ABSTRACT majority of which are freely available.

ABSTRACT                         The pace, by whichscientific knowledge is being produced and shared today, was never been so fastin the past.

Different areas of science are getting closer to each other togive rise new disciplines. Bioinformatics is one of such newly emerging fields,which makes use of computer, mathematics and statistics in molecular biology toarchive, retrieve, and analyse biological data. Although yet at infancy it hasbecome one of the fastest growing fields, and quickly established itself as anintegral component of any biological research activity. It is getting populardue to its ability to analyze a huge amount of biological data quickly andcost-effectively. Bioinformatics can assist a biologist to extract valuableinformation from biological data providing various web- and/or computer-basedtools, the majority of which are freely available.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now

The present review gives acomprehensive summary of some of these tools available to a life scientist toanalyse biological data. Exclusively this review will focus on those areas ofbiological research, which can be greatly assisted by such tools like analyzinga DNA and protein sequence to identify various features, prediction of 3Dstructure of protein molecules, to study molecular interactions, and to performsimulations to mimic a biological phenomenon to extract useful information fromthe biological data. The functioning and specificity of the tools like,iTasser, some other softwares and tools given on other pages and these are discussedin the following review.Introduction                              Bioinformatics isan interdisciplinary science, emerged by the combination of various otherdisciplines like biology, mathematics, computer science, and statistics, todevelop methods for storage, retrieval and analyses of biological data.PaulienHogeweg, a Dutch system-biologist, was first person who used the term”Bioinformatics” in 1970, referring to the use of information technology for studyingbiological systems. The launch of userfriendly interactive automated modelingalong with the creation of SWISS-MODEL server around 18 years ago resulted inmassive growth of this discipline. Since then, it has become an essential partof biological sciences to process biological data at a much faster rate withthe databases and informatics working at the back end.

These tools are alsoused for the designing of the primer and some other important sequencing likethe DNA and RNA or some protiens sequencing.                                 Computationaltools are routinely used for characterization of genes, determining structuraland physiochemical properties of proteins, phylogenetic analyses, andperforming simulations to study how biomolecule interact in a living cell.Although these tools cannot generate information as reliable asexperimentation, which is expensive, time consuming and tedious, however,the insilico analyses can still facilitate to reach an informeddecision for conducting a costly experiment. For example, a druggable moleculemust have certain ADMET properties to pass through clinical trials. If acompound does not have required ADMETs, it is likely to be rejected.

To avoidsuch failures, different bioinformatics tools have been developed to predictadmit properties, which allow researchers to screen a large number of compoundsto select most drugable molecule before launching of clinical trials. Earlier,a number of reviews on various specialized aspects of bioinformatics have beenwritten. However, none of these articles makes it suitable for a scientist whodoes not belong to computational biology. Here, we take the opportunity tointroduce various tools of bioinformatics to a non-specialist reader to helpextract useful information regarding his project. Therefore, we have selectedonly those areas where these tools could be highly useful to obtain usefulinformation from biological data. These areas include analyses of DNAsequences, phylogenetic studies, predicting 3D structures of protein molecules,molecular interactions and simulations as well as drug designing. Theorganization of text in each section starts from a simplistic overview of eacharea followed by key reports from literature and a tabulated summary of relatedtools, where necessary, towards the end of each section.i.

                  iTassar                                 Iterative Threading Assembly Refinementis abioinformatics method for predicting three-dimensional structure model ofprotein molecules from amino acid sequences.Specificity                        It detects thestructure templates from Protein Data Bank by a technique calledfold recognition or threading. The full-length structure models areconstructed by reassembling structural fragments from threading templates usingReplica Exchange Monte Carlo Simulation. I-TASSER is one of the mostsuccessful protein structure prediction methods in thecommunity-wide CASP experiments.

