Genomics and Proteomics Analysis

8/3/2019 Genomics and Proteomics Analysis

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Dr J Boateng BIOT 1011Bioinformatics

The biotechnology/IT

market will increase

at a compound annualgrowth rate (CAGR) of

24% to nearly $38

billion by 2006.

Source: IDC Research

Biotech and pharmaceutical companies

spent $10 billion on hardware, software,and services in 2002.

Source: Gartner

Reference: Prof. A.S. Kolaskar Vice Chancellor, University of Pune


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GENOMICSGenetics:the science of genes, heredity, and the variationoforganisms. In modern research, genetics providestoolsin the investigation of the functionof a particulargene, e.g. analysis of genetic interactions.

Genomics:the study of large-scale genetic patterns across thegenome for a given species. It deals with the

systematic use of genome information to provideanswers in biology, medicine, and industry.


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The study of sequences, gene organization &

mutations at the DNA level i.e. the study ofinformation flow within a cell

Genomicshas the potential of offering newtherapeutic methods for the treatment ofsome diseases, as well as new diagnosticmethods.

Major tools and methods related to genomics

are bioinformatics, genetic analysis,measurement of gene expression, anddetermination of gene function.



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GENOME COMPARISONSSpecies Chrom. Genes Base pairs

Humans 46 28-35,000 3.1 billion

Mouse 40 22.5-30000 3.1 billion

Puffer fish 44 31000 2.7 million

Malaria Mosquito 6 14000 365 million

Fruit Fly 8 14000 137 million

Roundworm 12 19000 97 million

E. Coli 1 5000 4.1 million


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GENOMIC ANALYSIS Many diverse studies require the determinationof the abundance of large numbers of specific

DNA or RNA molecules in complex mixtures,including, for example, the determination of the

changes in mRNA levels of many genes

Genome analysis entails the prediction of genes inuncharacterized genomic sequences.

The 21st century has seen the announcement of thedraft version of the human genome sequence. Modelorganisms have been sequenced in both the plant

and animal kingdoms.


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GENOMIC ANALSIS However, the pace of genome annotation is not

matching the pace of genome sequencing.

Experimental genome annotation is slow andtime consuming. The demand is to be able todevelop computational tools for gene

prediction. Computational gene prediction is relatively simple for the

prokaryotes where all the genes are converted into thecorresponding mRNA and then into proteins.

The process is more complex for eukaryotic cells wherethe coding DNA sequence is interrupted by randomsequences called introns.


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BIOLOGICAL QUESTIONSSome of the questions biologists want to answertoday are:

What part of and DNA sequence codes for aprotein and what part of it is junk DNA?

Classify the junk DNA as intron, untranslatedregion, transposons, dead genes, regulatoryelements.

Divide a newly sequenced genome into thegenes (coding) and the non-coding regions.


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Biological Research in 21st

Century

The new paradigm, now emerging is thatall the 'genes' will be known (in the sense

of being resident in databases availableelectronically), and that the starting "pointof a biological investigation will be

theoretical.- Walter Gilbert


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IMPORTANCE OF GENOME

ANALYSIS The importance of genome analysis can be

understood by comparing the human andchimpanzee genomes.

The chimp and human genomes vary byan average of just 2% i.e. just about 160enzymes. A complete genome analysis of

the two genomes would give a stronginsight into the various mechanismsresponsible for the differences.


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COMPLEXITY IS AN UNDERSTATEMENT?


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GENOMIC ANALYSIS_ basics

Techniques used to estimate the relativeabundance of two or more sets of mRNA

differential screening of cDNA libraries,

subtractive hybridization,

differential display,

However, more advanced methods havebeen recently developed.


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GENOMICS ANALYSIS_Advances

Advanced methods are particularlyamenable to organisms whose entiregenome sequences are known, such as S.cerevisiae.

It is now practicable to investigatechanges of mRNA levels of all yeast openreading frames (ORFs) in one experiment.


