bioinformatics databases

A bioinformatics/biological database is a large, organized body of persistent data, usually associated with computerized software designed to update, query, and retrieve components of the data stored within the system. A simple database might be a single file containing many records, each of which includes the same set of information. For example, a record associated with a nucleotide sequence database typically contains information such as contact name; the input sequence with a description of the type of molecule; the scientific name of the source organism from which it was isolated; and, often, literature citations associated with the sequence.

For researchers to benefit from the data stored in a database, two additional requirements must be met:
1.Easy access to the information; and
2.A method for extracting only that information needed to answer a specific biological question.

The principal requirements on the public data services are:

Data quality – data quality has to be of the highest priority. However, because the data services in most cases lack access to supporting data, the quality of the data must remain the primary responsibility of the submitter.
Supporting data – database users will need to examine the primary experimental data, either in the database itself, or by following cross-references back to network-accessible laboratory databases.
Deep annotation – deep, consistent annotation comprising supporting and ancillary information should be attached to each basic data object in the database.
Timeliness - the basic data should be available on an Internet-accessible server within days (or hours) of publication or submission.
Integration - each data object in the database should be cross-referenced to representation of the same or related biological entities in other databases. Data services should provide capabilities for following these links from one database or data service to another.

The Creation of Sequence Databases:
Most biological databases consist of long strings of nucleotides (guanine, adenine, thymine, cytosine and uracil) and/or amino acids (threonine, serine, glycine, etc.). Each sequence of nucleotides or amino acids represents a particular gene or protein (or section thereof), respectively. Sequences are represented in shorthand, using single letter designations. This decreases the space necessary to store information and increases processing speed for analysis.
While most biological databases contain nucleotide and protein sequence information, there are also databases which include taxonomic information such as the structural and biochemical characteristics of organisms. The power and ease of using sequence information has however, made it the method of choice in modern analysis.
In the last three decades, contributions from the fields of biology and chemistry have facilitated an increase in the speed of sequencing genes and proteins. The advent of cloning technology allowed foreign DNA sequences to be easily introduced into bacteria.
In this way, rapid mass production of particular DNA sequences, a necessary prelude to sequence determination, became possible. Oligonucleotide synthesis provided researchers with the ability to construct short fragments of DNA with sequences of their own choosing. These oligonucleotides could then be used in probing vast libraries of DNA to extract genes containing that sequence. Alternatively, these DNA fragments could also be used in polymerase chain reactions to amplify existing DNA sequences or to modify these sequences. With these techniques in place, progress in biological research increased exponentially.

For researchers to benefit from all this information, however, two additional things were required:

1) ready access to the collected pool of sequence information and
2) a way to extract from this pool only those sequences of interest to a given researcher

Simply collecting, by hand, all necessary sequence information of interest to a given project from published journal articles quickly became a formidable task. After collection, the organization and analysis of this data still remained. It could take weeks to months for a researcher to search sequences by hand in order to find related genes or proteins.
Computer technology has provided the obvious solution to this problem. Not only can computers be used to store and organize sequence information into databases, but they can also be used to analyze sequence data rapidly. The evolution of computing power and storage capacity has, so far, been able to outpace the increase in sequence information being created. Theoretical scientists have derived new and sophisticated algorithms which allow sequences to be readily compared using probability theories. These comparisons become the basis for determining gene function, developing phylogenetic relationships and simulating protein models. The physical linking of a vast array of computers in the 1970’s provided a few biologists with ready access to the expanding pool of sequence information. This web of connections, now known as the Internet, has evolved and expanded so that nearly everyone has access to this information and the tools necessary to analyze it. Databases of existing sequencing data can be used to identify homologues of new molecules that have been amplified and sequenced in the lab. The property of sharing a common ancestor, homology, can be a very powerful indicator in bioinformatics.

Acquisition of sequence data:
Bioinformatics tools can be used to obtain sequences of genes or proteins of interest, either from material obtained, labelled, prepared and examined in electric fields by individual researchers/groups or from repositories of sequences from previously investigated material.