Definitions of Fields Related to Bioinformatics
Bioinformatics is an interdisciplinary field that develops and improves on
methods for storing, retrieving, organizing and analyzing biological data. A
major activity in bioinformatics is to develop software tools to generate useful
biological knowledge. Bioinformatics has become an important part of many
areas of biology.
Bioinformatics uses many areas of computer science, mathematics and
engineering to process biological data. Complex machines are used to read in
biological data at a much faster rate than before. Databases and information
systems are used to store and organize biological data. Analyzing biological
data may involve algorithms in artificial intelligence, soft computing, data
mining, image processing, and simulation.
At the beginning of the "genomic revolution", the term bioinformatics
was re-discovered to refer to the creation and maintenance of a database to store
biological information such as nucleotide sequences and amino acid sequences.
Development of this type of database involved not only design issues but the
development of complex interfaces whereby researchers could access existing
data as well as submit new or revised data.
Definitions:
 The application of computer technology to the management of biological
information. Specifically, it is the science of developing computer
databases and algorithms to facilitate and expedite biological research,
particularly in genomics.
 The science of using computers, databases, and math to organize and
analyze large amounts of biological, medical, and health information.
Information may come from many sources, including patient statistics,
tissue specimens, genetics research, and clinical trials.
 The generation/creation, collection, storage (in databases), and efficient
use of data/information from genomics from biological research to
accomplish an objective (for example, to discover a new pharmaceutical
or a new herbicide).
 Research, development, or application of computational tools and
approaches for expanding the use of biological, medical, behavioral or
health data, including those to acquire, store, organize, archive, analyze,
or visualize such data. Bioinformatics is closely related to computational
biology.
 In experimental molecular biology, bioinformatics techniques such as
image and signal processing allow extraction of useful results from large
amounts of raw data.
 In the field of genetics and genomics, it aids in sequencing and
annotating genomes and their observed mutations. It plays a role in the
textual mining of biological literature and the development of biological
and gene ontologies to organize and query biological data. It plays a role
in the analysis of gene and protein expression and regulation.
Bioinformatics tools aid in the comparison of genetic and genomic data
and more generally in the understanding of evolutionary aspects of
molecular biology. At a more integrative level, it helps analyze and
catalogue the biological pathways and networks that are an important part
of systems biology.
 In structural biology, it aids in the simulation and modeling of DNA,
RNA, and protein structures as well as molecular interactions.
Fields Related to Bioinformatics
Genomics:
The branch of molecular biology concerned with the structure, function,
evolution, and mapping of genomes. It involves the ordering of genes in a
haploid set of chromosomes of a particular organism; the full DNA sequence of
an organism; "the human genome contains approximately three billion chemical
base pairs"
Proteomics:
The branch of genetics that studies the full set of proteins encoded by a
genome. It is the large-scale study of proteins, particularly their structures and
functions. Proteins are vital parts of living organisms, as they are the main
components of the physiological metabolic pathways of cells. The term
proteomics was first coined in 1997 to make an analogy with genomics, the
study of the genes. The word proteome is a blend of protein and genome, and
was coined by Marc Wilkins in 1994 while working on the concept as a PhD
student. The proteome is the entire complement of proteins, including the
modifications made to a particular set of proteins, produced by an organism or
system. This will vary with time and distinct requirements, or stresses, that a
cell or organism undergoes. Proteomics is an interdisciplinary formed on the
basis of the research and development of the Human Genome Project, is also an
emerging scientific research and exploration of the proteome research from the
overall level of intracellular protein composition, structure, and its own unique
activity patterns. It is an important component of functional genomics. It is
more complicated than genomics because an organism's genome is more or less
constant, whereas the proteome differs from cell to cell and from time to time.
Pharmacogenomics:
 The study of the interaction of an individual's genetic makeup and
response to a drug.
 The identification and study of genes and their corresponding products
that influence individual variation in the efficacy and toxicity of
therapeutic products, and the application of genomic information to help
inform therapeutic product development and clinical application.
 Pharmacogenomics extends the study of pharmacology to modern
genetics. Knowing the full genetic complement of the human genome, the
development and testing of drugs can be assessed at a global molecular
level and can also take into account genetic differences between
individuals, e.g., can assess the drug efficacy one patient at a time. Basing
pharmacology on genomics thus will eventually allow to match drugs
with patients that actually respond well to them, and avoid giving
medication to patients that do not respond at all or have side effects.
 The field of science that studies how genetic inheritance affects the way
that the body responds to medications.
 The science that examines the inherited variations in genes that dictate
drug response and explores the ways these variations can be used to
predict whether a patient will have a good response to a drug, a bad
response to a drug, or no response at all.
Pharmacogenetics:
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.
Cheminformatics:
The Web advertisement for Cambridge Healthtech Institute's Sixth
Annual Cheminformatics conference describes the field thus: "the combination
of chemical synthesis, biological screening, and data-mining approaches used
toguide drug discovery and development" but this, again, sounds more like a
field being identified by some of its most popular (and lucrative) activities,
rather than by including all the diverse studies that come under its general
heading.
The story of one of the most successful drugs of all time, penicillin,
seems bizarre, but the way we discover and develop drugs even now has
similarities, being the result of chance, observation and a lot of slow, intensive
chemistry. Until recently, drug design always seemed doomed to continue to be
a labour-intensive, trial-and-error process. The possibility of using information
technology, to planintelligently and to automate processes related to the
chemical synthesis of possible therapeutic compounds is very exciting for
chemists and biochemists. The rewards for bringing a drug tomarket more
rapidly are huge, so naturally this is what a lot of cheminformatics works is
about. The span of academic cheminformatics is wide and is exemplified by the
interests of the cheminformatics groups at the Centre for Molecular and
Biomolecular Informatics at the University of Nijmegen in the Netherlands.
These interests include: · Synthesis Planning · Reaction and Structure Retrieval
· 3-D Structure Retrieval · Modelling · Computational Chemistry· Visualisation
Tools and Utilities
Medical Informatics:
"Biomedical Informatics is an emerging discipline that has been defined
as the study, invention, and implementation of structuresand algorithms to
improve communication, understanding and management of medical
information." Medical informatics is more concerned with structures and
algorithms for the manipulation of medical data, rather than with the data itself.
This suggests that one difference between bioinformatics and medical
informatics as disciplines lies with their approaches to the data; there are
bioinformaticists interested in the theory behind the manipulation of that data
and there are bioinformatics scientists concerned with the data itself and its
biological implications. Medical informatics, for practical reasons, is more
likely to deal withdata obtained at "grosser" biological levels---that is
information from super-cellular systems, right up to the population level-while
most bioinformatics is concerned with information about cellular and
biomolecular structures and systems.