QIAGEN is a German-founded multinational provider of sample and assay technologies for molecular diagnostics, applied testing, academic and pharmaceutical research. The company operates in more than 35 offices in over 25 countries. QIAGEN N.V., the global corporate headquarter of the QIAGEN group, is located in Venlo, The Netherlands. The main operative headquarters are located in Hilden, Germany. European, American, and Asian regional headquarters are located in respectively Hilden, Germany; Germantown, Maryland, United States; and Shanghai, China. QIAGEN's shares are listed at the NYSE and at the Frankfurt Stock Exchange in the Prime Standard. Thierry Bernard is the company's Chief Executive Officer (CEO).
The completion of the human genome sequencing in the early 2000s was a turning point in genomics research. Scientists have conducted series of research into the activities of genes and the genome as a whole. The human genome contains around 3 billion base pairs nucleotide, and the huge quantity of data created necessitates the development of an accessible tool to explore and interpret this information in order to investigate the genetic basis of disease, evolution, and biological processes. The field of genomics has continued to grow, with new sequencing technologies and computational tool making it easier to study the genome.
Gene Codes Corporation is a privately owned international firm based in Ann Arbor, Michigan, which specializes in bioinformatics software for genetic sequence analysis. Its flagship software product, Sequencher, is a sequencing software used throughout the world. Its targeted use is by researchers at academic and government labs as well as biotechnology and pharmaceutical companies for DNA sequence assembly.
CLC bio was a bioinformatics software company that developed a software suite subsequently purchased by QIAGEN.
Synopsys Simpleware ScanIP is a 3D image processing and model generation software program developed by Synopsys Inc. to visualise, analyse, quantify, segment and export 3D image data from magnetic resonance imaging (MRI), computed tomography (CT), microtomography and other modalities for computer-aided design (CAD), finite element analysis (FEA), computational fluid dynamics (CFD), and 3D printing. The software is used in the life sciences, materials science, nondestructive testing, reverse engineering and petrophysics.
QIAGEN Silicon Valley is a company based in Redwood City, California, USA, that develops software to analyze complex biological systems. QIAGEN Silicon Valley's first product, IPA, was introduced in 2003, and is used to help researchers analyze omics data and model biological systems. The software has been cited in thousands of scientific molecular biology publications and is one of several tools for systems biology researchers and bioinformaticians in drug discovery and institutional research.
AstridBio Ltd. is a privately held Biotechnology company with office in Hungary. AstridBio's focus is biobanking software development, data management and analysis for genomics research. Its clients include academic research institutes, pharmaceutical and biotech companies.
De novo transcriptome assembly is the de novo sequence assembly method of creating a transcriptome without the aid of a reference genome.
Integromics was a global bioinformatics company headquartered in Granada, Spain and Madrid. The company had subsidiaries in the United States and United Kingdom, and distributors in 10 countries. Integromics specialised in bioinformatics software for data management and data analysis in genomics and proteomics. The company provided a line of products that serve the gene expression, sequencing, and proteomics markets. Customers include genomic research centers, pharmaceutical companies, academic institutions, clinical research organizations, and biotechnology companies.
In the field of cellular biology, single-cell analysis and subcellular analysis is the study of genomics, transcriptomics, proteomics, metabolomics and cell–cell interactions at the single cell level. The concept of single-cell analysis originated in the 1970s. Before the discovery of heterogeneity, single-cell analysis mainly referred to the analysis or manipulation of an individual cell in a bulk population of cells at a particular condition using optical or electronic microscope. To date, due to the heterogeneity seen in both eukaryotic and prokaryotic cell populations, analyzing a single cell makes it possible to discover mechanisms not seen when studying a bulk population of cells. Technologies such as fluorescence-activated cell sorting (FACS) allow the precise isolation of selected single cells from complex samples, while high throughput single cell partitioning technologies, enable the simultaneous molecular analysis of hundreds or thousands of single unsorted cells; this is particularly useful for the analysis of transcriptome variation in genotypically identical cells, allowing the definition of otherwise undetectable cell subtypes. The development of new technologies is increasing our ability to analyze the genome and transcriptome of single cells, as well as to quantify their proteome and metabolome. Mass spectrometry techniques have become important analytical tools for proteomic and metabolomic analysis of single cells. Recent advances have enabled quantifying thousands of protein across hundreds of single cells, and thus make possible new types of analysis. In situ sequencing and fluorescence in situ hybridization (FISH) do not require that cells be isolated and are increasingly being used for analysis of tissues.
NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016. The package is similar to other network visualization tools such as Pajek, UCINet, and Gephi. It is widely applied in ring, mapping of vertex and edge, and customizable visual attributes and tags. NodeXL enables researchers to undertake social network analysis work metrics such as centrality, degree, and clustering, as well as monitor relational data and describe the overall relational network structure. When applied to Twitter data analysis, it showed the total network of all users participating in public discussion and its internal structure through data mining. It allows social Network analysis (SNA) to emphasize the relationships rather than the isolated individuals or organizations, allowing interested parties to investigate the two-way dialogue between organizations and the public. SNA also provides a flexible measurement system and parameter selection to confirm the influential nodes in the network, such as in-degree and out-degree centrality. The software contains network visualization, social network analysis features, access to social media network data importers, advanced network metrics, and automation.
Gene set enrichment analysis (GSEA) (also called functional enrichment analysis or pathway enrichment analysis) is a method to identify classes of genes or proteins that are over-represented in a large set of genes or proteins, and may have an association with different phenotypes (e.g. different organism growth patterns or diseases). The method uses statistical approaches to identify significantly enriched or depleted groups of genes. Transcriptomics technologies and proteomics results often identify thousands of genes, which are used for the analysis.
The High-performance Integrated Virtual Environment (HIVE) is a distributed computing environment used for healthcare-IT and biological research, including analysis of Next Generation Sequencing (NGS) data, preclinical, clinical and post market data, adverse events, metagenomic data, etc. Currently it is supported and continuously developed by US Food and Drug Administration, George Washington University, and by DNA-HIVE, WHISE-Global and Embleema. HIVE currently operates fully functionally within the US FDA supporting wide variety (+60) of regulatory research and regulatory review projects as well as for supporting MDEpiNet medical device postmarket registries. Academic deployments of HIVE are used for research activities and publications in NGS analytics, cancer research, microbiome research and in educational programs for students at GWU. Commercial enterprises use HIVE for oncology, microbiology, vaccine manufacturing, gene editing, healthcare-IT, harmonization of real-world data, in preclinical research and clinical studies.
Multiomics, multi-omics, integrative omics, "panomics" or "pan-omics" is a biological analysis approach in which the data sets are multiple "omes", such as the genome, proteome, transcriptome, epigenome, metabolome, and microbiome ; in other words, the use of multiple omics technologies to study life in a concerted way. By combining these "omes", scientists can analyze complex biological big data to find novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology. In doing so, multiomics integrates diverse omics data to find a coherently matching geno-pheno-envirotype relationship or association. The OmicTools service lists more than 99 softwares related to multiomic data analysis, as well as more than 99 databases on the topic.
Sophia Genetics is a data-driven medicine software company with headquarters in Lausanne, Switzerland and Boston, Massachusetts. It provides genomic and radiomic analysis for hospitals, laboratories, and biopharma institutions. The company was ranked among the 50 smartest companies by the MIT Technology Review in 2017. The company went public on the Nasdaq in 2021, floating at $1.1B.
Deterministic Barcoding in Tissue for Spatial Omics Sequencing (DBiT-seq) was developed at Yale University by Rong Fan and colleagues in 2020 to create a multi-omics approach for studying spatial gene expression heterogenicity within a tissue sample. This method can be used for the co-mapping mRNA and protein levels at a near single-cell resolution in fresh or frozen formaldehyde-fixed tissue samples. DBiT-seq utilizes next generation sequencing (NGS) and microfluidics. This method allows for simultaneous spatial transcriptomic and proteomic analysis of a tissue sample. DBiT-seq improves upon previous spatial transcriptomics applications such as High-Definition Spatial Transcriptomics (HDST) and Slide-seq by increasing the number of detectable genes per pixel, increased cellular resolution, and ease of implementation.
The Visible Embryo Project (VEP) is a multi-institutional, multidisciplinary research project originally created in the early 1990s as a collaboration between the Developmental Anatomy Center at the National Museum of Health and Medicine and the Biomedical Visualization Laboratory (BVL) at the University of Illinois at Chicago, "to develop software strategies for the development of distributed biostructural databases using cutting-edge technologies for high-performance computing and communications (HPCC), and to implement these tools in the creation of a large-scale digital archive of multidimensional data on normal and abnormal human development." This project related to BVL's other research in the areas of health informatics, educational multimedia, and biomedical imaging science. Over the following decades, the list of VEP collaborators grew to include over a dozen universities, national laboratories, and companies around the world.
Precision diagnostics is a branch of precision medicine that involves precisely managing a patient's healthcare model and diagnosing specific diseases based on customized omics data analytics.
