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Dive into the research topics where Craig Knox is active.

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Featured researches published by Craig Knox.


Nucleic Acids Research | 2006

DrugBank: a comprehensive resource for in silico drug discovery and exploration

David S. Wishart; Craig Knox; An Chi Guo; Savita Shrivastava; Murtaza Hassanali; Paul Stothard; Zhan Chang; Jennifer Woolsey

DrugBank is a unique bioinformatics/cheminformatics resource that combines detailed drug (i.e. chemical) data with comprehensive drug target (i.e. protein) information. The database contains >4100 drug entries including >800 FDA approved small molecule and biotech drugs as well as >3200 experimental drugs. Additionally, >14,000 protein or drug target sequences are linked to these drug entries. Each DrugCard entry contains >80 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data. Many data fields are hyperlinked to other databases (KEGG, PubChem, ChEBI, PDB, Swiss-Prot and GenBank) and a variety of structure viewing applets. The database is fully searchable supporting extensive text, sequence, chemical structure and relational query searches. Potential applications of DrugBank include in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. DrugBank is available at http://redpoll.pharmacy.ualberta.ca/drugbank/.


Nucleic Acids Research | 2012

HMDB 3.0—The Human Metabolome Database in 2013

David S. Wishart; Timothy Jewison; Anchi Guo; Michael Wilson; Craig Knox; Yifeng Liu; Yannick Djoumbou; Rupasri Mandal; Farid Aziat; Edison Dong; Souhaila Bouatra; Igor Sinelnikov; David Arndt; Jianguo Xia; Philip Liu; Faizath S. Yallou; Trent C. Bjorndahl; Rolando Perez-Pineiro; Roman Eisner; Felicity Allen; Vanessa Neveu; Russell Greiner; Augustin Scalbert

The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both ‘detected’ metabolites (those with measured concentrations or experimental confirmation of their existence) and ‘expected’ metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).


Nucleic Acids Research | 2007

HMDB: the Human Metabolome Database

David S. Wishart; Dan Tzur; Craig Knox; Roman Eisner; An Chi Guo; Nelson Young; Dean Cheng; Kevin Jewell; David Arndt; Summit Sawhney; Chris Fung; Lisa Nikolai; Michael J. Lewis; Marie-Aude Coutouly; Ian D. Forsythe; Peter Tang; Savita Shrivastava; Kevin Jeroncic; Paul Stothard; Godwin Amegbey; David Block; David Hau; James Wagner; Jessica Miniaci; Melisa Clements; Mulu Gebremedhin; Natalie Guo; Ying Wen Zhang; Gavin E. Duggan; Glen D. MacInnis

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at:


Nucleic Acids Research | 2008

DrugBank: a knowledgebase for drugs, drug actions and drug targets

David S. Wishart; Craig Knox; An Chi Guo; Dean Cheng; Savita Shrivastava; Dan Tzur; Bijaya Gautam; Murtaza Hassanali

DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With ∼4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more ‘experimental’ drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food–drug interactions, drug–drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca


Nucleic Acids Research | 2011

DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs

Craig Knox; Vivian Law; Timothy Jewison; Philip Liu; Son Ly; Alex Frolkis; Allison Pon; Kelly Banco; Christine Mak; Vanessa Neveu; Yannick Djoumbou; Roman Eisner; An Chi Guo; David S. Wishart

DrugBank (http://www.drugbank.ca) is a richly annotated database of drug and drug target information. It contains extensive data on the nomenclature, ontology, chemistry, structure, function, action, pharmacology, pharmacokinetics, metabolism and pharmaceutical properties of both small molecule and large molecule (biotech) drugs. It also contains comprehensive information on the target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, DrugBank has become widely used by pharmacists, medicinal chemists, pharmaceutical researchers, clinicians, educators and the general public. Since its last update in 2008, DrugBank has been greatly expanded through the addition of new drugs, new targets and the inclusion of more than 40 new data fields per drug entry (a 40% increase in data ‘depth’). These data field additions include illustrated drug-action pathways, drug transporter data, drug metabolite data, pharmacogenomic data, adverse drug response data, ADMET data, pharmacokinetic data, computed property data and chemical classification data. DrugBank 3.0 also offers expanded database links, improved search tools for drug–drug and food–drug interaction, new resources for querying and viewing drug pathways and hundreds of new drug entries with detailed patent, pricing and manufacturer data. These additions have been complemented by enhancements to the quality and quantity of existing data, particularly with regard to drug target, drug description and drug action data. DrugBank 3.0 represents the result of 2 years of manual annotation work aimed at making the database much more useful for a wide range of ‘omics’ (i.e. pharmacogenomic, pharmacoproteomic, pharmacometabolomic and even pharmacoeconomic) applications.