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Advanced genomic analysis techniques

DNA sequencing

DNA microarray technology analysis of gene expression profiles at the mRNA level

Bioinformatic tools to organize and analyze

such data

Chip-based analysis of samples

Models of gene networks


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Microarray Technology


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Post-genomic Era Series of omics

Comparative genomics

Structural and functional genomics

Transriptomics

Proteomics

Metabolomics


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Bioinformatics toolsneeded for analysis of

data from theseomics


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Data MiningDevelopment of new tools for data mining

Sequence alignment

Genome sequencing

Genome comparison

Micro array data analysis Proteomics data analysis

Small molecular array analysis

To derive information and gain knowledge from thedata


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COMPARATIVE GENOMICS

Analyzing & comparing genetic material fromdifferent species to study evolution, gene

function, and inherited disease

Understand the uniqueness between different

species

Comparative genomics involves the use of

computer programs that can line up multiplegenomes and look for regions of similarityamong them.


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When we BLAST a sequence is that

comparative genomics?

Difference is in Scale and Direction

One or several genes

compared against all

other known genes.

Use genome toinform us about the

entire organism.

Use information frommany genomes to learn

more about the

individual genes.

Entire Genome

compared to other

entire genomes.

Other omics Comparative


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Background on Comparative

Genomic Analysis Sequencing the genomes of the human,

the mouse and a wide variety of otherorganisms - from yeast to chimpanzees

Driving force for the development of newfield of biological research called -

comparative genomics.



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BACKGROUND Comparing the human genome with the

genomes of different organisms helps tobetter understand gene structure and

function and thereby develop newstrategies in the battle against humandisease.

Comparative genomics also provides apowerful new tool for studying evolutionarychanges among organisms.


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This helps to identify the genes that areconserved among species along with thegenes that give each organism its ownunique characteristics.

Using computer-based analysis to zero in onthe genomic features that have beenpreserved in multiple organisms over

millions of years, researchers will be ableto pinpoint the signals that control genefunction.

This should in turn translate into innovativeapproaches for treating human diseaseand improving human health.



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BACKGROUND

The evolutionary perspective may proveextremely helpful in understanding diseasesusceptibility. For example, chimpanzees donot suffer from some of the diseases that strikehumans, such as malaria and AIDS.

A comparison of the sequence of genesinvolved in disease susceptibility may reveal

the reasons for this species barrier, therebysuggesting new pathways for prevention ofhuman disease.


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BACKGROUND Although living creatures look and behave inmany different ways, all of their genomes

consist of DNA, the chemical chain that makesup the genes that code for thousands ofdifferent kinds of proteins.

Precisely which protein is produced by a givengene is determined by the sequence in which

four chemical building blocks - adenine (A),thymine (T), cytosine (C) and guanine (G) - arelaid out along DNA's double-helix structure.


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BACKGROUND In order for researchers to most efficiently use an

organism's genome in comparative studies, dataabout its DNA must be in large, contiguous

segments, anchored to chromosomes and, ideally,fully sequenced.

Furthermore, the data needs to be organized for

easy access and high-speed analysis bysophisticated computer software.

Organisms that have been completely sequencedinclude: mouse (Mus musculus), human (Homosapiens), fruit fly (Drosophila melanogaster); and....................


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BACKGROUND

The fledgling field of comparative genomics hasalready yielded some dramatic results.

For example, a March 2000 study comparing thefruit fly genome with the human genome discoveredthat about 60 percent of genes are conserved

between fly and human.

Simply put, the two organisms appear to share a

core set of genes. Researchers have found thattwo-thirds of human cancer genes havecounterparts in the fruit fly.


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BACKGROUND More surprisingly, when scientists inserted a

human gene associated with early-onset

Parkinson's disease into fruit flies, theydisplayed symptoms similar to those seen inhumans with the disorder.

This raises the possibility that the tiny insects

could serve as a new model for testingtherapies aimed at Parkinson's.

