Data Mining-Basics of Bioinformatics
Transcriptomics: Open Access

Transcriptomics: Open Access
Open Access

ISSN: 2329-8936

Mini Review - (2018) Volume 6, Issue 1

Data Mining-Basics of Bioinformatics

Nida Tabassum Khan*
Department of Biotechnology, Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, Pakistan
*Corresponding Author: Nida Tabassum Khan, Department of Biotechnology, Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, Pakistan, Tel: +92 81 111 717 11 Email:


The world is advancing and developing with the ticking seconds. New technologies, inventions and discoveries have remarkably changed the world as it was before, making lives a lot simpler and easier. From the hunter of gathers society till the scientific society today, many new fields have emerged to combat diseases, make earth a substantially friendly place to live in and fore mostly, making changes for the welfare of mankind. One of such newly developing field is ‘Bioinformatics ‘which is the use of computers and its software’s for acquisition, management and analysis of biological information.

Keywords: Relational database; NoSQL database; Graph database; Flat file database


With the advancing discoveries, immense biological data has been generated which needs to be stored. Hence, bioinformatics uses various computational tools to study and analyze the information of biological systems, starting at molecular level. Bioinformatics can be defined as a multi-disciplinary field that incorporates the elements of computer management, database computing, database designing, computer programming, internet networking and molecular biology [1,2]. Bioinformatics can be broadly defined “as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems” [3].

Bioinformatics is found to be useful for the following purposes:

• Increasingly biological research relies on information science and hence is managed by computational bioinformatics tools of effective data analysis.

• It has enhanced understanding about the genome structure.

• It has been able to provide storing and sequencing data on databases

• The biological databases have made the complex research work easier.

Now it is used practically in many sub disciplines. Similarly database and knowledge management is also one of the applications of Bioinformatics [4-8].

Databases and knowledge management

This is a very diverse discipline that focuses on several databases and its uses along with the management of the knowledge it provides. The tools used in databases provide us with information in form of knowledge [9] (Figure 1).


Figure 1: Management of the knowledge.

It basically is a combination of two units:

Databases: Databases are basically a computerized collection of data for information retrieval which is shared by many users [10].

Evolution and explanation: The data is processed, organized and stored in databases where it is updated and expanded so that it can be run against applications. It is managed by a computer program, the Database Management System (DBMS). It is a software package that allows the computer to perform database function including storing, modifying and manipulating data [11]. Its history can be stretched back to early 1960’s when Charles Bachman created first general Database followed by the introduction of Information Management System (IMS) in 1970 by Codd [12,13] and later in 1980’s the relational databases [14]. Today onwards 1990 new data models are used like SQL (Structured query language) databases or cloud databases etc. [15].

Types of databases

Relational database: It is a tabular database in which the data is defined in discrete rows and columns (Table 1) [16].

Types of Databases Examples Knowledge
Nucleotide acid sequences databases (DNA and RNA) Gen bank DNA and RNA information [24]
Protein databases PSD- Atlas of protein sequences and structures It provides protein sequence analysis along with protein structure and classification prediction [25]  
Bibliographic databases ProClass Provides literature [26]
Taxonomic databases NCBI Gives classification and hierarchical information[27]
ZooBase- taxonomic databases
Genomic databases NCBI Gives information at gene level[28]
SNP database dbSNP (Single nucleotide polymorphism Database) Tells about small scale variations in a gene (insertions or deletions etc.[29]
Phylogenetic  databases RDP(Ribosomal Database Project) Tells about the ancestor to descendant relationship (i.e. evolutionary relationship) and included phylogenetic ally ordered alignments [30]
Metabolic pathway and enzyme database KEGG Provides the information of metabolic pathways and enzymes [31]

Table 1: Types of databases.

Distributed database: It is a database in which the data is distributes in many sites [17].

Cloud database: These are the data bases that are accessible on clouds whose primarily function are for online data management [18].

NoSQL database: Non-relational databases [19].

Object oriented database: This is a database that models and create data as objects [20].

Graph database: This provides and arranged data into graphs without the use of rows and columns [21].

Flat file database: This stores database as plain text file and are ideal for small data [22].

Biological databases: This provides information related to genes, nucleic acid, metabolic pathways etc. [23].

Knowledge management: it is the collection of processes that govern the creation, dissemination and utilization of knowledge [24-32].

History and Explanation

Many theorists have contributed to the evaluation of knowledge management including Peter Drucker and Peter Senge [33]. The idea was brought up in the beginning of 1970s and further developed with the publications of knowledge management related articles in 1980’s [34]. Until now a number of knowledge management firms exist. The knowledge management is the discipline that enables individual, teams or organizations to create and share knowledge collectively so that they can obtain their desired objectives. For instance, research work or case studies that use different tool to produce their collaborated information. For Example Dr. Bob Goldszer; a physician benefits from the knowledge based system by getting any patients tests run against clinical databases to get knowledge of their medical records which can also be compared to others [35,36].

Future Perspectives

Bioinformatics holds great potential in the future by assisting a number of field such as comparative genomics, proteomics, drug discovery, biodenses, microbial genome, system biology, molecular modelling, phylogenetics etc. [37]. It helps in storing the valuable data and provides numerous tools and software packages for manipulation of this data for scientific purpose [38].


Bioinformatics is a new emerging field which uses various computational tools to manipulate and handle biological data. The information tools are very much useful in various disciplines and spheres of life sciences including database and knowledge management.


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Citation: Khan NT (2018) Data Mining – Basics of Bioinformatics. Transcriptomics 6: 142.

Copyright: © 2018 Khan NT. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.