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.&...

This synthetic dataset was created to explore and develop machine learning models in bioinformatics. It contains 20,000 synthetic proteins, each with an amino acid sequence, calculated physicochemical properties, and a functional classification. The dataset includes the following columns: ID_Protein, a unique identifier for each protein; Sequence, a string of amino acids; Molecular_Weight, molecular weight calculated from the sequence; Isoelectric_Point, estimated isoelectric point based on the sequence composition; Hydrophobicity, average hydrophobicity calculated from the sequence; Total_Charge, sum of the charges of the amino acids in the sequence; Polar_Proportion, percentage of polar amino acids in the sequence; Nonpolar_Proportion, percentage of nonpolar amino acids in the sequence; Sequence_Length, total number of amino acids in the sequence; and Class, the functional class of the protein, one of five categories: Enzyme, Transport, Structural, Receptor, Other. While this is a simulated dataset, it was inspired by patterns observed in real protein datasets such as UniProt, a comprehensive database of protein sequences and annotations; the Kyte-Doolittle Scale, calculations of hydrophobicity; and Biopython, a tool for analyzing biological sequences. This dataset is ideal for training classification models for proteins, exploratory analysis of physicochemical properties of proteins, and building machine learning pipelines in bioinformatics. The dataset was created through sequence generation, where amino acid chains were randomly generated with lengths between 50 and 300 residues, property calculation using the Biopython library, and class assignment with classes randomly assigned for classification purposes. However, the sequences and properties do not represent real proteins but follow patterns observed in natural proteins, and the functional classes are simulated and do not correspond to actual biological characteristics. The dataset is divided into two subsets: Training, which includes 16,000 samples (proteinas_train.csv), and Testing, which includes 4,000 samples (proteinas_test.csv). This dataset was inspired by real bioinformatics challenges and designed to help researchers and developers explore machine learning applications in protein analysis.

Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a powerful genomic technology that is used for the global mapping and analysis of open chromatin regions. However, for users to process and analyze such data they either have to use a number of complicated bioinformatic tools or attempt to use the currently available ATAC-seq analysis software, which are not very user friendly and lack visualization of the ATAC-seq results. Because of these issues, biologists with minimal bioinformatics background who wish to process and analyze their own ATAC-seq data by themselves will find these tasks difficult and ultimately will need to seek help from bioinformatics experts. Moreover, none of the available tools provide complete solution for ATAC-seq data analysis. Therefore, to enable non-programming researchers to analyze ATAC-seq data on their own, we developed a tool called Graphical User interface for the Analysis and Visualization of ATAC-seq data (GUAVA). GUAVA is a standalone software that provides users with a seamless solution from beginning to end including adapter trimming, read mapping, the identification and differential analysis of ATAC-seq peaks, functional annotation, and the visualization of ATAC-seq results. We believe GUAVA will be a highly useful and time-saving tool for analyzing ATAC-seq data for biologists with minimal or no bioinformatics background. Since GUAVA can also operate through command-line, it can easily be integrated into existing pipelines, thus providing flexibility to users with computational experience.

Bioinformatics Software Market Outlook

The global bioinformatics software market size was valued at approximately USD 10 billion in 2023, and it is projected to reach around USD 25 billion by 2032, growing at a robust CAGR of 11% during the forecast period. This remarkable growth is fueled by the increased application of bioinformatics in drug discovery and development, the rising demand for personalized medicine, and the ongoing advancements in sequencing technologies. The convergence of biology and information technology has led to the optimization of biological data management, propelling the market's expansion as it transforms the landscape of biotechnology and pharmaceutical research. The rapid integration of artificial intelligence and machine learning techniques to process complex biological data further accentuates the growth trajectory of this market.

An essential growth factor for the bioinformatics software market is the burgeoning demand for sequencing technologies. The decreasing cost of sequencing has led to a massive increase in the volume of genomic data generated, necessitating advanced software solutions to manage and interpret this data efficiently. This demand is particularly evident in genomics and proteomics, where bioinformatics software plays a critical role in analyzing and visualizing large datasets. Additionally, the adoption of cloud computing in bioinformatics offers scalable resources and cost-effective solutions for data storage and processing, further fueling market growth. The increasing collaboration between research institutions and software companies to develop innovative bioinformatics tools is also contributing positively to market expansion.

Another significant driver is the growth of personalized medicine, which relies heavily on bioinformatics for the analysis of individual genetic information to tailor therapeutic strategies. As healthcare systems worldwide move towards precision medicine, the demand for bioinformatics software that can integrate genetic, phenotypic, and environmental data becomes more pronounced. This trend is not only transforming patient care but also significantly impacting drug development processes, as pharmaceutical companies aim to create more effective and targeted therapies. The strategic partnerships and collaborations between biotech firms and bioinformatics software providers are critical in advancing personalized medicine and enhancing patient outcomes.

