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
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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.

  2. 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
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    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

  3. 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
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    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.

  4. c

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

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    + more versions
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    Cognitive Market Research, Global Bioinformatics Service Market Report 2025 Edition, Market Size, Share, CAGR, Forecast, Revenue [Dataset]. https://www.cognitivemarketresearch.com/bioinformatics-service-market-report
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    pdf,excel,csv,pptAvailable download formats
    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.&...

  5. 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
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    txtAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    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)

  6. 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
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    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.

  7. d

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

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    Updated Apr 21, 2025
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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
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    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

  8. a

    [Coursera] Bioinformatics: Life Sciences on Your Computer (Johns Hopkins...

    • academictorrents.com
    bittorrent
    Updated Mar 5, 2017
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    Johns Hopkins University (2017). [Coursera] Bioinformatics: Life Sciences on Your Computer (Johns Hopkins University) (bioinform) [Dataset]. https://academictorrents.com/details/b02188bbb764f7f5fdd499c5144add35f56ed3e7
    Explore at:
    bittorrent(498196877)Available download formats
    Dataset updated
    Mar 5, 2017
    Dataset authored and provided by
    Johns Hopkins University
    License

    https://academictorrents.com/nolicensespecifiedhttps://academictorrents.com/nolicensespecified

    Description

    [Coursera] Bioinformatics: Life Sciences on Your Computer (Johns Hopkins University) (bioinform)

  9. 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
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    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.

  10. 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
    Figsharehttp://figshare.com/
    DataCitehttps://www.datacite.org/
    figshare
    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

  11. 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.

  12. n

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

    • data.niaid.nih.gov
    • datadryad.org
    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.

  13. q

    Integration of Bioinformatics into Life Science Curricula: Community...

    • qubeshub.org
    Updated Jul 23, 2020
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    Adam Kleinschmit; Rachel Cook; Barbara Murdoch; Elizabeth Ryder; William Tapprich (2020). Integration of Bioinformatics into Life Science Curricula: Community Development, Dissemination, and Assessment of a NIBLSE Learning Resource [Dataset]. http://doi.org/10.25334/F138-SS53
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    Dataset updated
    Jul 23, 2020
    Dataset provided by
    QUBES
    Authors
    Adam Kleinschmit; Rachel Cook; Barbara Murdoch; Elizabeth Ryder; William Tapprich
    Description

    Big data and computational tools have transformed the way we address biological questions. To prepare undergraduates for tomorrow’s challenges, life science curricula should integrate the understanding and use of these tools at all levels.

  14. Bioinformatics Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 28, 2025
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    Growth Market Reports (2025). Bioinformatics Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/bioinformatics-market-global-industry-analysis
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    pptx, csv, pdfAvailable download formats
    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Bioinformatics Market Outlook



    According to our latest research, the global bioinformatics market size reached USD 16.2 billion in 2024, reflecting robust industry momentum. The market is exhibiting a healthy compound annual growth rate (CAGR) of 13.1% and is projected to attain a value of USD 42.7 billion by 2033. This vigorous expansion is driven by the rapid integration of computational tools in life sciences, accelerating advancements in genomics, proteomics, and drug discovery. The increasing demand for personalized medicine and the surge in big data analytics within biological research are pivotal growth factors shaping the bioinformatics landscape.




    One of the principal growth factors fueling the bioinformatics market is the explosive rise in genomics research, particularly in the context of next-generation sequencing (NGS) technologies. The cost of sequencing has plummeted over the past decade, making large-scale genomic projects more accessible to both public and private sector entities. This democratization of sequencing technology has led to a significant influx of biological data, necessitating sophisticated bioinformatics tools for analysis, interpretation, and storage. The development of cloud-based bioinformatics platforms further enables researchers to manage and analyze vast datasets efficiently, fostering greater collaboration and innovation in genomics-driven healthcare, agriculture, and environmental sciences.




    Another critical driver is the increasing adoption of bioinformatics in drug discovery and development. Pharmaceutical and biotechnology companies are leveraging bioinformatics solutions to accelerate target identification, drug candidate screening, and biomarker discovery. The integration of artificial intelligence (AI) and machine learning algorithms within bioinformatics workflows is enhancing the predictive accuracy of drug response models and facilitating the identification of novel therapeutic targets. This not only shortens the drug development lifecycle but also reduces costs and improves the likelihood of clinical success. As precision medicine gains traction, bioinformatics is becoming indispensable in tailoring treatments based on individual genetic profiles, further propelling market growth across the healthcare sector.




    The expanding application of bioinformatics beyond human health is another significant growth factor. In agriculture, bioinformatics is instrumental in crop improvement, pest resistance, and livestock management through the analysis of genomic and phenotypic data. Environmental biotechnology also benefits from bioinformatics in monitoring biodiversity, tracking pathogen outbreaks, and assessing ecosystem health. Moreover, forensic biotechnology utilizes bioinformatics for DNA profiling and criminal investigations. These diverse applications underscore the versatility and critical importance of bioinformatics across multiple sectors, driving sustained investment and innovation in the market.




    From a regional perspective, North America continues to dominate the global bioinformatics market, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of major industry players, significant government funding for genomics research, and a well-established healthcare infrastructure. Europe follows closely, supported by strong academic research and collaborative initiatives such as the European Bioinformatics Institute. Meanwhile, the Asia Pacific region is witnessing the fastest growth, fueled by rising investments in life sciences, expanding biotechnology industries, and increasing adoption of digital health solutions. Latin America and the Middle East & Africa are also emerging as promising markets, albeit at a comparatively nascent stage, driven by growing awareness and infrastructural improvements.





