Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
Proteomics is the large-scale study of proteins. Proteins are vital macromolecules of all living organisms, with many functions such as the formation of structural fibers of muscle tissue, enzymatic digestion of food, or synthesis and replication of DNA. In addition, other kinds of proteins include antibodies that protect an organism from infection, and hormones that send important signals throughout the body.
Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach to biological research.
The transcriptome is the set of all RNA transcripts, including coding and non-coding, in an individual or a population of cells. The term can also sometimes be used to refer to all RNAs, or just mRNA, depending on the particular experiment. The term transcriptome is a portmanteau of the words transcript and genome; it is associated with the process of transcript production during the biological process of transcription.
Regulome refers to the whole set of regulatory components in a cell. Those components can be regulatory elements, genes, mRNAs, proteins, and metabolites. The description includes the interplay of regulatory effects between these components, and their dependence on variables such as subcellular localization, tissue, developmental stage, and pathological state.
A biochemical cascade, also known as a signaling cascade or signaling pathway, is a series of chemical reactions that occur within a biological cell when initiated by a stimulus. This stimulus, known as a first messenger, acts on a receptor that is transduced to the cell interior through second messengers which amplify the signal and transfer it to effector molecules, causing the cell to respond to the initial stimulus. Most biochemical cascades are series of events, in which one event triggers the next, in a linear fashion. At each step of the signaling cascade, various controlling factors are involved to regulate cellular actions, in order to respond effectively to cues about their changing internal and external environments.
QIAGEN N.V. is a German-founded multinational provider of sample and assay technologies for molecular diagnostics, applied testing, academic research, 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, Chinese, and Asian-Pacific regional headquarters are located respectively in respectively Hilden, Germany; Germantown, Maryland, United States; Shanghai, China; and Singapore. 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).
In the field of molecular biology, gene expression profiling is the measurement of the activity of thousands of genes at once, to create a global picture of cellular function. These profiles can, for example, distinguish between cells that are actively dividing, or show how the cells react to a particular treatment. Many experiments of this sort measure an entire genome simultaneously, that is, every gene present in a particular cell.
Thermo Fisher Scientific Inc. is an American-headquartered life science and clinical research company. It is a global supplier of analytical instruments, clinical development solutions, specialty diagnostics, laboratory, pharmaceutical and biotechnology services. Based in Waltham, Massachusetts, Thermo Fisher was formed through the merger of Thermo Electron and Fisher Scientific in 2006. Thermo Fisher Scientific has acquired other reagent, consumable, instrumentation, and service providers, including Life Technologies Corporation (2013), Alfa Aesar (2015), Affymetrix (2016), FEI Company (2016), BD Advanced Bioprocessing (2018), and PPD (2021).
A reverse phase protein lysate microarray (RPMA) is a protein microarray designed as a dot-blot platform that allows measurement of protein expression levels in a large number of biological samples simultaneously in a quantitative manner when high-quality antibodies are available.
Your Favorite Gene is a dynamic web-based research tool provided by Sigma-Aldrich Corp and powered by Ingenuity Systems' Knowledge Base, a repository of biological and chemical networks that is the largest database of its kind. Biological pathways, metabolic pathways, and gene interaction networks are available. The tool was initially released in 2007.
ArrayTrack is a multi-purpose bioinformatics tool primarily used for microarray data management, analysis, and interpretation. ArrayTrack was developed to support in-house filter array research for the U.S. Food and Drug Administration in 2001, and was made freely available to the public as an integrated research tool for microarrays in 2003. Since then, ArrayTrack has averaged about 5,000 users per year. It is regularly updated by the National Center for Toxicological Research.
Secretomics is a type of proteomics which involves the analysis of the secretome—all the secreted proteins of a cell, tissue or organism. Secreted proteins are involved in a variety of physiological processes, including cell signaling and matrix remodeling, but are also integral to invasion and metastasis of malignant cells. Secretomics has thus been especially important in the discovery of biomarkers for cancer and understanding molecular basis of pathogenesis. The analysis of the insoluble fraction of the secretome has been termed matrisomics.
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 gene expression, sequencing, and proteomics markets. Customers include genomic research centers, pharmaceutical companies, academic institutions, clinical research organizations, and biotechnology companies.