The increasing prevalence of complex diseases such as cancer and neurological disorders necessitates comprehensive research efforts, driving the need for robust bioinformatics software. These diseases require multi-omics approaches for better understanding, diagnosis, and treatment, where bioinformatics tools are indispensable. The ongoing research and development activities in this area, supported by government funding and private investments, are fostering innovation in bioinformatics solutions. Furthermore, the development of user-friendly and intuitive software interfaces is expanding the market beyond specialized research labs to include clinical settings and hospitals, broadening the potential user base and enhancing market penetration.

From a regional perspective, North America currently leads the bioinformatics software market, thanks to its advanced technological infrastructure, significant investment in healthcare R&D, and the presence of numerous key market players. The region accounted for the largest market share in 2023 and is expected to maintain its dominance throughout the forecast period. Meanwhile, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by increasing investments in biotechnology and pharmaceutical research, expanding healthcare infrastructure, and the rising adoption of bioinformatics in emerging economies like China and India. Europe's market growth is also significant, supported by substantial funding for genomic research and a strong focus on precision medicine initiatives.

Lifesciences Data Mining and Visualization are becoming increasingly vital in the bioinformatics software market. As the volume of biological data continues to grow exponentially, the need for sophisticated tools to mine and visualize this data is paramount. These tools enable researchers to uncover hidden patterns and insights from complex datasets, facilitating breakthroughs in genomics, proteomics, and other life sciences fields. The integration of advanced data mining techniques with visualization capabilities allows for a more intuitive

Snapshot img

Bioinformatics Market Size 2024-2028

The bioinformatics market size is forecast to increase by USD 13.2 billion at a CAGR of 16.59% between 2023 and 2028. The market is experiencing significant growth due to the reduction in the cost of genetic sequencing and the development of sophisticated bioinformatics tools for next-generation sequencing (NGS). These advancements are enabling the identification and analysis of disease biomarkers, leading to the discovery of new therapeutic strategies. The market is also driven by the increasing demand for database development and management systems to store and analyze the vast amounts of data generated from NGS. Furthermore, the potential of gene therapy and drug development in treating various diseases is fueling the market growth. However, the shortage of trained laboratory professionals poses a challenge to the market, as the analysis of complex genomic data requires specialized expertise.

What will be the Size of the Bioinformatics Market During the Forecast Period?

To learn more about the bioinformatics market report, Request Free Sample

Bioinformatics is a rapidly growing market, driven by advancements in genome sequencing and NGS technologies. Precision medicine, which utilizes genomic information for personalized healthcare, is a key application area. The market is witnessing a significant decrease in equipment costs, making genomics instruments more accessible to researchers and healthcare providers. Transcriptomics, which focuses on the study of RNA, is another emerging field. Virus research is a significant application area, with a focus on transmission chains, public health control, and containment measures. Virus variability and vaccine development are major challenges, driving the need for advanced diagnostic methods. Key players in the market include Illumina and Eurofins Scientific.

Moreover, companies are making strides in addressing this challenge by providing comprehensive solutions for bioinformatics analysis and data management. Big data is another key trend in the market, with the use of advanced algorithms and machine learning techniques to extract valuable insights from genomic data. Overall, the market is poised for strong growth, driven by technological advancements, increasing demand for personalized medicine, and the potential to revolutionize disease diagnosis and treatment. In addition, these companies provide a range of services, from DNA and RNA sequencing to bioinformatics analysis and diagnostic testing. The market is expected to grow significantly due to the increasing demand for accurate and timely diagnostic methods and the ongoing research in the field of genomics and transcriptomics.

The bioinformatics market is expanding rapidly, driven by advancements in genomics data analysis, next-gen sequencing, and precision medicine. Cloud-based bioinformatics solutions and AI in bioinformatics are revolutionizing molecular diagnostics, drug discovery platforms, and protein analysis tools. The market emphasizes genomic data storage, personalized healthcare, and biomarker discovery. With bioinformatics software, computational biology, and integrative bioinformatics solutions, bioinformatics as a service plays a pivotal role in advancing modern healthcare.

