100+ datasets found
  1. C

    Bioinformatics for Researchers in Life Sciences: Tools and Learning...

    • data.iadb.org
    csv, pdf
    Updated Apr 10, 2025
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    IDB Datasets (2025). Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources [Dataset]. http://doi.org/10.60966/kwvb-wr19
    Explore at:
    csv(276253), pdf(2989058), csv(355108)Available download formats
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    IDB Datasets
    License

    Attribution-NonCommercial-NoDerivs 3.0 (CC BY-NC-ND 3.0)https://creativecommons.org/licenses/by-nc-nd/3.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2020 - Jan 1, 2021
    Description

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

  2. Talks on Learning methods in Bioinformatics (Education and Training)

    • figshare.com
    pdf
    Updated Jan 18, 2016
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    Pedro Fernandes (2016). Talks on Learning methods in Bioinformatics (Education and Training) [Dataset]. http://doi.org/10.6084/m9.figshare.703118.v3
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    pdfAvailable download formats
    Dataset updated
    Jan 18, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Pedro Fernandes
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The slides displayend in recent talks are shared here

  3. c

    Global Bioinformatics Service Market Report 2025 Edition, Market Size,...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jun 15, 2025
    + more versions
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    Cognitive Market Research (2025). Global Bioinformatics Service Market Report 2025 Edition, Market Size, Share, CAGR, Forecast, Revenue [Dataset]. https://www.cognitivemarketresearch.com/bioinformatics-service-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jun 15, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the Global Bioinformatics Services Market Size will be USD XX Billion in 2023 and is set to achieve a market size of USD XX Billion by the end of 2031 growing at a CAGR of XX% from 2024 to 2031.

    • The global Bioinformatics services Market will expand significantly by XX% CAGR between 2024 and 2031.

    • Based on technology, Because of the growing number of platform applications and the need for improved tools for drug development, the bioinformatics platforms segment dominated the market.

    • In terms of service type, The sequencing services segment held the largest share and is anticipated to grow over the coming years

    • Based on application, The genomic segment dominated the bioinformatics market

    • Based on End-user, academic institutes and research centers segment hold the largest share.

    • Based on speciality segment, The medical bioinformatics segment holds the large share and is anticipated to expand at a substantial CAGR during the forecast period.

    • The North America region accounted for the highest market share in the Global Bioinformatics Services Market. CURRENT SCENARIO OF THE BIOINFORMATICS SERVICES

    Driving Factors of the Bioinformatics Services Market

    Expansive uses of bioinformatics across multiple sectors is propelling the market's growth.
    

    Several industries, such as the food, bioremediation, agriculture, forensics, and consumer industries, are also using bioinformatics services to improve the quality of their products and supply chain processes. Companies in a variety of sectors are rapidly utilizing bioinformatics services such as data integration, manipulation, lead generation, data management, in silico analysis, and advanced knowledge discovery.

    • Bioinformatics Approaches in Food Sciences

    In order to meet the needs of food production, food processing, enhancing the quality and nutritional content of food sources, and many other areas, bioinformatics plays a significant role in forecasting and evaluating the intended and undesired impacts of microorganisms on food, genomes, and proteomics research. Furthermore, bioinformatics techniques can be applied to produce crops with high yields and resistance to disease, among other desirable qualities. Additionally, there are numerous databases with information about food, including its components, nutritional value, chemistry, and biology.

    Genome Canada is proud to partner with five Institutes where there are five funding pools within this opportunity and Genome Canada is partnering on the Bioinformatics, Computational Biology and Health Data Sciences pool. (Source:https://genomecanada.ca/genome-canada-partners-with-cihr-to-launch-health-research-training-platform-2024-25/)

    • Bioinformatics in agriculture

    Bioinformatics is becoming more and more crucial in the gathering, storing, and processing of genomic data in the field of agricultural genomics, or agri-genomics. Generally referred to as agri-informatics, some of the various applications of bioinformatics tools and methods in agriculture focus on improving plant resistance against biotic and abiotic stressors as well as enhancing the nutritional quality in depleted soils. Beyond these uses, computer software-assisted gene discovery has enabled researchers to create focused strategies for seed quality enhancement, incorporate extra micronutrients into plants for improved human health, and create plants with phytoremediation potential.

