GENOMICS

• Genomics is an area within genetics that concerns
the sequencing and analysis of an organism’s
genome.
• The genome is the entire DNA content that is
present within one cell of an organism.
• Genomics is a discipline in genetics that applies
recombinant DNA, DNA sequencing methods, and
bioinformatics to sequence, assemble, and
analyze the function and structure of genomes.

• Genomics focuses on the development and
application of cutting-edge methods,
addressing fundamental questions with
potential interest to a wide audience.
• The fields of molecular biology and genetics
are mainly concerned with the study of the
role and function of single genes, a major
topic in today’s biomedical research.

• Genomics including genome projects, genome
sequencing, and genomic technologies and
novel strategies.
• Genomics including genome projects, genome
sequencing, and genomic technologies and
novel strategies
• The promise of genomics is huge. It could
someday help us maximize personal health
and discover the best medical care for any
condition.

• Genomics is a branch of genetics that studies
large scale changes in genomes of organisms.
• Bioinformatics is a hybrid field that brings
together the knowledge of biology and the
knowledge of information science, which is a
sub-field of computer science.
• Genomics and its subfield of transcriptomics,
which studies genome-wide changes in the RNA
that is transcribed from DNA, studies many
genes are once.

• Genomics may also involve reading and
aligning very long sequences of DNA or RNA.
Analysing and interpreting such large-scale,
complex data requires the help of computers.
The human mind, superb as it is, is incapable of
handling this much information.
• Bioinformatics is a hybrid field that brings
together the knowledge of biology and the
knowledge of information science, which is a
sub-field of computer science.

• Genomes of organisms are very large. The human
genome is estimated to have three billion base
pairs that contain about 25,000 genes.
• For comparison, the fruit fly is estimated to have
165 billion base pairs that contain 13,000 genes.
• Additionally, a subfield of genomics called
transcriptomics studies which genes, among the
tens of thousands in an organism, are turned on or
off at a given time, across multiple time points, and
multiple experimental conditions at each time
point.
• In other words, “omics” data contain vast amounts
of information that the human mind cannot grasp
without the help of computational methods in
bioinformatics.

• Common diseases such as type 2 diabetes and coronary
heart disease result from a complex interplay of genetic
and environmental factors.
• Recent developments in genomics research have
boosted progress in the discovery of susceptibility genes
and fuelled expectations about opportunities of genetic
profiling for personalizing medicine.
• Personalized medicine requires a test that fairly
accurately predicts disease risk, particularly when
interventions are invasive, expensive or have major side
effects.
• Recent studies on the prediction of common diseases
based on multiple genetic variants alone or in addition
to traditional disease risk factors showed limited
predictive value so far, but all have investigated only a
limited number of susceptibility variants.

• New gene discoveries from genome-wide association
studies will certainly further improve the prediction
of common diseases.
• Substantial improvements may only be expected if
we manage to understand the complete causal
mechanisms of common diseases to a similar extent
as we understand those of monogenic disorders.
• Genomics research will contribute to this
understanding, but it is likely that the complexity of
complex diseases may ultimately limit the
opportunities for accurate prediction of disease in
asymptomatic individuals as unravelling their
complete causal pathways may be impossible.

Application of
genomics in

• Genetic epidemiology is the study of the role of
genetics factors in determining health and
disease in families and in populations, and the
interplay of such genetic factors with
environmental factors.
• It is closely allied to both molecular
epidemiology and statistical genetics but these
overlapping fields each have distinct emphases,
societies and journals.

• More recently, the scope of genetic epidemiology
has expanded to include common diseases for
which many genes each make a smaller
contribution (polygenic, multifactorial or
mutagenic disorders).
• This has developed rapidly in the first decade of
the 21st century following completion of the
Human Genome Project, as advances in
genotyping technology and associated reductions
in cost has made it feasible to conduct large-scale
genome-wide association studies that genotype
many thousands of single nucleotide
polymorphisms in thousands of individuals.

• This traditional approach has proved highly
successful in identifying monogenic disorders
and locating the genes responsible.
• These have led to the discovery of many
genetic polymorphisms that influence the risk
of developing many common diseases.

• Proteomics 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.
• Proteomics is a rapidly growing field of that is
concerned with the systematic, high-throughput
approach to protein expression analysis of a cell
or an organism.
• Typical results of proteomics studies are
inventories of the protein content of differentially
expressed proteins across multiple conditions.

