1:-Introduction ( Hoersch et al. 2000)( Hogeweg 2011)

1:-Introduction ( Hoersch et al. 2000)( Hogeweg  2011)Bioinformatics is aemerging and developing field in the modern age. It has given many benefits toscientist in their research projects. It provides this ease by using differentmethods to store, retrieve and analyses the data either it is of biology or mathematics.Biological data may be of DNA, RNA and protein and all these biomoleculescontain unique sequences which are related to their functions. Bioinformaticsapproaches are emerging day by day which allows scientist to measure thechanges and regulation in genome wide genes simultaneously. Scientist hasdevised many bioinformatics tools to analyses sequence of different nature andall these tools serve different purposes.

Sequence analyses usually refer tocollect that information of the biomolecule (nucleic acid and protein) whichgives it to its unique function. Different tools are used for different purposes.Nature of analyses determines which type of tool should be used.

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

order now

Sequences aresubjected to these tools which predict its function according to their natureand features which are very much related to biomolecules function. Theobjective of this review is to encompass all the tools being used forbiological sequence analysis.                                2:-Bioinformatics Tools For Biological Seq Analysis2.

1:-Basic Local AlignmentSearch Tool (BLAST) (Johnson et al. 2008)It is sequence similaritysearch tool which can be use through web to compare users query to databases ofsequence. Different types of blast compare combination of nucleotide or proteinqueries to databases of nucleotide and protein. It usually finds similaritybetween two sequences and then align these sequence it tells about thealignment score expect value or E value of alignment. BLAST usually calculatesstatical significance by comparing nucleotide and protein sequences to databasesequence. It can be implemented in a number of ways to find out similaritybetween different sequences2.

2:-ClustalOmega ( Sievers et al. 2011)Multiple sequence alignment is very important in bioinformatics becauseit compares homologous sequences .we have an accurate tool for this purposeknown as Clustal Omega. It can align sequence of any size. It has generatedalignments of over 190,000 sequences in very few hours. So basically it canalign very large number of sequences accurately.

It has a number of features ofadding new sequences to the existing alignments or adding existing alignmentsinto the new sequences which help to align new sequences of DNA/RNA or protein. It allows user to specify a profile “HMM” whichis basically obtained from an alignment of the sequences that are similar tothe input set. Then sequences are aligned to these ‘externalprofiles’ which help them align to the rest of the input set. This tool has afull confidence on the accuracy of the alignments which are made by using it.That’s why it is most widely used tool for multiple seq alignment of nucleotideor protein.2.3:-GENSCAN (Burge et al.

1997)It is a tool which is used to identify the gene structures in genomicDNA.It predicts the location of exons and introns in the genomic DNA sequencesfrom a variety of organisms. It resolved the fundamental biochemical issues ofspecifying the accurate sequence determinants of transcription translation andRNA splicing.

It also identifies thewhole structure of exons and introns in genomic DNA.This tool can also estimatethe multiple genes in a sequence to deal with partial plus complete genes andto forecast the consistent set of genes occurring on either or both strands ofDNA. It has more accuracy than existing methods, with 70-80% exons identified accurately.It is expected that the statistical analysis of genes may give some clues tothe biochemical processes such as transcription, translation and RNA splicingwhich define genes biologically.2.4:-“CARNA”—alignment of RNA structure ensembles (Sorescu et al. 2012)Several approaches are use now a day for RNA analysis.

These approaches compare the RNA sequences with already predicted or single RNAstructure simultaneously. But we need another tool for multiple sequencealignment of RNAs available, where these approaches are not good to use andhave limitations. We introduced another tool for the multiple sequencealignment of RNA with riboswitch or pseudoknot structures and this tool isnamed as “CARNA”this tool supports multiple RNAs with conserved structure andaligns these pseudoknots originally. So CARNA is basically useful for aligningRNA riboswitch, which have more than one stable structure. We have to put RNAsequence as input and analyze base pair probability matrices and align thesequences on the basis of full ensembles of structures. So this tool isspecialized to align RNA with conserved structures.2.5:- “IPknot”:  IP-based prediction of RNA pseudoKNOTs (Satoet al.

2011)It is usedfor the prediction of RNA secondary structures with pseudokots based on theaccuracy of predicted structures. It breaks down the RNA structure with pseudoknotinto a set of pseudoknot free structures and predict base pairingprobability distribution that considers pseudoknot.It is an IP(integerprogramming) based prediction tool for RNA having pseudoknot .it is moreaccurate than previously used IP based methods. It computes the base pairpossibilities used in the IP objective function and solve the IP problem toestimate the optimal pseudoknoted RNA secondary structure. It can take a singlesequence or aligned sequence as input. Prediction accuracy of IPknot depends onits scoring functions as this method uses approximate possibilitiesdistribution of pseudoknoted structures.

Another fact is that IPknot can runquite fast long sequences less than one thousands bases. So it is a fast andaccurate computational prediction tool for both single sequence analysis andcomparative sequence analysis.


I'm Mary!

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

Check it out