Bioinformatics Market Segmentation

The bioinformatics market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Molecular phylogenetics
  Transcriptomic
  Proteomics
  Metabolomics


Product

  Platforms
  Tools
  Services


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France


  Asia



  Rest of World (ROW)

By Application Insights

The molecular phylogenetics segment is estimated to witness significant growth during the forecast period. Bioinformatics, a critical field in molecular biology, encompasses the application of computational tools and techniques to analyze biological data. One significant area within bioinformatics is molecular phylogenetics, which utilizes molecular data to explore evolutionary relationships among various species. This technique has transformed the biological landscape by offering more precise and comprehensive insights into the interconnections among living organisms. In the international market, molecular phylogenetics is a vital instrument in numerous research domains, such as clinical diagnostics, drug discovery, RNA-based therapeutics, and conservation biology. For instance, in the realm of viral research, molecular phylogenetics is extensively employed to examine the evolution of viruses.

In addition, by deciphering the molecular data of distinct strains of viruses, scientists can trace the origins and dissemination patterns of these pathoge

The file is a binary alignment file (BAM file) of the illumina sequencing data of sample Psae provided as test data for the publication of the tool SASpector.

Bioinformatics Services Market size was valued at USD 11.1 Billion in 2023 and is projected to reach USD 3.58 Billion by 2031, growing at a CAGR of 15.06% from 2024-2031.

Bioinformatics Services Market: Definition/ Overview

Bioinformatics services cover a wide range of computational tools and methods for managing, analyzing, and interpreting biological data. These services enable the integration of data from domains such as genomics, proteomics, transcriptomics, and metabolomics to provide insights into biological systems. Drug discovery, customized medicine, gene sequencing, and biological data management are some of the most important applications of bioinformatics. Researchers and healthcare professionals use these services to analyze big datasets, detect disease markers, and develop tailored medicines, considerably improving the precision and efficiency of life science research.

Database of curated links to molecular resources, tools and databases selected on the basis of recommendations from bioinformatics experts in the field. This resource relies on input from its community of bioinformatics users for suggestions. Starting in 2003, it has also started listing all links contained in the NAR Webserver issue. The different types of information available in this portal: * Computer Related: This category contains links to resources relating to programming languages often used in bioinformatics. Other tools of the trade, such as web development and database resources, are also included here. * Sequence Comparison: Tools and resources for the comparison of sequences including sequence similarity searching, alignment tools, and general comparative genomics resources. * DNA: This category contains links to useful resources for DNA sequence analyses such as tools for comparative sequence analysis and sequence assembly. Links to programs for sequence manipulation, primer design, and sequence retrieval and submission are also listed here. * Education: Links to information about the techniques, materials, people, places, and events of the greater bioinformatics community. Included are current news headlines, literature sources, educational material and links to bioinformatics courses and workshops. * Expression: Links to tools for predicting the expression, alternative splicing, and regulation of a gene sequence are found here. This section also contains links to databases, methods, and analysis tools for protein expression, SAGE, EST, and microarray data. * Human Genome: This section contains links to draft annotations of the human genome in addition to resources for sequence polymorphisms and genomics. Also included are links related to ethical discussions surrounding the study of the human genome. * Literature: Links to resources related to published literature, including tools to search for articles and through literature abstracts. Additional text mining resources, open access resources, and literature goldmines are also listed. * Model Organisms: Included in this category are links to resources for various model organisms ranging from mammals to microbes. These include databases and tools for genome scale analyses. * Other Molecules: Bioinformatics tools related to molecules other than DNA, RNA, and protein. This category will include resources for the bioinformatics of small molecules as well as for other biopolymers including carbohydrates and metabolites. * Protein: This category contains links to useful resources for protein sequence and structure analyses. Resources for phylogenetic analyses, prediction of protein features, and analyses of interactions are also found here. * RNA: Resources include links to sequence retrieval programs, structure prediction and visualization tools, motif search programs, and information on various functional RNAs.

List of bioinformatics tools and databases students used.

The TReCCA Analyser is conceived to facilitate, speed up and intensify the analysis and representation of your time-resolved data, more specically in the case of cell culture assays. Without having to type any formula, it will perform at wish the following calculations: Control condition normalisation. Technical replicate averaging and standard deviation calculation. Smoothing and slope calculation of the data in order to obtain the rate of change. IC50/EC50 determination of a substance in a time-resolved fashion.

Introduction

The Global Bioinformatics Services Market is poised for substantial growth, projected to increase from USD 2.9 billion in 2023 to USD 10.7 billion by 2033, achieving a compound annual growth rate (CAGR) of 13.9%. This market expansion is fueled by several key factors including technological advancements in genomics and the increasing complexity of biological datasets, which necessitate advanced computational technologies for efficient data management, analysis, and interpretation. These technologies are crucial for advancing medical research and improving patient care, particularly through personalized treatment plans and precision medicine.

