What is bioinformatics

 INTRODUCTION TO BIOINFORMATICS

Over the past few decades rapid developments in genomics and other molecular research technologies and, advancement in information technologies have combined to produce a tremendous amount of information related to molecular biology. 

Bioinformatics is an evolving, interdisciplinary field of biology. Bioinformatics is the somewhat new and rather unfortunate term that is commonly employed for referring to the use of computers in biological research. 

Bioinformatics is the application of mathematics/statistics and computer to the field of molecular biology. It is the name given to these mathematical and computing approaches used to glean understanding of biological processes.

 The term bioinformatics was coined by Ben Hesper and Paulien Hogeweg in 1978 for the study of informatic methods in biological systems. Its primary use since the late 1980s has been in genetics & genomics, mainly in large-scale DNA sequencing area of genomics. 

Bioinformatics now involves the creation and upgradation of algorithms, databases, statistical and computational theory and techniques to decipher practical problems arising from the collection and investigation of biological data.

 Definition

Generally, bioinformatics describes any use of computers to handle biological information. In practice the bioinformatics to most people is a synonym for “computational molecular biology” –that mean the use of computers to characterize the molecular components of living things.

In simple words bioinformatics is defined as “The statistical (mathematical) and computing methods intend to solve biological problems using molecular biology and related information i.e DNA & protein sequences”or more simply “bioinformatics is a study of biological information pathways.”

 Bioinformatics derives knowledge from computational analysis of biological data. These consist of the information stored in the DNA, but also results from a variety of sources, like experiments, patient stats, and literature in scientific journals. Study in bioinformatics includes method development for data storage, retrieval, analysis and interpretation. Bioinformatics is a rapidly developing field of biology and is highly interdisciplinary, implying concepts and techniques from computer sciences, statistics & mathematical sciences, chemistry, physics, and other branches of biology. It has a lot of practical applications in diverse fields of biology and medicine. 

 Aims of Bioinformatics 

There are three main aims of bioinformatics. 

The first - it is a very organized way of dealing with biological information. Therefore, it is important to develop large scale databases and server repositories for genomes & proteomes. 

The second -it views the processes and mechanisms of life as information processing. For example, it puts a weight on how the regulation can be modeled and generalized as well as how a specific four gene transcription systems works in a bacterium.

The third - it is highly multi-disciplinary that is it needs a very rigid integration of theoretical science, experimental biology and informatics as a one single subject. 

Therefore, a model bioinformaticst should be able to understand what the HMM(Hidden Markov Model), Monte Carlo method, relational database system;object oriented programming language and a Linux operating systems as well as polymerase chain reaction (PCR), transcription elongation factors etc. 

The bioinformatics field as a whole encompasses all the interdisciplinary skills. The ideal way of understanding bioinformatics as an integrated discipline is to look at all the major parts of it.

Divisions of bioinformatics

There are different schemes to divide bioinformatics. 

A. Omics: The various -omics sciences in biology are beneath the umberalla of bioinformatics. They all intend to understand “molecules as networks”. The spirit of such sciences lies in “networks and the interactions of nodes within them”. 

Therefore, proteomics is not just collecting all the information of proteins but also studying their relationships, controls, and emergent properties.The omic sciences includes: 

(1) Genomics (DNA oriented) 

(2) Transcriptomics (RNA oriented)

 (3) Proteomics (protein oriented) 

(4) Systeomics (systematic study) 

(5) Metabolomics (biological pathways oriented) 

(6) Physiomics (disease and physiological level of study) 

(7) Glycomics (study of glycomes)

 (8) Interactomics (study of interactions) 

(9) Medical informatics. 

B. Domains: Large-scale biological data can be represented in different types on the basis of their analysis. The main ones are: 

(1) Sequence 

(2) Structure 

(3) Interaction 

(4) Expression

 (5) Function

 Bioinformatics Applications/Branches of bioinformatics: 

Bioinformatics has a variety of applications in biotechnology, medicine, agriculture etc. Following research fields has bioinformatics as an essential part :- 

1. Genomics: “Genomics is any effort to investigate the entire genetic material or makeup of a species” (singleor plural). 

2. Proteomics: “Proteomics is the study of proteins their position, structure & function”. It is the identification, characterization of all proteins involved in a particular pathway, organelle, cell, tissue, organ or organism. Proteomics, now include not only all the proteins, but also the set of all protein isoforms & modifications, the interactions between them, the structural details and their complexes, simply approximately everything „post-genomic‟.

 3. Computational Biology: “The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems”. 

4. Pharmacogenomics: Pharmacogenomics is the application of genomic approaches & techniques to the identification of drug targets. In Short, pharmacogenomics is using genetic information to predict whether a drug will help make a patient well or sick. It Studies how genes influence the response of humans to drugs, from the population to the molecular level. 

