Introduction - Design and Use of Relational Databases in Chemistry - page 2

and maintain robust and powerful chemical relational databases. And
all four languages begin with S! Finally, you will see how you can use
your familiarity with perl, python, or C to implement new functions in
the database.
Much chemical data is stored in computer files, some of which have
little or no structural organization. Some data files are more structured,
perhaps in tabular form or as an Excel spreadsheet. There are many simi-
larities between spreadsheet files and relational tables in a database.
However, storing data in a relational database offers many advantages
not possible when data is stored in files. The greatest advantage comes
from the proper design and use of tables themselves. Chapter 2 shows
how to design and use tables to store and search numerical or text data.
The reason for using multiple tables is explained and the use of relation-
ships among tables is examined. Finally, the entity-relationship diagram
is shown as an aid to designing and understanding a database of tables.
An introduction to SQL is provided in Chapter 3, but with an emphasis
on examples relevant to chemical information rather than business infor-
mation, which is often used in other topics. Chapter 4 discusses some of
the RDBMS that are available, namely Oracle, MySQL, and PostgreSQL.
All of them use SQL to insert, delete, update, and select data. Chapter 5
shows ways in which client programs, including Web-based applications,
are used to connect to the database server. Chapter 6 examines ways in
which RDBMS are typically used to handle numerical and textual chemi-
cal information using relational tables. An example of using data files
from the PubChem project is included.
Chapter 7 introduces ways in which RDBMS can be used to handle
chemical structural information using SMILES and SMARTS represen-
tations. It shows how extensions to relational databases allow chemical
structural information to be stored and searched efficiently. In this way,
chemical structures themselves can be stored in data columns. Once
chemical structures become proper data types, many search and compu-
tational options become available. Conversion between different chemical
structure formats is also discussed, along with input and output of chemi-
cal structures.
Chapter 8 shows ways in which molecular fragments can be used
to speed up searches for chemical structures. Both path-based and frag-
ment-based methods are discussed. Several types of molecular similarity
are explained using bit-string fingerprints representing the presence or
absence of various fragments. Finally, it is shown how tables of fragments
along with parameter values for these fragments can be used to compute
theoretical molecular properties.