History of proteomics

• The first protein studies that can be called
proteomics began in 1975 with the introduction
of the two-dimensional gel and mapping of the
proteins from the bacterium Escherichia coli,
guinea pig and mouse. Albeit many proteins
could be separated and visualized, they could
not be identified.
• The terms “proteome” and “proteomics” were
coined in the early 1990s by Marc Wilkins, a
student at Australia's Macquarie University, in
order to mirror the terms “genomics” and
“genome”, which represent the entire collection
of genes in an organism

• Following the release of the Human Genome
Sequence data in 2004, humans are considered to
have 19,599 genes encoding proteins.
• Alternative RNA splicing and post-translational
modification may result in 1 million or more
proteins or protein fragments. As a consequence,
the proteome is far more complex than the
genome.
• Advances in methods and technologies have
catalysed an expansion of the scope of biological
studies from the reductionist biochemical analysis
of single proteins to proteome-wide
measurements.

• Proteomics and other complementary analysis
methods are essential components of the
emerging 'systems biology' approach that
seeks to comprehensively describe biological
systems through integration of diverse types
of data and, in the future, to ultimately allow
computational simulations of complex
biological systems.
• Detailed analysis of the proteome permits the
discovery of new protein markers for
diagnostic purposes and of novel molecular
targets for drug discovery.

Role of
proteomics in

• Proteomics is a branch of Bioinformatics that deals
with the techniques of molecular biology,
biochemistry, and genetics to analyze the structure,
function, and interactions of the proteins produced
by the genes of a particular cell, tissue, or organism.
This technology is being improved continuously and
new tactics are being introduced.
• In the current day and age it is possible to acquire
the proteome data.
• Bioinformatics makes it easier to come up with new
algorithms to handle large and heterogeneous data
sets to improve the processes.

• To date, algorithms for image analysis of 2D
gels have been developed. In case of mass
spectroscopy, data analysis algorithms for
peptide mass fingerprinting and peptide
fragmentation fingerprinting have been
developed.

• Proteomics technologies are under continuous
improvements and new technologies are
introduced. Nowadays high throughput
acquisition of proteome data is possible.
• The young and rapidly emerging field of
bioinformatics in proteomics is introducing
new algorithms to handle large and
heterogeneous data sets and to improve the
knowledge discovery process.

• For example new algorithms for image analysis of
two dimensional gels have been developed within
the last five years. Within mass spectrometry
data analysis algorithms for peptide mass
fingerprinting (PMF) and peptide fragmentation
fingerprinting (PFF) have been developed.
• Local proteomics bioinformatics platforms
emerge as data management systems and
knowledge bases in Proteomics. We review recent
developments in bioinformatics for proteomics
with emphasis on expression proteomics.

• Proteins are the principal targets of drug discovery.
Most large pharmaceutical companies now have a
proteomics-oriented biotech or academic partner or
have started their own proteomics division.
• Common applications of proteomics in the drug
industry include target identification and validation,
identification of efficacy and toxicity biomarkers
from readily accessible biological fluids, and
investigations into mechanisms of drug action or
toxicity.
• Proteomics technologies may also help identify
protein–protein interactions that influence either
the disease state or the proposed therapy.

• Proteomics is widely envisioned as playing a
significant role in the translation of genomics to
clinically useful applications, especially in the areas of
diagnostics and prognostics.
• In the diagnosis and treatment of kidney disease, a
major priority is the identification of disease-
associated biomarkers. Proteomics, with its high-
throughput and unbiased approach to the analysis of
variations in protein expression patterns, promises to
be the most suitable platform for biomarker discovery.
• Combining such classic analytical techniques as two-
dimensional gel electrophoresis with more
sophisticated techniques, such as MS, has enabled
considerable progress to be made in cataloguing and
quantifying proteins present in urine and various
kidney tissue compartments diseased physiological
states.

• Proteomics is vital for decrypting how proteins
interact as a system and for comprehending
the functions of cellular systems in human
disease.
• Advances in mass spectrometry, coupled with
better isolation and enrichment techniques
which allows the separation of organelles and
membrane proteins, made the in-depth
analysis of cardiac proteome a reality.

• While neurovascular diseases such as ischemic and
haemorrhagic stroke are the leading causes of
disability in the world, the repertoire of therapeutic
interventions has remained remarkably limited.
• There is a dire need to develop new diagnostic,
prognostic, and therapeutic options. The study of
proteomics is particularly enticing for
cerebrovascular diseases such as stroke, which most
likely involve multiple gene interactions resulting in a
wide range of clinical phenotypes.
• Currently, rapidly progressing neuroproteomic
techniques have been employed in clinical and
translational research to help identify biologically
relevant pathways.

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