    India/UK-based Agri-Genomics startup, Piatrika Biosystems has raised $1.2 Million in a seed round led by Ankur Capital. The company is bringing sustainable seeds and agri chemicals to market faster and cheaper. The investment will be used to build a strong Product Development team, also for more profound research, and to accelerate the productionising and commercialization of MVP. (Source:https://pressroom.icrisat.org/agri-genomics-startup-piatrika-biosystems-raises-12-million-in-seed-funding-led-by-ankur-capital)

    This expansion in the application areas of bioinformatics services is likely to drive the overall market growth. Bioinformatics services such as data integration, manipulation, lead discovery, data management, in silico analysis, and advanced knowledge discovery are increasingly being adopted by companies across various industries.&...

  4. Bioinformatics Market Analysis, Size, and Forecast 2025-2029: North America...

    • technavio.com
    Updated Jun 19, 2025
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    Technavio (2025). Bioinformatics Market Analysis, Size, and Forecast 2025-2029: North America (US, Canada, and Mexico), Europe (France, Germany, Italy, and UK), APAC (China, India, and Japan), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/bioinformatics-market-industry-analysis
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    Dataset updated
    Jun 19, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Mexico, Canada, France, Europe, United Kingdom, Germany, United States, Global
    Description

    Snapshot img

    Bioinformatics Market Size 2025-2029

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

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

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

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    The market continues to evolve, driven by advancements in genome editing, data mining, and sequence alignment, among other techniques. Molecular modeling and high-throughput screening are essential tools in drug discovery, while bioimage analysis and gene ontology play a pivotal role in systems biology. Metabolomics data and phylogenetic analysis contribute to a deeper understanding of biological processes.

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

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

    How is this Bioinformatics Industry segmented?

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

    Application
    
      Molecular phylogenetics
      Transcriptomic
      Proteomics
      Metabolomics
    
    
    Product
    
      Platforms
      Tools
      Services
    
    
    End-user
    
      Pharmaceutical and biotechnology companies
      CROs and research institutes
      Others
    
    
    Geography
    
      North America
    
        US
        Canada
        Mexico
    
    
      Europe
    
        France
        Germany
        Italy
        UK
    
    
      APAC
    
        China
        India
        Japan
    
    
      Rest of World (ROW)
    

    By Application Insights

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

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

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

    Request Free Sample

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

    Regional Analysis

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

  5. M

    AI In Bioinformatics Market To Reach US$ 136.3 Million By 2033

    • media.market.us
    Updated Dec 17, 2024
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    Market.us Media (2024). AI In Bioinformatics Market To Reach US$ 136.3 Million By 2033 [Dataset]. https://media.market.us/ai-in-bioinformatics-market-news-2024/
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    Dataset updated
    Dec 17, 2024
    Dataset authored and provided by
    Market.us Media
    License

    https://media.market.us/privacy-policyhttps://media.market.us/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    United States
    Description

    Introduction

    Global AI In Bioinformatics Market size is expected to be worth around US$ 136.3 Million by 2033, from US$ 3.8 Million in 2023, growing at a CAGR of 42.9% during the forecast period from 2024 to 2033. In 2023, North America led the market, achieving over 46.5% share with a revenue of US$ 1.7 Million.

    This growth is driven by increasing demand for bioinformatics, decreasing sequencing costs, and significant funding from both public and private sectors for bioinformatics research. Technological advancements and strategic collaborations among leading players, such as Thermo Fisher Scientific, Illumina Inc., and Qiagen, are further fueling market expansion. These collaborations often focus on developing or upgrading bioinformatics tools to efficiently manage biological data essential for gene therapy, drug discovery, and personalized medicine.

