Apache Lucene is a free and open-source search engine software library, originally written in Java by Doug Cutting. It is supported by the Apache Software Foundation and is released under the Apache Software License. Lucene is widely used as a standard foundation for production search applications.
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.
The metabolome refers to the complete set of small-molecule chemicals found within a biological sample. The biological sample can be a cell, a cellular organelle, an organ, a tissue, a tissue extract, a biofluid or an entire organism. The small molecule chemicals found in a given metabolome may include both endogenous metabolites that are naturally produced by an organism as well as exogenous chemicals that are not naturally produced by an organism.
The DrugBank database is a comprehensive, freely accessible, online database containing information on drugs and drug targets created and maintained by the University of Alberta and The Metabolomics Innovation Centre located in Alberta, Canada. As both a bioinformatics and a cheminformatics resource, DrugBank combines detailed drug data with comprehensive drug target information. DrugBank has used content from Wikipedia; Wikipedia also often links to Drugbank, posing potential circular reporting issues.
KEGG is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances. KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.
Chemical Entities of Biological Interest, also known as ChEBI, is a chemical database and ontology of molecular entities focused on 'small' chemical compounds, that is part of the Open Biomedical Ontologies (OBO) effort at the European Bioinformatics Institute (EBI). The term "molecular entity" refers to any "constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity". The molecular entities in question are either products of nature or synthetic products which have potential bioactivity. Molecules directly encoded by the genome, such as nucleic acids, proteins and peptides derived from proteins by proteolytic cleavage, are not as a rule included in ChEBI.
Orciprenaline, also known as metaproterenol, is a bronchodilator used in the treatment of asthma. Orciprenaline is a moderately selective β2 adrenergic receptor agonist that stimulates receptors of the smooth muscle in the lungs, uterus, and vasculature supplying skeletal muscle, with minimal or no effect on α adrenergic receptors. The pharmacologic effects of β adrenergic agonist drugs, such as orciprenaline, are at least in part attributable to stimulation through β adrenergic receptors of intracellular adenylyl cyclase, the enzyme which catalyzes the conversion of ATP to cAMP. Increased cAMP levels are associated with relaxation of bronchial smooth muscle and inhibition of release of mediators of immediate hypersensitivity from many cells, especially from mast cells.
Glycochenodeoxycholic acid is a bile salt formed in the liver from chenodeoxycholic acid and glycine, usually found as the sodium salt. It acts as a detergent to solubilize fats for absorption.
PDBsum is a database that provides an overview of the contents of each 3D macromolecular structure deposited in the Protein Data Bank. The original version of the database was developed around 1995 by Roman Laskowski and collaborators at University College London. As of 2014, PDBsum is maintained by Laskowski and collaborators in the laboratory of Janet Thornton at the European Bioinformatics Institute (EBI).
The Human Metabolome Database (HMDB) is a comprehensive, high-quality, freely accessible, online database of small molecule metabolites found in the human body. It bas been created by the Human Metabolome Project funded by Genome Canada and is one of the first dedicated metabolomics databases. The HMDB facilitates human metabolomics research, including the identification and characterization of human metabolites using NMR spectroscopy, GC-MS spectrometry and LC/MS spectrometry. To aid in this discovery process, the HMDB contains three kinds of data: 1) chemical data, 2) clinical data, and 3) molecular biology/biochemistry data (Fig. 1–3). The chemical data includes 41,514 metabolite structures with detailed descriptions along with nearly 10,000 NMR, GC-MS and LC/MS spectra.
The Small Molecule Pathway Database (SMPDB) is a comprehensive, high-quality, freely accessible, online database containing more than 600 small molecule (i.e. metabolic) pathways found in humans. SMPDB is designed specifically to support pathway elucidation and pathway discovery in metabolomics, transcriptomics, proteomics and systems biology. It is able to do so, in part, by providing colorful, detailed, fully searchable, hyperlinked diagrams of five types of small molecule pathways: 1) general human metabolic pathways; 2) human metabolic disease pathways; 3) human metabolite signaling pathways; 4) drug-action pathways and 5) drug metabolism pathways. SMPDB pathways may be navigated, viewed and zoomed interactively using a Google Maps-like interface. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures (Fig. 1). Each small molecule in SMPDB is hyperlinked to detailed descriptions contained in the HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. Additionally, all SMPDB pathways are accompanied with detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram. Users can browse the SMPDB (Fig. 2) or search its contents by text searching (Fig. 3), sequence searching, or chemical structure searching. More powerful queries are also possible including searching with lists of gene or protein names, drug names, metabolite names, GenBank IDs, Swiss-Prot IDs, Agilent or Affymetrix microarray IDs. These queries will produce lists of matching pathways and highlight the matching molecules on each of the pathway diagrams. Gene, metabolite and protein concentration data can also be visualized through SMPDB's mapping interface.
MetaboAnalyst is a set of online tools for metabolomic data analysis and interpretation, created by members of the Wishart Research Group at the University of Alberta. It was first released in May 2009 and version 2.0 was released in January 2012. MetaboAnalyst provides a variety of analysis methods that have been tailored for metabolomic data. These methods include metabolomic data processing, normalization, multivariate statistical analysis, and data annotation. The current version is focused on biomarker discovery and classification.
5-Androstenedione, also known as androst-5-ene-3,17-dione, is a prohormone of testosterone. The World Anti-Doping Agency prohibits its use in athletes. In the United States, it is a controlled substance.