C ti G i


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Comparative Genomics

What one should look for?Human

P. falciparum

Mosquito

Proteins that are shared by

All genomes

Exclusively by Human & P.f.

Exclusively by Human &Mosquito

Exclusively by P.f. & Mosquito

Unique proteins in

Human

P.f. Targets foranti-malarial drugs

Mosquito


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Comparative Gene Prediction

GenScan: ab initio gene prediction.

GeneWise, Procrustes : homology guided.

Rosseta, SGP1 (Syntetic Gene Prediction), CEM(Conserved Exon Method) : gene prediction andsequence alignment are clearly separated.

GenomeScan: Ab Initio modified by BLASThomologies.

SGP-2, TwinScan, SLAM, DoubleScan :modification of GenScan scoring schema toincorporate similarity to known proteins.


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Proteomics (Practical) - the study of theproteome using technologies of large-scale proteinseparation and identification.

Large scale separation : 2DELiquid Chromatography

Identification : MALDI MS

Tandem MS/MSFT-MS ..

Proteomics by the dictionary


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http:www.bio-itworld.com/archive/031704/horizons_horizons_comm.html



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Proteomics according to MedlineDevelopment of Proteomics

1730

From 220 publications in the previous millennium (94-99)To 21,350 (!!!) publications in this millennium (00-05)

0

10002000

3000

4000

50006000

7000

8000

9000

1997 1998 1999 2000 2001 2002 2003 2004

Papers

Reviews


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Proteomics by Google

THE REALISTIC TRUTH.

Proteomics 886,000 hits (2004)4,700,000 hits (2005)

Genomics 2,070,000 hits (2004)16,000,000 hits (2005)


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Comparing Proteomics & Genomics

Genome Genomics

analysis

proteome Proteome

analysis

DNA

Nc-RNA

mRNA Coding DNA Proteins

Peptides

Glyco, other

modifications

linear Dynamic

Up/down

3D Dynamic

Up/ down

variants

Completion

Archived

(EST, cDNA,GEO

No notion ofcompletion

Poorly archived


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Proteomics GenomicsMore differences

Gene/ RNA

dynamic

Protein

dynamicStable molecules

Handling cheap/ easyMinimal modification

Works in isolation

Fragile molecules

Handling dependentLabile modification

Protein-interaction

Localization dependent

Handle

Tech

HTP

Sequencing (established) MS related (not yet)

DNA array / genotyping/expression / CGH/

Protein Chip (not yet)

Antibodies array (not yet)


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Proteomics:Original definition: study of the proteins

encoded by the genome of a biological sample

Current definition: study of the wholeproteincomplement of a biological sample (cell, tissue,

animal, biological fluid [urine, serum])

Usually involves high resolution separation of

polypeptides at front-end, followed by massspectrometry identification and analysis


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Challenges facing Proteomic TechnologiesChallenges facing Proteomic Technologies Limited/variable sample material

Sample degradation (occurs rapidly, even during sample

preparation) Vast dynamic range required

Post-translational modifications (often skew results)

Specificity among tissue, developmental and temporalstages

Perturbations by environmental (disease/drugs)conditions

Researchers have deemed sequencing the genomeeasy, as PCR was able to assist in overcoming many ofthese issues in genomics.


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The Proteomics Tool Kit technologies for separating and

visualizing proteins and peptides

technologies for assessing protein-proteininteractions

technologies for identifying proteins* technologies for quantifying protein

expression*

bioinformatic tools for assessment andcommunication

Proteomic TechnologiesProteomic Technologies


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Proteomic TechnologiesProteomic Technologies

Amino Acid Composition

Array-based Proteomics

2D PAGE

Mass Spectrometry

Structural Proteomics

Informatics (and the challenges facing the

Human Proteome Project)


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Amino Acid Composition (Edmund)Amino Acid Composition (Edmund)

Pioneering method of obtaining information fromproteins.

Cumbersome and tedious by todays standards.

Requires the use of terrible smelling -mercaptoethanol.

Not high-throughput by todays standards,hence, comp is no longer the most widely usedtechnique.