I-TASSER has been extended forstructure-based protein function predictions, which provides annotationson ligand bindingsite, geneontology and enzymecommission by structurally matchingstructural models of the target protein to the known proteins in proteinfunction databases. It has an on-line server built in the Yang Zhang Lab at the University of Michigan, AnnArbor, allowing users to submitsequences and obtain structure and function predictions. A standalone packageof  I-TASSER is available for download at the I-TASSERwebsite.Functioning The I-TASSER server allows usersto generate automatically protein structure and function predictions.·        Input·        Mandatory·           Amino acid sequence with length from 10 to1,500 residues·        Optional·           Contact restraints·           Distance maps·           Inclusion of special templates·           Exclusion of special templates·           Secondary structures·        Output·        Structureprediction·           Secondary structure prediction·           Solvent accessibility prediction·           Top 10 threading alignment from LOMETS·          Top 5 full-length atomic models·          Top 10 proteins in PDB which are structurallyclosest to the predicted models·           Estimated accuracy of the predicted models·           B-factor estimation·        Function prediction:·            Enzyme Classification and the confidencescore·            Gene Ontology terms and the confidencescore·             Ligand-binding sites and the confidence score·             An image of the predicted ligand-bindingsitesConclusion andFuture ProspectsBioinformatics is a comparatively young discipline and hasprogressed very fast in the last few years. It has made it possible to test ourhypotheses virtually and therefore allows to take a better and an informeddecision before launching costly experimentations. Although, more and moretools for analyzing genomes, proteomes, predicting the structures, rationaldrug designing and molecular simulations are being developed, none of them is’perfect’. Therefore hunt for finding a better package for solving the givenproblems will continue.

One thing is clear that the future research will beguided largely by the availability of databases, which could be either genericor specific. It can also be safely assumed, based on the developments in thefield of bioinformatics, that the bioinformatics tools and software packageswould be able to give results that are more accurate and thus more reliableinterpretations. Prospects in the field of bioinformatics include its futurecontribution to functional understanding of the human genome, leading toenhanced discovery of drug targets and individualized therapy.

Thus,bioinformatics and other scientific disciplines have to move hand in hand toflourish for the welfare of humanity. And some other softwares and tools aregiven below·        Ensamble·        Readseq·        INSDC·        DDBJ·        PIR·        AceDB·        BanKit·        Sequin·        Spin·        Panther·        NCBI ORF finder·        ORF Predicter·        ORF Investigation·        RNA Seq·        PDB·        UniProt·        UCSC·        Genbank·        Expaxy·        Ensamble·        Readseq·        Entrez·        Magpie·        GenQuiz·        GenScan·        ORF finder·        Modeller·        I-TasserREFERENCES Mount DW Sequence and genome analysis. New York: Cold Spring. Hesper B, Hogeweg P Bioinformatica:eenwerkconcept. Kameleon 1:28-9. Hogeweg P The roots of bioinformatics in theoretical biology. PLoS Comput Biol 7: e1002021.

Peitsch MC ProMod and Swiss-Model: Internet-based tools for automated comparative protein modelling. Biochem Soc Trans 24: 274-279. Dibyajyoti S, Bin ET, Swati P Bioinformatics: The effects on the cost of drug discovery. Galle Med J 18:44-50. Ouzounis CA, Valencia A Early bioinformatics: the birth of a discipline–a personal view.

Bioinformatics 19: 2176-2190. Molatudi M, Molotja N, Pouris A Abibliometric study of bioinformatics research in South Africa. Scientometrics 81:47-59. Ouzounis CA Rise and demise of bioinformatics? Promise and progress. PLoS Comput Biol 8: e1002487. Geer RC, Sayers EW Entrez: making use of its power. Brief Bioinform 4: 179-184.

Parmigiani G, Garrett ES, Irizarry RA, Zeger SL. The analysis of gene expression data: an overview of methods and software, Springer, New York.


I'm Mary!

Would you like to get a custom essay? How about receiving a customized one?

Check it out