具的需求預計將進一步推動市場成長。
診斷領域預計在預測期內複合年成長率最高
診斷領域預計在預測期內複合年成長率最高。這些工具在識別與疾病相關的遺傳變異和支持個人化醫療方面發揮著重要作用。對準確、高效的診斷解決方案的需求正在刺激基因預測工具的創新,創造一個競爭激烈的市場形勢。主要企業專注於提高診斷準確性、擴展應用程式和增強方便用戶使用介面,為整體市場的成長和發展做出貢獻。
預計北美在預測期內將佔據最大的市場佔有率。人們對基因研究的興趣和投資不斷成長,特別是在個人化醫療、癌症研究和農業等領域,正在推動對複雜基因預測工具的需求。該地區的生物技術和製藥公司正在大力投資與基因編輯、治療和診斷相關的研發,進一步推動市場成長。
預計亞太地區在預測期內將維持最高的複合年成長率。有幾個因素促成了這種擴張,包括基因組研究和開發活動的活性化、生物技術和製藥領域投資的增加以及個人化醫療意識的增強。各國透過對生命科學研究的大量投資為這個市場做出了重大貢獻。這些國家擁有充滿活力的生物技術產業和進行廣泛基因組研究的學術機構。
According to Stratistics MRC, the Global Gene Prediction Tools Market is accounted for $127.3 billion in 2023 and is expected to reach $464.1 billion by 2030 growing at a CAGR of 20.3% during the forecast period. Gene prediction tools are computational algorithms used to identify and annotate potential protein-coding regions within DNA sequences. They analyze genetic sequences, employing statistical models, hidden Markov models, or machine learning techniques to predict the locations of genes, coding regions, exon-intron boundaries, and regulatory elements. These tools aid in understanding genetic structures, facilitating gene annotation, functional analysis, and genome annotation in various organisms, contributing significantly to genomics and molecular biology research.
According to Briefings in Bioinformatics in 2021, a program called TSSFinder was used to describe the promoter sequences from Eukaryotic species. The initial transcription start site (TSS) prediction approach that uses a probabilistic model based on linear chain conditional random fields (LCCRFs) is TSSFinder, which was originally disclosed in the literature.
Rising demand for personalized medicines
The increasing demand for personalized medicine has been a driving force in the advancement of gene prediction tools. These tools utilize genetic information to predict an individual's likelihood of developing certain diseases, their response to particular medications, and potential adverse reactions. Gene prediction tools analyze an individual's genetic data to identify variations associated with diseases or drug metabolism, aiding in customizing treatment plans.
Data quality and complexity
Gene prediction tools face challenges with data quality due to variations in genome sequences, leading to errors in predictions. The complexity of gene structures, including alternative splicing and overlapping genes, adds intricacy, affecting accuracy. Moreover, the vast amount of available genomic data poses computational challenges, requiring robust algorithms to handle diverse genomic features. Consequently, limitations in data quality and complexities hinder precise gene predictions, impacting biological interpretations and downstream analyses.
Growing adoption of bioinformatics
Bioinformatics plays a pivotal role in advancing gene prediction tools, driving their widespread adoption. Leveraging computational algorithms and biological data, bioinformatics enables accurate gene identification, annotation, and functional analysis. Its integration optimizes predictive models, employing sequence analysis, machine learning, and statistical methods to decipher genetic codes. The growing reliance on bioinformatics ensures enhanced precision, scalability, and accessibility of Gene Prediction Tools in various biological research domains.
Stringent regulatory approval process
The stringent regulatory approval process for gene prediction tools poses several disadvantages. It often leads to prolonged development timelines, delaying crucial innovations in genetic research and clinical applications. High regulatory barriers limit accessibility and affordability, impeding smaller research groups or companies from contributing novel solutions. Additionally, these stringent processes may stifle innovation by favouring established tools, hindering the emergence of potentially more effective or groundbreaking technologies.
Gene prediction tools played a crucial role in identifying viral genes, mutations, and functional components. These tools were used by researchers to evaluate the safety and efficacy of possible vaccine candidates in addition to identifying them. However, as the epidemic spread, numerous research projects unrelated to COVID-19 had to be cancelled or postponed due to resource reallocation, lockdowns, and disruptions in research activity. Consequently, there was a deceleration in the acceptance and application of gene prediction instruments in research domains other than COVID-19.
The software segment is expected to be the largest during the forecast period
The software segment is expected to be the largest during the forecast period. These tools utilize sophisticated algorithms to analyze genomic data, accurately predicting gene locations, structures, and functions. Key players in this market offer user-friendly interfaces, ensuring accessibility for researchers and clinicians. The software's ability to enhance precision in gene prediction significantly contributes to advancements in genomics research and personalized medicine, driving the market's expansion. As genomic data continues to grow, the demand for efficient and reliable gene prediction tools is expected to further propel market growth.
The diagnostics segment is expected to have the highest CAGR during the forecast period
The diagnostics segment is expected to have the highest CAGR during the forecast period. These tools play a crucial role in identifying genetic variations associated with diseases, aiding in personalized medicine. The demand for accurate and efficient diagnostic solutions has spurred innovation in gene prediction tools, creating a competitive market landscape. Key players are focusing on improving diagnostic accuracy, expanding applications, and enhancing user-friendly interfaces, contributing to the overall growth and evolution of the market.
North America is projected to hold the largest market share during the forecast period. Growing interest and investment in genetic research, particularly in fields like personalized medicine, cancer research, and agriculture, have increased the demand for sophisticated gene prediction tools. Biotech and pharmaceutical companies in the region are investing heavily in research and development related to gene editing, therapeutics, and diagnostics, further propelling the market growth.
Asia Pacific is projected to hold the highest CAGR over the forecast period. Several factors were contributing to this expansion, including increased research and development activities in genomics, rising investments in biotechnology and pharmaceutical sectors, and growing awareness about personalized medicine. Countries were key contributors to this market due to their substantial investments in life sciences research. These nations had vibrant biotechnology industries and academic institutions conducting extensive genomic research.
Key players in the market
Some of the key players in Gene Prediction Tools market include AZoLifeSciences, Illumina, Inc., BGI Genomics, Geneious, Thermo Fisher Scientific, Inc., Genscript, Exiqon, Softberry Technologies, Qiagen NV, National Human Genome Research Institute, New England Biolabs, ERS Genomics, Horizon Discovery Ltd., Sangamo Therapeutics, Takara Bio Inc. and Merck KGaA.
In June 2023, Illumina, Inc. disclosed the AI software for predicting disease-causing genetic mutations in patients. Through this, the company has enhanced its product portfolio and revenue growth.
In March 2022, Illumina, Inc. announced the launch of TruSigh Oncology (TSO) Comprehensive (EU). It is an examination that assesses various tumor of a patient's malignancy.