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Protein Sequencingstep 1, fragmenting into peptides

Protein Sequencingstep 1, fragmenting into peptides


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Protein Sequencingstep 2, sequencing the peptides by Edmund degradation.

Separation by HPLC and detect by absorbance at 269nm.

A b d P t iA b d P t i


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Array-based ProteomicsArray-based Proteomics

Employ two-hybrid assays

Use GFP, FRET, and GST GFP = green florescent protein

FRET = florescence resonance energytransfer

GST = glutathione S-transferase, a wellcharacterized protein used as a markerprotein.


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A b d P t iA b d P t i


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Offer a high-throughput technique forproteome analysis.

These small plates are able to hold manydifferent samples at a time.

Current research is ongoing in an attemptto interface array methodologies with

Mass Spectrometry at ORNL.

2D PAGE2D PAGE


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2D PAGE2D PAGE 2-D gel electrophoresis is a multi-step procedure that

can be used to separate hundreds to thousands ofproteins with extremely high resolution.

It works by separation of proteins by their pI's in onedimension using an immobilized pH gradient (firstdimension: isoelectric focusing) and then by their MW'sin the second dimension.

The core technology of proteomics is 2-DE

At present, there is no other technique that is capable ofsimultaneously resolving thousands of proteins in oneseparation procedure. (sited in 2000)

E l ti f 2 DE th d l


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Traditional IEF procedure:

Iso electric focusing (IEF) in run in thin polyacrylamide gelrods in glass or plastic tubes.

Gel rods containing: 1. urea, 2. detergent, 3. reductant,and 4. carrier ampholytes (form pH gradient).

Problem: 1. tedious. 2. not reproducible.

Evolution of 2-DE methodology

In the past

Evolution of 2 DE methodology


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SDS-PAGE Gel size:

This OFarrell techniques has been used for 20 years

without major modification.

20 x 20 cm have become a standard for 2-DE.

Assumption: 100 bands can be resolved by 20 cm long1-DE.

Therefore, 20 x 20 cm gel can resolved 100 x 100 =10,000 proteins, in theory.


100

100

Evolution of 2 DE methodology


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Problems with traditional 1st dimension IEF

Works well for native protein, not good for denaturingproteins, because:

1. Takes longer time to run.

2. Techniques are cumbersome. (the soft, thin, long gel rodsneeds excellent experiment technique)

3. Batch to batch variation of carrier ampholytes.

4. Patterns are not reproducible enough.

5. Lost of most basic proteins and some acidic protein.


OPERATOR DEPENDENT

2D PAGE2D PAGE


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2D PAGE2D PAGE

2-D gel electrophoresis process consists ofthese steps:

Sample preparation First dimension: isoelectric focusing

Second dimension: gel electrophoresis

Staining

Imaging analysis via software

Challenges for 2 DE


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Challenges for 2-DE

1. Spot number:

10,000-150,000 gene products in a cell.

PTM makes it difficult to predict real number.

Sensitivity and dynamic range of 2-DE must be adequate.

Its impossible to display all proteins in one single gels.

Challenges for 2-DE


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Challenges for 2-DE

2. Isoelectric point spectrum:

pI of proteins: range from pH 3-13. (by in vitrotranslated ORF)

PTM would not alter the pI outside this range.

pH gradient from 3-13 dose not exist.

For proteins which pI > 11.5, they need to be handedseparately.

Challenges for 2 DE


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Challenges for 2-DE

3. molecular weights:

Small proteins or peptides can be analysed bymodifying the gel and buffer condition of SDS-PAGE.

Protein > 250 kDa do not enter 2nd

SDS-PAGEproperly.

1-DE (SDS-PAGE) can be run in a lane at the side of2-DE.

Challenges for 2-DE


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Challenges for 2-DE

4. hydrophobic proteins:

Some very hydrophobic proteins do not go insolution.

Some hydrophobic proteins are lost duringsample preparation and iso electric focusing

(IEF).