    Recent developments highlight the market's dynamic growth, with investments accelerating genomic and proteomic data analysis. These advancements are critical for understanding disease mechanisms and identifying therapeutic strategies. AI-powered bioinformatics is revolutionizing the field by enhancing data analysis speed, facilitating discoveries of new disease pathways, and identifying potential therapeutic targets.

    Despite its promising growth, the market faces challenges such as the lack of standardized data formats, the need for user-friendly tools, and the complexities of managing large biological datasets. However, with ongoing technological innovations and increased investments, these challenges are expected to be addressed, creating a robust environment for further market expansion.

    https://sp-ao.shortpixel.ai/client/to_auto,q_lossy,ret_img,w_1216,h_709/https://market.us/wp-content/uploads/2024/03/AI-In-Bioinformatics-Market-Growth.jpg" alt="AI In Bioinformatics Market Growth" class="wp-image-116134">

  6. d

    Data from: Transcriptomic and bioinformatics analysis of the early...

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +1more
    Updated Apr 21, 2025
    + more versions
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    Agricultural Research Service (2025). Data from: Transcriptomic and bioinformatics analysis of the early time-course of the response to prostaglandin F2 alpha in the bovine corpus luteum [Dataset]. https://catalog.data.gov/dataset/data-from-transcriptomic-and-bioinformatics-analysis-of-the-early-time-course-of-the-respo-cd938
    Explore at:
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Agricultural Research Service
    Description

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

  7. Article PDF Filesizes

    • figshare.com
    txt
    Updated Jun 2, 2023
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    Ross Mounce (2023). Article PDF Filesizes [Dataset]. http://doi.org/10.6084/m9.figshare.748784.v2
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Ross Mounce
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A small bit of my thesis. Why are BMC PDFs so significantly larger on average than PLOS or Zootaxa PDFs?

    data sources:

    A) 'Zootaxa' the entire set of articles published in the journal Zootaxa from 2001 to 2012 inclusive, consisting of 11563 pdf files downloaded direct from the publisher website : http://mapress.com/zootaxa/ B) 'PLOS' the entire set of articles published across 7 different PLOS journals: PLOS ONE, PLOS Biology, PLOS Computational Biology, PLOS Genetics, PLOS Medicine, PLOS Neglected Tropical Diseases, and PLOS Pathogens from 2003 to 2010-06-04, consisting of 20694 articles obtained via BioTorrents (Langille & Eisen, 2010). C) 'BMC' a subsample of 7948 open access articles containing the stemword 'phylogen*' at least once in the fulltext from the wide range of journals that BioMedCentral publish (the OA subset of this selection of papers: http://www.citeulike.org/user/testtest87)

  8. B

    Biological Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Apr 21, 2025
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    Data Insights Market (2025). Biological Software Report [Dataset]. https://www.datainsightsmarket.com/reports/biological-software-1444091
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global biological software market is experiencing robust growth, driven by the increasing adoption of advanced technologies in life sciences research and healthcare. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of approximately 12% from 2025 to 2033, reaching an estimated market value of $7 billion by 2033. This expansion is fueled by several key factors: the escalating demand for high-throughput data analysis in genomics and proteomics, the rising prevalence of chronic diseases necessitating advanced diagnostic tools, and the growing adoption of cloud-based solutions for enhanced collaboration and accessibility. Furthermore, the continuous development of sophisticated algorithms and user-friendly interfaces is making biological software more accessible to a wider range of researchers and clinicians. The segment encompassing experimental design and data analysis software holds a significant market share, reflecting the crucial role of computational tools in optimizing research workflows and extracting meaningful insights from complex biological datasets. North America currently dominates the market, owing to the robust presence of established biotechnology companies and a well-funded research infrastructure. However, Asia-Pacific is expected to witness significant growth in the coming years due to the expanding healthcare sector and increasing government investments in research and development. Market restraints include the high cost of software licenses, the requirement for specialized training to effectively utilize these tools, and the potential challenges associated with data security and integration across different platforms. Nevertheless, the ongoing innovation in software capabilities, coupled with the increasing adoption of subscription-based models and cloud-based solutions, is expected to mitigate these constraints. The competitive landscape is characterized by a mix of established players like Thermo Fisher Scientific and DNASTAR, along with smaller specialized companies offering niche solutions. This dynamic competitive environment fosters innovation and drives the development of advanced biological software solutions tailored to the specific needs of diverse research and clinical applications. Future growth will be influenced by factors such as advancements in artificial intelligence and machine learning within the software, integration with laboratory automation systems, and increasing collaboration between software providers and research institutions.