Institutions like the Mayo Clinic are significantly contributing to this growth by expanding their bioinformatics services to support translational research and enhance patient care through the integration of large multi-omics data sets. Additionally, prominent educational institutions such as Stanford and Georgetown University are advancing their bioinformatics programs to equip the next generation of professionals with the necessary skills to address complex biomedical challenges using computational and quantitative methods.

The sector is also witnessing a surge in demand within the healthcare and pharmaceutical industries, where bioinformatics tools are integral to drug discovery and disease diagnosis. This demand drives the development of therapeutic strategies and deepens the understanding of disease mechanisms, further boosting the market growth. Research initiatives and collaborations, such as those at Harvard Medical School’s Department of Biomedical Informatics and Stanford's Biomedical Informatics Research division, are key in transforming biomedical data into actionable insights for precision medicine.

In terms of recent industry developments, in January 2024, Qiagen announced a significant expansion of investments into its Qiagen Digital Insights (QDI) business. This expansion, fueled by robust sales of approximately $100 million in 2023, is set to enhance QDI's bioinformatics capabilities, including launching at least five new products and broadening the applications of Artificial Intelligence and Natural Language Processing within the sector.

Furthermore, in January 2023, Agilent Technologies unveiled a major investment of $725 million to double its manufacturing capacity for nucleic acid-based therapeutics, in response to the rapid growth in the therapeutic oligonucleotides market, projected to reach $2.4 billion by 2027. This expansion will introduce two new manufacturing lines to meet the escalating demand for siRNA, antisense, and CRISPR guide RNA molecules, reinforcing Agilent's market presence and capacity in this fast-evolving field.

Purpose

These data can be used to test my tool delfies on real data, to get a concrete sense of its inputs/outputs and test that it is
properly installed.

Description

Genome

I downloaded the genome of Oscheius onirici, accession: GCA_932521025.

I subsampled the genome to the last 2kbp of chromosome I, which contains an elimination breakpoint,
using `seqkit` v2.8.2, giving the FASTA file in this release.

Sequencing data

I then downloaded the following sequencing data for *O. onirici*, from the European Nucleotide Archive:

• ERR5967937: Illumina NovaSeq 6000 paired end short reads. Reads are 2x150bp with average per-base quality of Q27.
• ERR10796202: Oxford Nanopore PromethION long reads. Reads have average length 11.9kbp and average per-base quality Q11.4.
• ERR7979900: Pacific Biosciences (PacBio) Sequel II long reads. Reads have average length 11.1kbp and average per-base quality Q28.
  
  

And aligned them to the above genome with `minimap2` version 2.26-r1175, using the following presets:
"map-ont" for the Nanopore data, "map-hifi" for the PacBio data, "sr" for the Illumina data.

After sorting with `samtools`, this gives the BAM files in this release.

Running delfies

I then ran `delfies` version 0.6.0 on each BAM and genome, as:

```sh
delfies --threads 16 \
--telo_forward_seq TTAGGC \
--breakpoint_type all \
--min_mapq 20 \
--min_supporting_reads 6 \
\${genome} \${bam} \${odirname}
```

The three resulting output directories are in this release, prefixed with `delfies_`.

A single, identical breakpoint is found using all three BAMs (see files '*breakpoint_locations.bed').

Data source

The above raw data were produced and released by the Wellcome Sanger Institute as part of projects
PRJEB51305 and PRJEB59023.

Recent advances in whole genome sequencing have made the technology available for routine use in microbiological laboratories. However, a major obstacle for using this technology is the availability of simple and automatic bioinformatics tools. Based on previously published and already available web-based tools we developed a single pipeline for batch uploading of whole genome sequencing data from multiple bacterial isolates. The pipeline will automatically identify the bacterial species and, if applicable, assemble the genome, identify the multilocus sequence type, plasmids, virulence genes and antimicrobial resistance genes. A short printable report for each sample will be provided and an Excel spreadsheet containing all the metadata and a summary of the results for all submitted samples can be downloaded. The pipeline was benchmarked using datasets previously used to test the individual services. The reported results enable a rapid overview of the major results, and comparing that to the previously found results showed that the platform is reliable and able to correctly predict the species and find most of the expected genes automatically. In conclusion, a combined bioinformatics platform was developed and made publicly available, providing easy-to-use automated analysis of bacterial whole genome sequencing data. The platform may be of immediate relevance as a guide for investigators using whole genome sequencing for clinical diagnostics and surveillance. The platform is freely available at: https://cge.cbs.dtu.dk/services/CGEpipeline-1.1 and it is the intention that it will continue to be expanded with new features as these become available.

