Bioinformatics is a meeting point of two key comtemporary
displines - Biology and computer science. It has had a
pivotal role high throughput projects such the human genome project.
Bioinformatics is the computer assisted data management discipline that helps
us gather, analyze, and represent this information in order to edify ourselves,
knowing the life’s progression in the healthy and disease conditions, and find
novel or better drugs. Bioinformatics is being practiced across the globe by
educational groups, companies, national and international research
organizations. This discipline should be thought of as core of current and
future biotechnology. The demands and opportunities for interpreting these data
are expanding more than ever. Bioinformatics is a discipline which uses
computational techniques to analyze the biological problems; the science of
developing and utilizing computer databases and algorithms to accelerate and
enhance biological research. It’s commonly referred as dry lab work which accelerates
the wet lab work drastically. Bioinformatics is a tool to solve the Biological
problems based on existing data. It is a mode to solve the Biological outcomes
based on existing experimental results. It creates the way for the biologists
to store all the data. It makes some lab experiments easy by predicting the
outcome of the lab. Experiment from exiting results. It helps the researchers
to get an idea about any lab experiments before they start. Computer have
become an essential component of modern biology.
Bioinformatics has established itself in just a few years as a
foundation of modern biotechnology, its focus on biology information management
independent of origin or representation is enabling life science and novel drug
discovery to progress much faster. Still, there are significant issues that
challenge the industry. Integration of data acquisition, storage, manipulation,
analysis and dissemination in a cross-platform manner, un ambiguous gene
sequence assignment, and development and application of new, language and
ontology based approaches are all of the leading edge of the field, with many
companies and other Institutions advancing these areas. The Ultimate prize is
the computer aided empowerment of researchers to work seamlessly with multiple
types of biological information, as close to real time as possible. Once all
this is achieved at multiple levels, including genes, proteins, cells, tissues,
diseases, population variations, plants, animals and other organisms, then the promise
will have been fulfilled.
Career Path
Today’s
bioinformaticists are in for a real treat with a seemingly endless stream of
biological data being generated across sectors, there is high demand for
talented, experimented professionals at the crossroad of biology, statistics,
and computer science scientists who can analyze large amounts of information
and present it in a clear manner to decision maker are finding the sky is the
limit in terms of jobs and career pathways, especially in the big pharma and
bio tech sectors.
For
life scientists with expertise and an interest in bioinformatics computer
science, statistics, and related skill sets, the job outlook couldn’t be
rosier. Big pharma, biotech, and software companies are clamoring to here professionals with experience in
bioinformatics and identification, compilation, analysis, and visualization of
huge amounts of biological and health care information with the rapid
development of new tools to make sense of life science research and out comes,
spurred by innovative research in Bioinformatics itself, scientists who are
entranced by data can pursue more career options than ever before.
When
people refer to the field of bioinformatics, they’re referring to what might be
argued as two overlapping areas. The first is what you would call
‘’bioinformatics’’ which is more technical, and examples are creating tools to
analyze data for biologists, or specific databases to store and retrieve
information. For example if you created a new tool that could analyse
sequencing in a way that hasn’t been done previously, then this is
bioinformatics. Many journals such as Nature and Bioinformatics have sections
purely for articles about new methods and tools.
The second path is what you might call
``computational biology ‘’ which is all about doing biological research, using
a computer instead of a pipette. A strong understanding of biology is
important, as well as the ability to praise, then answer a research question.
For example, If you believed that duplicate genes were less well coserved
compared with non-duplicates, and you tested this hypothesis across a set of
genomes, then this would be computational biology.
These
two field are not distinct, and over lap a fair amount. Some universities have
bioinformartics departments in both the computer science and life science
facilities, indicating the types of reasearch carried out in each.
Bioinformatics specialists must acquire an unusual background, an
ecletic blend of molecular biology, chemistry, and computer science. They work
in close collaboration with bench scientists, helping them to plan and organise
experiments and data collection so as to maximise the production of reliable
and useful information. They are found in academic, Government, and Industrial
research labs.
There is no suchthing as a typical career path in this field.
Bioinformaticians need to perform two critical roles. Develop IT tools embodying
novel algorithms and analytical techniques, and apply existing tools to achieve
new insights into molecular biology. However, you must remember that although
powerful and highly specialised in
itself, bioinformatics is only a part of biotechnology.
Specific areas that fall within the scope of bioinformatics.
Sequence assembly
The
genome of an organism is assembled from thousands of fragments that must be
correctly ``stitched’’ together sophisticated computer-based methods, is
carried out by a specialist in bioinformatics.
Database design and maintenance:
Many pharmaceutical companies maintain private databanks of gene
sequence and other biological and chemical information. These repositories must
be continually updated with data generated intermally and from outside sources.
This is a challenging task, and the design and maintenance of these complex
databases has become an important part of bioinformatics.
Sequence (gene) analysis
Once the DNA sequence of a fragment of the
genome has been determined, the work just began; one must next understand the
function of the gene. This involves locating regions of the gene that code for
a protein product that is involved in regulation and control and also finding
those sections of the gene (introns) that are clipped out and discarded. The
gene may be compared against databases of known genes with well understood
functions to find clues to its role in health or disease. All of these analyses
are carried out using powerful computers and specialized software, and many
would consider this activity the most important area of focus within
bioinformatics.
Pharmacogenomics:
It is
now realized that single-point mutations (alterations in the genome at specific
positions) can be associated not only with particular disease states(for
example, sickle cell anemia ) but also with reduced or increase sensitivity to
particular drugs or with side-effects to those single necleotide polymorphisms
(SNP) are rapidly evolving and promise to play an important role in future drug
development efforts and in the design of clinical trials. Again, experts in
bioinformatics are at the forefront of efforts to collect, analyse, and apply
this crucial data.
Proteomics:
A
relatively new area proteomics studies not the entire genome but rather is
expressed in particular cells. This often involves cutting edge technology,
such as the use of microarrays (DNA-ON-A-CHIP) that allow the expression level of
thousands of genes in a cell sample to be quickly determined. Once a large and
diverse database of expression data has been collected, the next step is to
identify connections between of genes and a particular disease state. In this
gene therapy can be located. Bioinformatics specialists work closely with bench
sciencists to accomplish the ``Data mining’’ that lies behi nd this next wave
of the pharmaceutical industry.
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