  9. D

    Bioinformatics Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Bioinformatics Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-bioinformatics-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Bioinformatics Market Outlook



    The global bioinformatics market size was projected at $10.4 billion in 2023 and is anticipated to grow to $24.8 billion by 2032, with a compound annual growth rate (CAGR) of 10.2%. This rapid growth is primarily attributed to the increasing demand for bioinformatics tools in genomics and proteomics research, thereby enhancing data interpretation and analysis capabilities. Additionally, the surge in the adoption of cloud-based solutions and the increasing volume of biological data generated through research activities are key factors driving the market growth. Furthermore, the rising emphasis on precision medicine and personalized healthcare approaches plays a significant role in the expansion of this market.



    One of the major growth factors driving the bioinformatics market is the vast amount of biological data being generated, necessitating advanced data analysis and management tools. The advent of next-generation sequencing technologies has revolutionized genetic research, leading to exponential data generation. Bioinformatics provides the necessary computational solutions to manage, analyze, and interpret this data efficiently. Moreover, the increasing collaboration between biological scientists and computer experts is further accelerating the development of novel bioinformatics tools, enhancing their application across various domains. This interdisciplinary approach is not only improving research outcomes but also facilitating the discovery of new biological insights.



    Another significant growth driver is the rising investment in research and development in the field of genomics and proteomics. Governments and private organizations across the globe are investing heavily in life sciences research to understand complex biological processes and diseases better. These investments are expected to increase the demand for sophisticated bioinformatics tools and services. Additionally, the integration of artificial intelligence and machine learning with bioinformatics is opening new avenues for research, enabling more precise data analysis and prediction models. This technological convergence is expected to provide significant growth opportunities for the bioinformatics market during the forecast period.



    The increasing prevalence of chronic diseases and the growing need for personalized medicine are also contributing to the expansion of the bioinformatics market. Personalized medicine, which tailors healthcare to individual patients, relies heavily on bioinformatics to analyze genetic information and develop targeted therapies. As healthcare systems worldwide shift towards more personalized approaches, the demand for bioinformatics solutions is expected to rise significantly. Moreover, bioinformatics plays a crucial role in drug discovery and development processes, providing insights that accelerate the identification of potential drug targets and biomarkers.



    The role of Life Sciences Software in the bioinformatics market is becoming increasingly prominent as researchers and healthcare providers seek more sophisticated tools to manage and analyze complex biological data. These software solutions are essential for processing the vast amounts of data generated by modern research techniques, such as next-generation sequencing and mass spectrometry. By providing robust data management and analysis capabilities, Life Sciences Software enables researchers to gain deeper insights into genetic and proteomic information, facilitating the discovery of new therapeutic targets and the development of personalized medicine approaches. As the demand for precision medicine continues to grow, the importance of Life Sciences Software in bioinformatics is expected to rise, driving innovation and market expansion.