Biomatrica, Inc. is a United States-based biotechnology company, and subsidiary of Exact Sciences Corporation, that develops chemicals for ambient temperature preservation of biological materials for the purpose of expanding the availability and accuracy of medical diagnostics and research. Specifically, the company focuses on improving the stability of biological materials, such as DNA, RNA, proteins, cells from patient samples used in research, and diagnostic testing reagents. Company scientists have developed alternatives to existing preservation technologies, such as cold storage and lyophilization (freeze-drying), to prevent degradation of perishable biological materials. Biomatrica's technologies are used in applications such as pre-analytic sample collection, diagnostic assays, biobanking, forensics, and basic research.
Extracellular RNA (exRNA) describes RNA species present outside of the cells in which they were transcribed. Carried within extracellular vesicles, lipoproteins, and protein complexes, exRNAs are protected from ubiquitous RNA-degrading enzymes. exRNAs may be found in the environment or, in multicellular organisms, within the tissues or biological fluids such as venous blood, saliva, breast milk, urine, semen, menstrual blood, and vaginal fluid. Although their biological function is not fully understood, exRNAs have been proposed to play a role in a variety of biological processes including syntrophy, intercellular communication, and cell regulation. The United States National Institutes of Health (NIH) published in 2012 a set of Requests for Applications (RFAs) for investigating extracellular RNA biology. Funded by the NIH Common Fund, the resulting program was collectively known as the Extracellular RNA Communication Consortium (ERCC). The ERCC was renewed for a second phase in 2019.
Molecular diagnostics is a collection of techniques used to analyze biological markers in the genome and proteome, and how their cells express their genes as proteins, applying molecular biology to medical testing. In medicine the technique is used to diagnose and monitor disease, detect risk, and decide which therapies will work best for individual patients, and in agricultural biosecurity similarly to monitor crop- and livestock disease, estimate risk, and decide what quarantine measures must be taken.
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.
Pathway is the term from molecular biology for a curated schematic representation of a well characterized segment of the molecular physiological machinery, such as a metabolic pathway describing an enzymatic process within a cell or tissue or a signaling pathway model representing a regulatory process that might, in its turn, enable a metabolic or another regulatory process downstream. A typical pathway model starts with an extracellular signaling molecule that activates a specific receptor, thus triggering a chain of molecular interactions. A pathway is most often represented as a relatively small graph with gene, protein, and/or small molecule nodes connected by edges of known functional relations. While a simpler pathway might appear as a chain, complex pathway topologies with loops and alternative routes are much more common. Computational analyses employ special formats of pathway representation. In the simplest form, however, a pathway might be represented as a list of member molecules with order and relations unspecified. Such a representation, generally called Functional Gene Set (FGS), can also refer to other functionally characterised groups such as protein families, Gene Ontology (GO) and Disease Ontology (DO) terms etc. In bioinformatics, methods of pathway analysis might be used to identify key genes/ proteins within a previously known pathway in relation to a particular experiment / pathological condition or building a pathway de novo from proteins that have been identified as key affected elements. By examining changes in e.g. gene expression in a pathway, its biological activity can be explored. However most frequently, pathway analysis refers to a method of initial characterization and interpretation of an experimental condition that was studied with omics tools or genome-wide association study. Such studies might identify long lists of altered genes. A visual inspection is then challenging and the information is hard to summarize, since the altered genes map to a broad range of pathways, processes, and molecular functions. In such situations, the most productive way of exploring the list is to identify enrichment of specific FGSs in it. The general approach of enrichment analyses is to identify FGSs, members of which were most frequently or most strongly altered in the given condition, in comparison to a gene set sampled by chance. In other words, enrichment can map canonical prior knowledge structured in the form of FGSs to the condition represented by altered genes.
Prognostic markers are biomarkers used to measure the progress of a disease in the patient sample. Prognostic markers are useful to stratify the patients into groups, guiding towards precise medicine discovery. The widely used prognostic markers in cancers include stage, size, grade, node and metastasis. In addition to these common markers, there are prognostic markers specific to different cancer types. For example estrogen level, progesterone and HER2 are markers specific to breast cancer patients. There is evidence showing that genes behaving as tumor suppressors or carcinogens could act as prognostic markers due to altered gene expression or mutation. Besides genetic biomarkers, there are also biomarkers that are detected in plasma or body fluid which can be metabolic or protein biomarkers.