    Product & Service Analysis



    The bioinformatics market by product & service is segmented into software, hardware, and services, each playing a pivotal role in driving the

  15. 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/
    figshare
    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

  16. d

    Two-step mixed model approach to analyzing differential alternative RNA...

    • datadryad.org
    • zenodo.org
    zip
    Updated Sep 28, 2020
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    Li Luo; Huining Kang; Xichen Li; Scott Ness; Christine Stidley (2020). Two-step mixed model approach to analyzing differential alternative RNA splicing: Datasets and R scripts for analysis of alternative splicing [Dataset]. http://doi.org/10.5061/dryad.66t1g1k0h
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    zipAvailable download formats
    Dataset updated
    Sep 28, 2020
    Dataset provided by
    Dryad
    Authors
    Li Luo; Huining Kang; Xichen Li; Scott Ness; Christine Stidley
    Time period covered
    2020
    Description

    The dataset was collected through whole-transcriptome RNA-Sequencing technologies. The processing method was described in the manuscript.

  17. 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.

  18. L

    Life Science Tools and Reagents Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 4, 2025
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    Market Report Analytics (2025). Life Science Tools and Reagents Report [Dataset]. https://www.marketreportanalytics.com/reports/life-science-tools-and-reagents-58984
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 4, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The life science tools and reagents market, valued at $95650 million in 2025, is projected to experience robust growth, driven by several key factors. The increasing prevalence of chronic diseases globally fuels demand for advanced diagnostic tools and reagents for research and development in pharmaceuticals and biotechnology. Furthermore, the rising adoption of personalized medicine and the burgeoning field of genomics are significantly boosting market expansion. Technological advancements, such as the development of high-throughput screening platforms and automation in laboratory processes, are enhancing efficiency and driving market growth. The proteomics, cell biology, epigenetics, and metabolomics application segments are key contributors to market expansion due to ongoing research initiatives in these areas. Within the types segment, tools like next-generation sequencing platforms and advanced microscopy equipment represent a significant market share, complemented by the consistent demand for a wide range of reagents including antibodies, enzymes, and assay kits. Competition among established players like Thermo Fisher Scientific, Illumina, and Bio-Rad, alongside the emergence of innovative smaller companies, ensures a dynamic and rapidly evolving market landscape. However, market growth is not without its challenges. High research and development costs for innovative tools and reagents can limit market accessibility, especially for smaller research institutions and developing nations. Stringent regulatory approvals and the complexity of intellectual property rights can further hinder market penetration for new entrants. Despite these restraints, the long-term outlook for the life science tools and reagents market remains positive, fuelled by continuous investment in research and development, increasing funding for scientific research from both public and private sources, and the ongoing push for advancements in healthcare technologies. The market is expected to experience a compound annual growth rate (CAGR) exceeding 3.1% through 2033, solidifying its position as a vital sector within the broader life sciences industry.

  19. m

    SARS-CoV-2 Surface glycoproteins Alignment Data

    • data.mendeley.com
    Updated Aug 20, 2021
    + more versions
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    Done Stojanov (2021). SARS-CoV-2 Surface glycoproteins Alignment Data [Dataset]. http://doi.org/10.17632/btb5ffk247.1
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    Dataset updated
    Aug 20, 2021
    Authors
    Done Stojanov
    License

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

    Description
    1. SARS-CoV-2SpikeProteinMutations.docx contains data on mutations found in aligned SARS-CoV-2 surface glycoproteins.
    2. SARS-CoV-2SpikeProteinVariants.docx contains data on computed SARS-CoV-2 surface glycoprotein variants in Europe.
  20. o

    WORKSHOP: Machine learning in the life sciences

    • explore.openaire.eu
    Updated Jun 11, 2024
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    Benjamin Goudey; Erin Graham; William Pinzon Perez; Giorgia Mori; Joseph McConnell; Jessica Chung; Marius Mather (2024). WORKSHOP: Machine learning in the life sciences [Dataset]. http://doi.org/10.5281/zenodo.14676359
    Explore at:
    Dataset updated
    Jun 11, 2024
    Authors
    Benjamin Goudey; Erin Graham; William Pinzon Perez; Giorgia Mori; Joseph McConnell; Jessica Chung; Marius Mather
    Description

    This record includes training materials associated with the Australian BioCommons workshop ‘Machine Learning in the Life Sciences’. This on 11 June 2024. Event description Machine learning promises to revolutionise life science research by speeding up data analysis, enabling prediction of biological patterns and modelling complex biological systems. But what exactly is machine learning and when should you use it? This hands-on online workshop provides a high-level introduction to machine learning: what it is, its advantages and disadvantages compared to traditional modelling approaches and the types of scenarios where it may be the right tool for the job. Using example datasets and basic machine learning pipelines we contrast a few commonly used algorithms for constructing predictive models and explore some of their trade-offs. We discuss common pitfalls in how machine learning is applied and evaluated, with a focus on its application in the life sciences, to help you recognise overly optimistic results. We discuss how and why such errors arise and strategies to avoid them. Lead trainer: Dr Benjamin Goudey, Research Fellow, Florey Department of Neuroscience and Mental Health Facilitators: Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) / James Cook University William Pinzon Perez, Queensland Cyber Infrastructure Foundation (QCIF) Dr Giorgia Mori, Sydney Informatics Hub, University of Sydney Joseph McConnell, University of Adelaide Jessica Chung, Melbourne Bioinformatics 0000-0002-0627-0955 Host: Dr Melissa Burke, Australian BioCommons. Training materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Schedule (PDF): Schedule describing the timing of sessions for the in person and online events Materials shared elsewhere: This workshop follows the Google Colab Notebook developed by Dr Benjamin Goudey: https://github.com/bwgoudey/IntroMLforLifeScienceWorkshopR

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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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