    Regionally, North America holds the largest share of the bioinformatics market due to the presence of a well-established healthcare infrastructure and significant investments in biotechnological research. The region is home to several leading bioinformatics companies and research institutions, which are at the forefront of innovation and technological advancements. Additionally, the Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by increasing government funding for genomics research and the growing adoption of bioinformatics in emerging economies like China and India. The expansion of biopharmaceutical industries and a rising focus on precision medicine in these regions are further contributing to market growth.



    Pro

  10. Bioinformatic training needs at a health sciences campus

    • plos.figshare.com
    • figshare.com
    pdf
    Updated Jun 4, 2023
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    Jeffrey C. Oliver (2023). Bioinformatic training needs at a health sciences campus [Dataset]. http://doi.org/10.1371/journal.pone.0179581
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jeffrey C. Oliver
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundHealth sciences research is increasingly focusing on big data applications, such as genomic technologies and precision medicine, to address key issues in human health. These approaches rely on biological data repositories and bioinformatic analyses, both of which are growing rapidly in size and scope. Libraries play a key role in supporting researchers in navigating these and other information resources.MethodsWith the goal of supporting bioinformatics research in the health sciences, the University of Arizona Health Sciences Library established a Bioinformation program. To shape the support provided by the library, I developed and administered a needs assessment survey to the University of Arizona Health Sciences campus in Tucson, Arizona. The survey was designed to identify the training topics of interest to health sciences researchers and the preferred modes of training.ResultsSurvey respondents expressed an interest in a broad array of potential training topics, including "traditional" information seeking as well as interest in analytical training. Of particular interest were training in transcriptomic tools and the use of databases linking genotypes and phenotypes. Staff were most interested in bioinformatics training topics, while faculty were the least interested. Hands-on workshops were significantly preferred over any other mode of training. The University of Arizona Health Sciences Library is meeting those needs through internal programming and external partnerships.ConclusionThe results of the survey demonstrate a keen interest in a variety of bioinformatic resources; the challenge to the library is how to address those training needs. The mode of support depends largely on library staff expertise in the numerous subject-specific databases and tools. Librarian-led bioinformatic training sessions provide opportunities for engagement with researchers at multiple points of the research life cycle. When training needs exceed library capacity, partnering with intramural and extramural units will be crucial in library support of health sciences bioinformatic research.

  11. Survey of biologist's computational needs

    • figshare.com
    txt
    Updated Feb 10, 2017
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    Lindsay Barone; Jason Williams; David Micklos (2017). Survey of biologist's computational needs [Dataset]. http://doi.org/10.6084/m9.figshare.4643641.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    Feb 10, 2017
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Lindsay Barone; Jason Williams; David Micklos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Figures and survey data from forthcoming pre-print:

    In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principle investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work—including high performance computing (HPC), bioinformatics support, multi-step workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the U.S. and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC – acknowledging that data science skills will be required to build a deeper understanding of life.

  12. B

    Bioinformatics Cloud Platform Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 15, 2025
    + more versions
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    Archive Market Research (2025). Bioinformatics Cloud Platform Report [Dataset]. https://www.archivemarketresearch.com/reports/bioinformatics-cloud-platform-58815
    Explore at:
    ppt, doc, pdfAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Bioinformatics Cloud Platform market is experiencing robust growth, driven by the increasing volume of biological data generated through next-generation sequencing and other high-throughput technologies. Researchers and pharmaceutical companies are increasingly relying on cloud-based solutions for data storage, analysis, and collaboration due to their scalability, cost-effectiveness, and enhanced computational power. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 20% from 2025 to 2033, reaching approximately $10 billion by 2033. This growth is fueled by several key trends including the rising adoption of cloud computing in life sciences, the development of sophisticated bioinformatics tools and algorithms accessible via cloud platforms, and the increasing need for collaborative research initiatives. The Software as a Service (SaaS) segment currently holds the largest market share, reflecting the preference for readily available and user-friendly applications. Key players such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are actively expanding their bioinformatics offerings, driving competition and innovation within the market. The pharmaceutical and academic & research segments are major contributors to market demand, benefiting from the enhanced speed and efficiency offered by cloud-based solutions for drug discovery and genomic research. However, market growth is not without its challenges. Data security and privacy concerns remain significant restraints, particularly when dealing with sensitive patient information. High upfront investment costs for cloud infrastructure and the need for specialized expertise to effectively utilize these platforms can also impede wider adoption. Furthermore, integration challenges with legacy on-premise systems can pose a barrier to migration to cloud-based bioinformatics solutions. To overcome these hurdles, providers are focusing on enhanced security measures, user-friendly interfaces, and cost-effective pricing models to encourage broader market penetration. The future success of the Bioinformatics Cloud Platform market depends on addressing these challenges while continuing to innovate and improve the functionality and accessibility of these crucial tools for life science research and development.