Nucleic Acids Research | 2009

HMDB: a knowledgebase for the human metabolome

David S. Wishart; Craig Knox; Anchi Guo; Roman Eisner; Nelson Young; Bijaya Gautam; David Hau; Nick Psychogios; Edison Dong; Souhaila Bouatra; Rupasri Mandal; Igor Sinelnikov; Jianguo Xia; Leslie Jia; Joseph A. Cruz; Emilia Lim; Constance A. Sobsey; Savita Shrivastava; Paul Huang; Philip Liu; Lydia Fang; Jun Peng; Ryan Fradette; Dean Cheng; Dan Tzur; Melisa Clements; Avalyn Lewis; Andrea De Souza; Azaret Zuniga; Margot Dawe

The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.


Nucleic Acids Research | 2014

DrugBank 4.0: shedding new light on drug metabolism

Vivian Law; Craig Knox; Yannick Djoumbou; Timothy Jewison; Anchi Guo; Yifeng Liu; Adam Maciejewski; David Arndt; Michael Wilson; Vanessa Neveu; Alexandra Tang; Geraldine Gabriel; Carol Ly; Sakina Adamjee; Zerihun T. Dame; Beomsoo Han; You Zhou; David S. Wishart

DrugBank (http://www.drugbank.ca) is a comprehensive online database containing extensive biochemical and pharmacological information about drugs, their mechanisms and their targets. Since it was first described in 2006, DrugBank has rapidly evolved, both in response to user requests and in response to changing trends in drug research and development. Previous versions of DrugBank have been widely used to facilitate drug and in silico drug target discovery. The latest update, DrugBank 4.0, has been further expanded to contain data on drug metabolism, absorption, distribution, metabolism, excretion and toxicity (ADMET) and other kinds of quantitative structure activity relationships (QSAR) information. These enhancements are intended to facilitate research in xenobiotic metabolism (both prediction and characterization), pharmacokinetics, pharmacodynamics and drug design/discovery. For this release, >1200 drug metabolites (including their structures, names, activity, abundance and other detailed data) have been added along with >1300 drug metabolism reactions (including metabolizing enzymes and reaction types) and dozens of drug metabolism pathways. Another 30 predicted or measured ADMET parameters have been added to each DrugCard, bringing the average number of quantitative ADMET values for Food and Drug Administration-approved drugs close to 40. Referential nuclear magnetic resonance and MS spectra have been added for almost 400 drugs as well as spectral and mass matching tools to facilitate compound identification. This expanded collection of drug information is complemented by a number of new or improved search tools, including one that provides a simple analyses of drug–target, –enzyme and –transporter associations to provide insight on drug–drug interactions.


PLOS ONE | 2011

The Human Serum Metabolome

Nikolaos Psychogios; David Hau; Jun Peng; An Chi Guo; Rupasri Mandal; Souhaila Bouatra; Igor Sinelnikov; Ramanarayan Krishnamurthy; Roman Eisner; Bijaya Gautam; Nelson Young; Jianguo Xia; Craig Knox; Edison Dong; Paul Huang; Zsuzsanna Hollander; Theresa L. Pedersen; Steven R. Smith; Fiona Bamforth; Russell Greiner; Bruce M. McManus; John W. Newman; Theodore L. Goodfriend; David S. Wishart

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with todays technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.


Database | 2010

Phenol-Explorer: an online comprehensive database on polyphenol contents in foods

V. Neveu; Jara Pérez-Jiménez; F. Vos; V. Crespy; L. du Chaffaut; L. Mennen; Craig Knox; Roman Eisner; Joseph A. Cruz; David S. Wishart; Augustin Scalbert

A number of databases on the plant metabolome describe the chemistry and biosynthesis of plant chemicals. However, no such database is specifically focused on foods and more precisely on polyphenols, one of the major classes of phytochemicals. As antoxidants, polyphenols influence human health and may play a role in the prevention of a number of chronic diseases such as cardiovascular diseases, some cancers or type 2 diabetes. To determine polyphenol intake in populations and study their association with health, it is essential to have detailed information on their content in foods. However this information is not easily collected due to the variety of their chemical structures and the variability of their content in a given food. Phenol-Explorer is the first comprehensive web-based database on polyphenol content in foods. It contains more than 37 000 original data points collected from 638 scientific articles published in peer-reviewed journals. The quality of these data has been evaluated before they were aggregated to produce final representative mean content values for 502 polyphenols in 452 foods. The web interface allows making various queries on the aggregated data to identify foods containing a given polyphenol or polyphenols present in a given food. For each mean content value, it is possible to trace all original content values and their literature sources. Phenol-Explorer is a major step forward in the development of databases on food constituents and the food metabolome. It should help researchers to better understand the role of phytochemicals in the technical and nutritional quality of food, and food manufacturers to develop tailor-made healthy foods. Database URL: http://www.phenol-explorer.eu


PLOS ONE | 2013

The Human Urine Metabolome

Souhaila Bouatra; Farid Aziat; Rupasri Mandal; An Chi Guo; Michael Wilson; Craig Knox; Trent C. Bjorndahl; Ramanarayan Krishnamurthy; Fozia Saleem; Philip Liu; Zerihun T. Dame; Jenna Poelzer; Jessica Huynh; Faizath Yallou; Nick Psychogios; Edison Dong; Ralf Bogumil; Cornelia Roehring; David S. Wishart

Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

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