More chemical developments are required.

Challenges for 2-DE


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Challenges for 2-DE

5. Sensitivity of detection:

Low copy number proteins are very difficultto detect, even employing most sensitive

staining methods.

Sensitivity of staining methods:

1. Silver staining2. Fluorescent staining

3. Dye binding staining (CBR)

Challenges for 2-DE


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Challenges for 2-DE

6. Loading capacity:

For detection of low abundant proteins,more sample needs to be loaded.

A wide dynamic range of the SDS-PAGE isrequired to prevent merging of highlyabundant protein.

Loading capacity: IEF > SDS-PAGE.

Challenges for 2-DE


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Challenges for 2 DE

7. Quantitation:

The detection method must give reliablequantitative information.

Silver staining does not give reliablequantitative data.

Challenges for 2-DE


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Challenges for 2-DE

8. Reproducibility:

Highest importance in 2-DE experiment.

Immobilized pH gradient strip haveimproved a lot for 1st dimensionconsistency

Variation most comes from samplepreparation.


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A good-looking spot pattern streak and smear free is not a guarantee for best 2-DEprotocol

Technologies for identifying


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g y g

proteins Western blotting

Chemical (Edman) sequencing ofproteins

mass spectrometry

peptide mass fingerprint

mass spec decaydatabases and search engines

Mass SpectrometryMass Spectrometry


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Mass SpectrometryMass Spectrometry

Mass Spectrometry is another tool to analyzethe proteome.

In general a Mass Spectrometer consists of: Ion Source

Mass Analyzer

Detector

Mass Spectrometers are used to quantify themass-to-charge (m/z) ratios of substances.

From this quantification, a mass is determined,proteins are identified, and further analysis isperformed.

MASS SPECTROMETRY


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MASS SPECTROMETRY

MORE DETAILED MASS SPECTROMETRYAPPLICATIONS IN MORNING LECTURE ON

28TH NOVEMBER 2011


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application of bioinformatics in the

fields of genomics and proteomics

What is Bioinformatics?


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What is Bioinformatics?

Conceptualizing biology in terms ofmolecules and then applying

informatics techniques from math,computer science, and statistics to

understand and organize the informationassociated with these molecules on a

large scale

How do we use Bioinformatics?


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How do we use Bioinformatics?

Store/retrieve biological information(databases)

Retrieve/compare gene sequences

Predict function of unknown genes/proteins

Search for previously known functions of agene

Compare data with other researchers Compile/distribute data for other researchers

Sequence retrieval:


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National Center for BiotechnologyInformation

GenBank and other genome databases

Protein Structure:

3D modeling programs RasMol, Protein Explorer

Sequence comparison programs:

BLAST GCG MacVector


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Similarity Search: BLAST


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Similarity Search: BLAST

A tool for searching gene or protein sequence

databases for related genes of interest

The structure, function, and evolution of a genemay be determined by such comparisons

Alignments between the query sequence andany given database sequence, allowing formismatches and gaps, indicate their degreeof similarity

http://www.ncbi.nlm.nih.gov/BLAST/

% identity


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MRCKTETGAR

MRCGTETGAR

% identity

90%

CATTATGATA

GTTTATGATT

70%

Strengths:


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Accessibility

Growing rapidly

User friendly

Weaknesses:

Sometimes not up-to-date

Limited possibilities

Limited comparisons and information

Not accurate

Need for improved Bioinformatics


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Genomics: Human Genome Project Gene array technology

Comparative genomics Functional genomics

Proteomics: Global view of protein

function/interactions

Protein motifs

Structural databases

Data Mining


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Data Mining

Handling enormous amounts of data

Sort through what is important and what is not

Manipulate and analyze data to find patternsand variations that correlate with biological

function

Proteomics


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Proteomics Uses information determined bybiochemical/crystal structure methods

Visualization of protein structure Make protein-protein comparisons

Used to determine:

- conformation/folding

- antibody binding sites

- protein-protein interactions

- computer aided drug design


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