  13. d

    Raw motif mapping bedfile data and model training set class probabilities

    • search.dataone.org
    • data.niaid.nih.gov
    • +2more
    Updated May 6, 2025
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    Phillip Davis (2025). Raw motif mapping bedfile data and model training set class probabilities [Dataset]. http://doi.org/10.5061/dryad.tdz08kq3w
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    Dataset updated
    May 6, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Phillip Davis
    Time period covered
    Jan 1, 2023
    Description

    Leveraging prior viral genome sequencing data to make predictions on whether an unknown, emergent virus harbors a ‘phenotype-of-concern’ has been a long-sought goal of genomic epidemiology. A predictive phenotype model built from nucleotide-level information alone is challenging with respect to RNA viruses due to the ultra-high intra-sequence variance of their genomes, even within closely related clades. We developed a degenerate k-mer method to accommodate this high intra-sequence variation of RNA virus genomes for modeling frameworks. By leveraging a taxonomy-guided ‘group-shuffle-split’ cross validation paradigm on complete coronavirus assemblies from prior to October 2018, we trained multiple regularized logistic regression classifiers at the nucleotide k-mer level. We demonstrate the feasibility of this method by finding models accurately predicting withheld SARS-CoV-2 genome sequences as human pathogens and accurately predicting withheld Swine Acute Diarrhea Syndrome coronavirus (...

  14. q

    Genome Solver - A bioinformatics pipeline for community science

    • qubeshub.org
    Updated Feb 20, 2024
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    Vinayak Mathur; Gaurav Arora; Anne Rosenwald (2024). Genome Solver - A bioinformatics pipeline for community science [Dataset]. http://doi.org/10.25334/SEDX-YS29
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    Dataset updated
    Feb 20, 2024
    Dataset provided by
    QUBES
    Authors
    Vinayak Mathur; Gaurav Arora; Anne Rosenwald
    Description

    The Genome Solver was an NSF-funded project developed as a way to train undergraduate life science faculty in basic web-based tools for bioinformatics. As part of the project we developed a one-day workshop consisting of bioinformatics modules on the theme of bacterial genomics, which we delivered to faculty at colleges and universities around the country. All of our workshop material can be accessed on the QUBESHub website: https://qubeshub.org/community/groups/genomesolver/

  15. n

    Data from: The new bioinformatics: integrating ecological data from the gene...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Jul 16, 2012
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    Matthew B. Jones; Mark P. Schildahuer; O. J. Reichman; Shawn Bowers; Mark P. Schildhauer; O.J. Reichman (2012). The new bioinformatics: integrating ecological data from the gene to the biosphere [Dataset]. http://doi.org/10.5061/dryad.qb0d6
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    zipAvailable download formats
    Dataset updated
    Jul 16, 2012
    Dataset provided by
    University of California, Santa Barbara
    University of California, Davis
    Authors
    Matthew B. Jones; Mark P. Schildahuer; O. J. Reichman; Shawn Bowers; Mark P. Schildhauer; O.J. Reichman
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Bioinformatics, the application of computational tools to the management and analysis of biological data, has stimulated rapid research advances in genomics through the development of data archives such as GenBank, and similar progress is just beginning within ecology. One reason for the belated adoption of informatics approaches in ecology is the breadth of ecologically pertinent data (from genes to the biosphere) and its highly heterogeneous nature. The variety of formats, logical structures, and sampling methods in ecology create significant challenges. Cultural barriers further impede progress, especially for the creation and adoption of data standards. Here we describe informatics frameworks for ecology, from subject-specific data warehouses, to generic data collections that use detailed metadata descriptions and formal ontologies to catalog and cross-reference information. Combining these approaches with automated data integration techniques and scientific workflow systems will maximize the value of data and open new frontiers for research in ecology.

