Cheminformatics

Cheminformatics (also known as chemoinformatics and chemical informatics) is the study of large amounts of chemical information. It is done mostly with the help of computers. These tools are used by pharmaceutical companies to discovery new drugs.
Cheminformatics uses computer science and information technology to help solve chemistry problems. Cheminformatics deals with algorithms, databases and information systems, web technologies, artificial intelligence and soft computing, information and computation theory, software engineering, data mining, image processing, modeling and simulation, signal processing, discrete mathematics, control and system theory, circuit theory, and statistics, for generating new knowledge of chemistry.
History
The term chemoinformatics was defined by F.K. Brown in 1998:
Basics
Cheminformatics combines the scientific working fields of chemistry and computer science.
Cheminformatics can also be applied to data analysis for the paper, pulp and dye industries.
Uses
Storage and retrieval
The primary application of cheminformatics is in the storage of information relating to compounds. The efficient search of such stored information includes topics that are dealt with in computer science as data mining and machine learning.
File formats
Computers represent chemical structures in specialized formats such as the XML-based Chemical Markup Language or SMILES. While some formats are suited for visual representations in 2 or 3 dimensions, others are more suited for studying physical interactions, modeling and docking studies.
Virtual libraries
Chemical data can pertain to real or virtual molecules. Virtual compounds may be used to explore chemical space and predict new
compounds with desired properties.
Virtual libraries of classes of compounds (drugs, natural products, diversity-oriented synthetic products) were recently generated using the FOG (fragment optimized growth) algorithm.
Virtual screening
Instead og testing the actual chemicals, virtual screening involves
screening compounds by computer, to identify members likely to possess desired properties such as biological activity against a given target.
Quantitative structure-activity relationship (QSAR)
This is to predict the activity of compounds from their structures. These studies link cheminofrmatics to chemometrics. Chemical expert systems are also relevant. They represent parts of chemical knowledge in computers.
References
Other websites
OEChem Cheminformatics Programming Toolkit
The Blue Obelisk Movement
The eCheminfo Network and Community of Practice
Cheminformatics at Indiana University
Indiana Cheminformatics Education Portal
Cheminformatics at Rensselaer Polytechnic Institute
The Chemical Structure Association Trust (see also CSA Trust).
Comprehensive cheminformatics link list and data set repository
A cheminformatics glossary
Chemoinformatics initiatives at NCL Pune, India
International Conference on Chemoinformatics at NCL,Pune
Chemical Informatics Education and Research at Indiana University
Famous Cheminformatics quotations
The Cheminformatics and QSAR Society
UK-QSAR and ChemoInformatics Group
Education and Research at the University of Hamburg
Cheminformatics research at the Unilever Centre for Molecular Informatics, Cambridge, UK
YACHS Yet Another CHemistry Summarizer, Laboratoire Informatique d'Avignon LIA, France
Cheminformatics research at NovaMechanics Cyprus
Weblink-Cheminformatics SW and DB
Cheminformatics studies from Unilever Centre for Molecular Informatics to OpenEye
Computational chemistry