Cheminformatics refers to the use of physical chemistry theory with computer and information science techniques—so called "in silico" techniques—in application to a range of descriptive and prescriptive problems in the field of chemistry, including in its applications to biology and related molecular fields. Such in silico techniques are used, for example, by pharmaceutical companies and in academic settings to aid and inform the process of drug discovery, for instance in the design of well-defined combinatorial libraries of synthetic compounds, or to assist in structure-based drug design. The methods can also be used in chemical and allied industries, and such fields as environmental science and pharmacology, where chemical processes are involved or studied.
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.
This page describes mining for molecules. Since molecules may be represented by molecular graphs this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics.
Chemaxon is a cheminformatics and bioinformatics software development company, headquartered in Budapest with 250 employees. The company also has offices in Cambridge, San Diego, Basel and in Prague. and it has distributors in China, India, Japan, South Korea, Singapore, and Australia.
In the fields of computational chemistry and molecular modelling, scoring functions are mathematical functions used to approximately predict the binding affinity between two molecules after they have been docked. Most commonly one of the molecules is a small organic compound such as a drug and the second is the drug's biological target such as a protein receptor. Scoring functions have also been developed to predict the strength of intermolecular interactions between two proteins or between protein and DNA.
Søren Brunak is a Danish biological and physical scientist working in bioinformatics, systems biology, and medical informatics. He is a professor of Disease Systems Biology at the University of Copenhagen and professor of bioinformatics at the Technical University of Denmark. As Research Director at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen Medical School, he leads a research effort where molecular-level systems biology data are combined with phenotypic data from the healthcare sector, such as electronic patient records, registry information, and biobank questionnaires. A major aim is to understand the network biology basis for time-ordered comorbidities and discriminate between treatment-related disease correlations and other comorbidities in disease trajectories. Søren Brunak also holds a position as a Medical Informatics Officer at Rigshospitalet, the Capital Region of Denmark.
Chemical similarity refers to the similarity of chemical elements, molecules or chemical compounds with respect to either structural or functional qualities, i.e. the effect that the chemical compound has on reaction partners in inorganic or biological settings. Biological effects and thus also similarity of effects are usually quantified using the biological activity of a compound. In general terms, function can be related to the chemical activity of compounds.
Jack Y. Yang is an American computer scientist and biophysicist. As of 2011, he is the editor-in-chief of the International Journal of Computational Biology and Drug Design.
Ming-Ming Zhou is an American scientist whose specification is structural and chemical biology, NMR spectroscopy, and drug design. He is the Dr. Harold and Golden Lamport Professor and Chairman of the Department of Pharmacological Sciences. He is also the co-director of the Drug Discovery Institute at the Icahn School of Medicine at Mount Sinai and Mount Sinai Health System in New York City, as well as Professor of Sciences. Zhou is an elected fellow of the American Association for the Advancement of Science.
Druggability is a term used in drug discovery to describe a biological target that is known to or is predicted to bind with high affinity to a drug. Furthermore, by definition, the binding of the drug to a druggable target must alter the function of the target with a therapeutic benefit to the patient. The concept of druggability is most often restricted to small molecules but also has been extended to include biologic medical products such as therapeutic monoclonal antibodies.
Translational bioinformatics (TBI) is a field that emerged in the 2010s to study health informatics, focused on the convergence of molecular bioinformatics, biostatistics, statistical genetics and clinical informatics. Its focus is on applying informatics methodology to the increasing amount of biomedical and genomic data to formulate knowledge and medical tools, which can be utilized by scientists, clinicians, and patients. Furthermore, it involves applying biomedical research to improve human health through the use of computer-based information system. TBI employs data mining and analyzing biomedical informatics in order to generate clinical knowledge for application. Clinical knowledge includes finding similarities in patient populations, interpreting biological information to suggest therapy treatments and predict health outcomes.
In structure mining, a graph kernel is a kernel function that computes an inner product on graphs. Graph kernels can be intuitively understood as functions measuring the similarity of pairs of graphs. They allow kernelized learning algorithms such as support vector machines to work directly on graphs, without having to do feature extraction to transform them to fixed-length, real-valued feature vectors. They find applications in bioinformatics, in chemoinformatics, and in social network analysis.
eTOX is a temporary consortium established in 2010 to share and use toxicology data. It is a pre-competitive collaboration which main goal is to create and distribute tools to predict drug side-effects based on pre-clinical experiments. Aims are a better in silico predictability of potential adverse events and a decrease of the use of animals in toxicological research. eTOX is funded by the Innovative Medicines Initiative (IMI).
Carbohydrate Structure Database (CSDB) is a free curated database and service platform in glycoinformatics, launched in 2005 by a group of Russian scientists from N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences. CSDB stores published structural, taxonomical, bibliographic and NMR-spectroscopic data on natural carbohydrates and carbohydrate-related molecules.
AMDD otherwise known as Antimicrobial Drug Database is a biological database that seeks to consolidate antibacterial and antifungal drug information from a variety of sources such as PubChem, PubChem Bioassay, ZINC, ChemDB and DrugBank in order to advance the field of treatment of resistance microbes. As of 2012, AMDD contains ~2900 antibacterial and ~1200 antifungal compounds. These compounds are organized via their description, target, format, bioassay, molecular weight, hydrogen bond donor, hydrogen bond acceptor and rotatable bond. AMDD was built on Apache server 2.2.11. The function of this database is to ultimately provide a comprehensive tool that is intuitively navigated such that development of novel antibacterial and antifungal compounds are facilitated.
Hanoch Senderowitz is an Israeli chemist specializing in the fields of Computational Chemistry, Molecular modelling, Computer-Aided Drug Design, and Chemoinformatics.
Jason W. Locasale is an American scientist and university professor. His focus is on metabolism.
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.
Yu-Shan Lin is a computational chemist. She is an associate professor of chemistry at Tufts University in the United States. Her research lab uses computational chemistry to understand and design biomolecules, with topics focusing on cyclic peptides, protein folding, and collagen.
The Genealogical Adam and Eve: The Surprising Science of Universal Ancestry is a 2019 book by S. Joshua Swamidass. In this book, Swamidass, a computational biologist and Christian, uses the findings of biology and genealogy to affirm belief in both evolution and a historical Genesis creation narrative.