  16. Bioinformatics infrastructure and training summary

    • search.datacite.org
    Updated Jan 20, 2016
    + more versions
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    Nicholas Loman; Thomas Connor (2016). Bioinformatics infrastructure and training summary [Dataset]. http://doi.org/10.6084/m9.figshare.1572287.v1
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    Dataset updated
    Jan 20, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    DataCitehttps://www.datacite.org/
    Authors
    Nicholas Loman; Thomas Connor
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We undertook a poll of bioinformaticians, marketed through Twitter, in order to understand more about the current issues with bioinformatics practice and training. Methods: Through using a public Google Form we asked questions relating to frustrations, working practices, limitations of working practices. We also assessed whether the survey participant was UK based and what level of self-declared skill they had. Users had the opportunity to read the other responses to the survey, and edit or delete their answers. Results: This fileset presents the form, the responses (in Excel and CSV format) and the summary responses. The results may be of use for those wishing to understand more about the current issues facing bioinformaticians and bioinformatics training. The results are distributed under the CC-BY license. We are grateful to all participants who took the time to fill out this survey.

  17. Using Bioinformatics: Genetic Research

    • search.datacite.org
    • figshare.com
    Updated Feb 16, 2014
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    Jeanne Chowning; Dina Kovarik; Sandra Porter; Joan Griswold; Jodie Spitze; Carol Farris; Karen Petersen; Tami Caraballo (2014). Using Bioinformatics: Genetic Research [Dataset]. http://doi.org/10.6084/m9.figshare.936568
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    Dataset updated
    Feb 16, 2014
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    DataCitehttps://www.datacite.org/
    Authors
    Jeanne Chowning; Dina Kovarik; Sandra Porter; Joan Griswold; Jodie Spitze; Carol Farris; Karen Petersen; Tami Caraballo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Introductory curriculum for high school students (grades 9-12) that explores genetic research and bioinformatics. Posted on-line October 2012. Funded by NSF grant DRL-0833779

  18. f

    Table1_Bioinformatics on the Road: Taking Training to Students and...

    • frontiersin.figshare.com
    docx
    Updated Jun 8, 2023
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    Marcus Braga; Fabrício Araujo; Edian Franco; Kenny Pinheiro; Jakelyne Silva; Denner Maués; Sebastiao Neto; Lucas Pompeu; Luis Guimaraes; Adriana Carneiro; Igor Hamoy; Rommel Ramos (2023). Table1_Bioinformatics on the Road: Taking Training to Students and Researchers Beyond State Capitals.DOCX [Dataset]. http://doi.org/10.3389/feduc.2021.726930.s001
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    docxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers
    Authors
    Marcus Braga; Fabrício Araujo; Edian Franco; Kenny Pinheiro; Jakelyne Silva; Denner Maués; Sebastiao Neto; Lucas Pompeu; Luis Guimaraes; Adriana Carneiro; Igor Hamoy; Rommel Ramos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In Brazil, training capable bioinformaticians is done, mostly, in graduate programs, sometimes with experiences during the undergraduate period. However, this formation tends to be inefficient in attracting students to the area and mainly in attracting professionals to support research projects in research groups. To solve these issues, participation in short courses is important for training students and professionals in the usage of tools for specific areas that use bioinformatics, as well as in ways to develop solutions tailored to the local needs of academic institutions or research groups. In this aim, the project “Bioinformática na Estrada” (Bioinformatics on the Road) proposed improving bioinformaticians’ skills in undergraduate and graduate courses, primarily in the countryside of the State of Pará, in the Amazon region of Brazil. The project scope is practical courses focused on the areas of interest of the place where the courses are occurring to train and encourage students and researchers to work in this field, reducing the existing gap due to the lack of qualified bioinformatics professionals. Theoretical and practical workshops took place, such as Introduction to Bioinformatics, Computer Science Basics, Applications of Computational Intelligence applied to Bioinformatics and Biotechnology, Computational Tools for Bioinformatics, Soil Genomics and Research Perspectives and Horizons in the Amazon Region. In the end, 444 undergraduate and graduate students from higher education institutions in the state of Pará and other Brazilian states attended the events of the Bioinformatics on the Road project.