The size of the Bioinformatics Market was valued at USD 11.44 billion in 2024 and is projected to reach USD 33.50 billion by 2033, with an expected CAGR of 16.59% during the forecast period. The bioinformatics industry is growing rapidly, fueled by technological advancements and the augmented demand for personalized medicine. Bioinformatics, an integration of biology, computer science, and information technology, is pivotal in managing and analyzing biological data, more so in genomics and proteomics. The application of bioinformatics in drug research and development has improved the efficiency of pharmaceutical research by streamlining the identification of therapeutic targets and biomarkers. Also, the declining cost of genome sequencing has opened up bioinformatics tools, driving further market growth. The market is dominated by a wide variety of applications such as microbial genome analysis, gene engineering, drug discovery, personalized medicine, and other 'omics' research. Bioinformatics tools, platforms, and services are among the main products provided by industry players in this market. Academic collaborations and industry partners have driven innovation, and as a result, high-end algorithms and software solutions with high-end biological data complexity analysis capabilities have emerged. In spite of the encouraging growth trend, the bioinformatics market is challenged by issues like data privacy and the necessity for standardized data formats. Exorbitant prices of sophisticated bioinformatics tools and the need for trained professionals to manage these systems could also act as a dampener for market growth. Nevertheless, growing markets and ongoing technological developments offer lucrative opportunities for market players.

The Report Covers Global Bioinformatics Services Market Growth & Insights. The Market is Segmented by Products and Services (Knowledge Management Tools, Bioinformatics Platform, and Bioinformatics Services), Applications (Microbial Genome, Gene Engineering, Drug Development, Personalized Medicine, Omics, and Other Applications), and Geography (North America, Europe, Asia-Pacific, Middle East and Africa, and South America). The value is provided in (USD million) for the above segments.

Additional file 1. SRA IDs of datasets downloaded to conduct the QUOD analysis of the A. thaliana genomes.

The archive "simulated_forward_reverse_reads.zip" contains the sequence reads simulated with Grinder.

The archive "species_abundance_per_sample.zip" contains 1 file per sample with the relative proportions of reads per species, in the simulated samples.

The archive "real_eDNA_forward_reverse_reads.zip" contains the real eDNA metabarcoding data collected in the Mediterranean Sea.

A named entity recognizer for the recovery of bioinformatics databases and software from primary literature. The entity recognizer achieved an F-measure of between 63% and 91% on different datasets (63%78% at the document level). Results from full-text literature analysis for both Genome Biology and BMC Bioinformatics journals are available as well as a full list of references and links for the various major resources mentioned. Data generated data can be used for exploration of bioinformatics database and software usage. This tool makes heavy use of GATE (version 6.1). It can be run in sandbox mode, which means a installation of GATE is not a prerequisite, but you will instead need to point the config to a unzipped gate_plugins directory instead (located in the bin/BMC_Files directory).

The relationship between protein structure and function is a foundational concept in undergraduate biochemistry. We find this theme is best presented with assignments that encourage exploration and analysis. Here, we share a series of four assignments that use open-source, online molecular visualization and bioinformatics tools to examine the interaction between the SARS-CoV-2 spike protein and the ACE2 receptor. The interaction between these two proteins initiates SARS-CoV-2 infection of human host cells and is the cause of COVID-19. In assignment I, students identify sequences with homology to the SARS-CoV-2 spike protein and use them to build a primary sequence alignment. Students make connections to a linked primary research article as an example of how scientists use molecular and phylogenetic analysis to explore the origins of a novel virus. Assignments II through IV teach students to use an online molecular visualization tool for analysis of secondary, tertiary, and quaternary structure. Emphasis is placed on identification of noncovalent interactions that stabilize the SARS-CoV-2 spike protein and mediate its interaction with ACE2. We assigned this project to upper-level undergraduate biochemistry students at a public university and liberal arts college. Students in our courses completed the project as individual homework assignments. However, we can easily envision implementation of this project during multiple in-class sessions or in a biochemistry laboratory using in-person or remote learning. We share this project as a resource for instructors who aim to teach protein structure and function using inquiry-based molecular visualization activities.

Primary image: Exploration of SARS-CoV-2 spike protein: student generated data from assignments I - IV. Includes examples of figures submitted by students, including a sequence alignment and representations of 3D protein structure generated using UCSF Chimera. The primary image includes student generated data and a cartoon from Pixabay, an online repository of copyright free art.

No description was included in this Dataset collected from the OSF