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