The Yeast Metabolome Database (YMDB) is a comprehensive, high-quality, freely accessible, online database of small molecule metabolites found in or produced by Saccharomyces cerevisiae. The YMDB was designed to facilitate yeast metabolomics research, specifically in the areas of general fermentation as well as wine, beer and fermented food analysis. YMDB supports the identification and characterization of yeast metabolites using NMR spectroscopy, GC-MS spectrometry and Liquid chromatography–mass spectrometry. The YMDB contains two kinds of data: 1) chemical data and 2) molecular biology/biochemistry data. The chemical data includes 2027 metabolite structures with detailed metabolite descriptions along with nearly 4000 NMR, GC-MS and LC/MS spectra.
Metabolite Set Enrichment Analysis (MSEA) is a method designed to help metabolomics researchers identify and interpret patterns of metabolite concentration changes in a biologically meaningful way. It is conceptually similar to another widely used tool developed for transcriptomics called Gene Set Enrichment Analysis or GSEA. GSEA uses a collection of predefined gene sets to rank the lists of genes obtained from gene chip studies. By using this “prior knowledge” about gene sets researchers are able to readily identify significant and coordinated changes in gene expression data while at the same time gaining some biological context. MSEA does the same thing by using a collection of predefined metabolite pathways and disease states obtained from the Human Metabolome Database. MSEA is offered as a service both through a stand-alone web server and as part of a larger metabolomics analysis suite called MetaboAnalyst.
BacMap is a freely available web-accessible database containing fully annotated, fully zoomable and fully searchable chromosome maps from more than 2500 prokaryotic species. BacMap was originally developed in 2005 to address the challenges of viewing and navigating through the growing numbers of bacterial genomes that were being generated through large-scale sequencing efforts. Since it was first introduced, the number of bacterial genomes in BacMap has grown by more than 15X. Essentially BacMap functions as an on-line visual atlas of microbial genomes. All of the genome annotations in BacMap were generated through the BASys genome annotation system. BASys is a widely used microbial annotation infrastructure that performs comprehensive bioniformatic analyses on raw bacterial genome sequence data. All of the genome (chromosome) maps in BacMap were constructed using the program known as CGView. CGView is a popular visualization program for generating interactive, web-compatible circular chromosome maps. Each chromosome map in BacMap is extensively hyperlinked and each chromosome image can be interactively navigated, expanded and rotated using navigation buttons or hyperlinks. All identified genes in a BacMap chromosome map are colored according to coding directions and when sufficiently zoomed-in, gene labels are visible. Each gene label on a BacMap genome map is also hyperlinked to a 'gene card'. The gene cards provide detailed information about the corresponding DNA and protein sequences. Each genome map in BacMap is searchable via BLAST and a gene name/synonym search.
FooDB is a freely available, open-access database containing chemical composition data on common, unprocessed foods. It also contains extensive data on flavour and aroma constituents, food additives as well as positive and negative health effects associated with food constituents. The database contains information on more than 28,000 chemicals found in more than 1000 raw or unprocessed food products. The data in FooDB was collected from many sources including textbooks, scientific journals, on-line food composition or nutrient databases, flavour and aroma databases and various on-line metabolomic databases. This literature-derived information has been combined with experimentally derived data measured on thousands of compounds from more than 40 very common food products through the Alberta Food Metabolome Project which is led by David S. Wishart. Users are able to browse through the FooDB data by food source, name, descriptors or function. Chemical structures and molecular weights for compounds in FooDB may be searched via a specialized chemical structure search utility. Users are able to view the content of FooDB using two different “Viewing” options: FoodView, which lists foods by their chemical compounds, or ChemView, which lists chemicals by their food sources. Knowledge about the precise chemical composition of foods can be used to guide public health policies, assist food companies with improved food labelling, help dieticians prepare better dietary plans, support nutraceutical companies with their submissions of health claims and guide consumer choices with regard to food purchases.
The E. coli Metabolome Database (ECMDB) is a freely accessible, online database of small molecule metabolites found in or produced by Escherichia coli. Escherichia coli is perhaps the best studied bacterium on earth and has served as the "model microbe" in microbiology research for more than 60 years. The ECMDB is essentially an E. coli "omics" encyclopedia containing detailed data on the genome, proteome and metabolome of E. coli. ECMDB is part of a suite of organism-specific metabolomics databases that includes DrugBank, HMDB, YMDB and SMPDB. As a metabolomics resource, the ECMDB is designed to facilitate research in the area gut/microbiome metabolomics and environmental metabolomics. The ECMDB contains two kinds of data: 1) chemical data and 2) molecular biology and/or biochemical data. The chemical data includes more than 2700 metabolite structures with detailed metabolite descriptions along with nearly 5000 NMR, GC-MS and LC-MS spectra corresponding to these metabolites. The biochemical data includes nearly 1600 protein sequences and more than 3100 biochemical reactions that are linked to these metabolite entries. Each metabolite entry in the ECMDB contains more than 80 data fields with approximately 65% of the information being devoted to chemical data and the other 35% of the information devoted to enzymatic or biochemical data. Many data fields are hyperlinked to other databases. The ECMDB also has a variety of structure and pathway viewing applets. The ECMDB database offers a number of text, sequence, spectral, chemical structure and relational query searches. These are described in more detail below.
David S. Wishart is a Canadian researcher and a Distinguished University Professor in the Department of Biological Sciences and the Department of Computing Science at the University of Alberta. Wishart also holds cross appointments in the Faculty of Pharmacy and Pharmaceutical Sciences and the Department of Laboratory Medicine and Pathology in the Faculty of Medicine and Dentistry. Additionally, Wishart holds a joint appointment in metabolomics at the Pacific Northwest National Laboratory in Richland, Washington. Wishart is well known for his pioneering contributions to the fields of protein NMR spectroscopy, bioinformatics, cheminformatics and metabolomics. In 2011, Wishart founded the Metabolomics Innovation Centre (TMIC), which is Canada's national metabolomics laboratory.
