Bioinformatics is an emerging discipline of Biotechnology which has now become the heart of modern biological research. The team Bioinformatics, which was coined by Paulien Hogeweg, merges the two major power houses of modern science and technology – Biology and Information Technology (IT). In other words, Bioinformatics is the systematic development and application of IT solutions to handle biological information by addressing biological data collection and warehousing, data mining, database searches, analyzes and interpretation, modeling and product design.
Bioinformatics – a Definition1 (Molecular) bio-informatics: bioinformatics is conceptualising biology in terms of molecules (in the sense of Physical chemistry) and applying “informatics techniques” (derived from disciplines such as applied maths, computer science and statistics) to understand and organise the information associated with these molecules, on a large scale. In short, bioinformatics is a management information system for molecular biology and has many practical applications.
1As submitted to the Oxford English Dictionary.
It involves discovery, development and implementation of computational algorithms and software tools that facilitate an understanding of the biological processes with the goal to serve the humankind. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. Bioinformatics is not just a useful tool in biological research or drug development. It is an indispensable ally of researchers. The technology is versatile and can be applied whenever gene, protein and cell research are used for the discovery of a new drug or a new herbicide/herbicide-resistant crop combination. Drug toxicology, pharmacogenetics and clinical trial studies can also benefit from this technology which can even be used to genetically engineer crops and livestock that have enhanced nutritional qualities and the ability to produce pharmaceuticals. Its application is not only limited to biomedical, pharmaceutical and agriculture but some of its recent application even extends to bio-diversity conservation, biopolymers and even space science.
Aims of Bioinformatics
In general, there are three basic aims of bioinformatics.
- The first aim of bioinformatics is to store the biological data organized in form of a database. This allows the researchers an easy access to existing information and submit new entries. These data must be annoted to give a suitable meaning or to assign its functional characteristics. The databases must also be able to correlate between different hierarchies of information. For example: GenBank for nucleotide and protein sequence information, Protein Data Bank for 3D macromolecular structures, etc.
- The second aim is to develop tools and resources that aid in the analysis of data. For example: BLAST to find out similar nucleotide/amino-acid sequences, ClustalW to align two or more nucleotide/amino-acid sequences, Primer3 to design primers probes for PCR techniques, etc.
- The third and the most important aim of bioinformatics is to exploit these computational tools to analyze the biological data interpret the results in a biologically meaningful manner.
The ultimate goal of bioinformatics is to better understand a living cell and how it functions at molecular level. The fact that the all the cells functions respecting the “Central Dogma” of Molecular Biology in which DNA is transcribed into RNA, which is translated into proteins, makes us possible to analyze the behavior of cell utilizing various levels of information. Cellular functions are mainly performed by proteins which are determined by the nucleotide sequences.
What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g., data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, genome-wide association studies and the modeling of evolution.
Level of Organization in Bioinformatics
Basically there are two sub-fields in bioinformatics:
- Computational Bioinformatics
- Application Bioinformatics
It refers to all the computational work done so as to develop an application that is aimed to address certain problems in biology. Computational Bioinformatics further has the following levels:
Algorithm and Software Development: To solve any problem we first must have a strategy to tackle the problem. For this algorithm of the application is a must. Here people with different expertise work together to develop an algorithm.
For example: A molecular biologist put forward the problems that he wants to get it solve. A bioinformaticist analyzes the problem and suggests the possible way of handling the problem and also bridges the gap between the biologist and computer experts. A computer scientist or a system engineer designs a framework where the application can be built. Then the software engineer and Mathematician/Statistician work together to design algorithm and ultimately cope up with an application. And again the molecular biologist sits in the user end to evaluate if the software fulfills his demands.
Database Construction and Curation: Any information generated in the lab must be stored in a database for easy retrieval in the future. Without database bioinformatics becomes lame. Database is a place where one can store related information which makes the information much more meaningful and help in the future development. There are countless public databases that focus on different levels or types of biological information.
All the applications of bioinformatics are carried out in the user level. Here is the biologist including the students at various level can use certain applications and use the output in their research or in study. Various bioinformatics application can be categorized under following groups:
- Sequence Analysis
- Function Analysis
- Structure Analysis
Sequence Analysis: All the applications that analyzes various types of sequence information and can compare between similar types of information is grouped under Sequence Analysis.
Function Analysis: These applications analyze the function engraved within the sequences and helps predict the functional interaction between various proteins or genes. Also expressional analysis of various genes is a prime topic for research these days.
Structure Analysis: When it comes to the realm of RNA and Proteins, its structure plays a vital role in the interaction with any other thing. This gave birth to a whole new branch termed Structural Bioinformatics with is devoted to predict the structure and possible roles of these structures of Proteins or RNA.