5. Pharmacogenetics: Pharmacogenetics is the “study of how the actions of and reactions to drugs vary with the patient‟s genes”. All individuals respond differently to drug treatments; some positively, others with little obvious change in their conditions and yet others with side effects or allergic reactions. Much of this variation is known to have a genetic basis.

 Pharmacogenetics is a subset of pharmacogenomics which uses genomic/bioinformatic methods to identify genomic correlates, for example SNPs (Single Nucleotide Polymorphisms), characteristic of particular patient response profiles and use those markers to inform the administration and development of therapies. Strikingly such approaches have been used to “resurrect” drugs thought previously to be ineffective, but subsequently found to work with in subset of patients or in optimizing the doses of chemotherapy for particular patients. 

6. Cheminformatics: “The mixing of information technology and information management to transform data into information and information into knowledge for the intended purpose of making better decisions faster in the arena of drug lead identification and optimization”. Other terms for cheminformatics are chemi-informatics, chemometrics, computationalc hemistry, chemical informatics, chemical information management or science, and cheminformatics. But we can distinguish chemoinformatics and chemical informatics as follows: 

A. Chemical informatics: “Computer-assisted storage, retrieval and analysis of chemical information, from data to chemical knowledge”. This definition is different from „Chemo-informatics‟ (synonymous chem-informatics & chemi-informatics) which center on drug design.

B. Chemometrics: “Application of statistics to the analysis of chemical data (from organic, analytical or medicinal chemistry) and design of chemical experiments & simulations”. 

7. Computational Chemistry: A discipline using mathematical techniques for the calculation of molecular properties or for the simulation of molecular behavior. It also includes, database searching, synthesis planning, manipulation of combinatorial library etc. 

8. Structural Bioinformatics: also called Structural Genomics is the analysis of macromolecular structure mainly proteins, using computational tools & theoretical frameworks. One of the aims of structural bioinformatics is the extension of idea of genomics, to obtain accurate 3-D structural models for all known, protein domains /folds and protein families. Structural alignment is a tool of structural genomics. 

9. Comparative Genomics: “The study of human genetics by comparisons with model organisms” such as E. coli, fruit fly, and mice. 

10. Biophysics: The British Biophysical Society defines biophysics as: “an interdisciplinary field which applies techniques from the physical sciences to understanding biological structure and function”. 

11. Medical Informatics or Biomedical Informatics: Medical Informatics is an upcoming discipline that has been defined as “the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information”. 

12. Mathematical Biology: Mathematical biology also attempts to splve biological problems, but the methods it applies to undertake problems need not be numerical and need not to be implemented in computers. It comprises obsessions of theory which are not essentially algorithmic, not essentially molecular, and are not essentially useful in interpreting of data. 

13. Computational Chemistry: Computational chemistry is the feild of theoretical chemistry whose main aims are to develop competent computer programs that calculate the properties of molecules such as energy, dipole moment, vibrational frequencies and to apply these programs to concrete chemical objects. It is used to cover the areas of overlap between chemistry & computer science. 

14. Functional Genomics: “Functional genomics is a field of molecular biology that is attempting to make use of the vast wealth of data produced by genome sequencing projects to describe genome function”. Functional genomics uses high-throuput techniques to describe the function & interactions of genes like DNA microarrays, proteomics, metabolomics and mutation analysis etc.

15. Pharmacoinformatics: Pharmacoinformatics focuses on the aspects of bioinformatics dealing with drug discovery. 

16. Agricultural Informatics: also known as Agro-informatics focuses on the aspects of bioinformatics dealing with plant genomes. 

17. Systems Biology: Systems biology is the “coordinated study of biological systems by investigating the components of cellular networks and their interactions, by applying experimental high-throughput and whole-genome techniques, and integrating computational methods with experimental efforts”. 

18. Bio-programming: Bio-programming identifies and accumulates the technical and biological criteria which are employd to define the physical plan of the facility. The output is the Bio-programme, “a document which contains statements of the concept and objectives, the design criteria, a biological and operational plan, and relevant schedules. It can also contain illustrations which enhance or clarify statements”. Currently used bio-programs are “BioPerl, BioPython, BioJava, and BioLinux”. 

19. Drug Design & Development: molecular modeling is the approach of “finding drugs by design, based on their biological targets”. Normally a drug target is a “key molecule involved in a particular metabolic or signalling pathway that is specific to a disease condition or pathology or to the infectivity or survival of a microbial pathogen”. This branch is related with Chemo-informatics.