  19. q

    The Network for Integrating Bioinformatics into Life Sciences Education...

    • qubeshub.org
    Updated Jul 23, 2020
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    Anne Rosenwald; Elizabeth Dinsdale; William Morgan; Mark Pauley; William Tapprich; Eric Triplett; Jason Williams (2020). The Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE): Barriers to Integration [Dataset]. http://doi.org/10.25334/NHB4-X766
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    Dataset updated
    Jul 23, 2020
    Dataset provided by
    QUBES
    Authors
    Anne Rosenwald; Elizabeth Dinsdale; William Morgan; Mark Pauley; William Tapprich; Eric Triplett; Jason Williams
    Description

    The Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE) seeks to promote the use of bioinformatics and data science as a way to teach biology.

  20. L

    Life Science Analytics Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Jul 15, 2025
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    Archive Market Research (2025). Life Science Analytics Software Report [Dataset]. https://www.archivemarketresearch.com/reports/life-science-analytics-software-137485
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Life Science Analytics Software market is experiencing robust growth, driven by the increasing volume of biological data generated through advancements in genomics, proteomics, and other "-omics" fields. The need for sophisticated software solutions to analyze this complex data and extract meaningful insights is fueling market expansion. While precise figures for market size and CAGR are unavailable from the provided data, based on industry reports and comparable software markets, a reasonable estimation suggests a 2025 market size of approximately $2.5 billion, with a compound annual growth rate (CAGR) of 15% projected from 2025 to 2033. This growth trajectory is attributed to several key factors, including the rising adoption of cloud-based solutions for data storage and analysis, the increasing demand for AI and machine learning algorithms in drug discovery and development, and the growing focus on personalized medicine initiatives. The market is further propelled by the need for improved efficiency and reduced costs in research and development processes. Major players like Revvity, IBM, DNAnexus, Qiagen, Genedata, Clario, Thermo Fisher Scientific, Agilent Technologies, Illumina, and Oracle Corporation are driving innovation and competition within the market. These companies are continually developing and enhancing their software offerings, integrating advanced analytical capabilities and expanding their functionalities to cater to the diverse needs of researchers and pharmaceutical companies. Despite the positive growth outlook, challenges such as data security concerns, the complexity of software implementation, and the need for skilled personnel to utilize these tools effectively pose some restraints. However, ongoing technological advancements and increasing investments in bioinformatics infrastructure are expected to mitigate these challenges and drive sustained market growth in the coming years.

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IDB Datasets (2025). Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources [Dataset]. http://doi.org/10.60966/kwvb-wr19

Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources

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csv(276253), pdf(2989058), csv(355108)Available download formats
Dataset updated
Apr 10, 2025
Dataset provided by
IDB Datasets
License

Attribution-NonCommercial-NoDerivs 3.0 (CC BY-NC-ND 3.0)https://creativecommons.org/licenses/by-nc-nd/3.0/
License information was derived automatically

Time period covered
Jan 1, 2020 - Jan 1, 2021
Description

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

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