SureshKumar's Bioinformatics Blog

I am Suresh Kumar Sampathrajan. I have completed my PhD degree in bioinformatics from the University of Vienna, Austria in the year 2010. If you want to know more about me and my research,please click the menus at the top.

I have started this bioinformatics blog mainly for undegraduate and postgraduate students of bioinformatics. This blog will serve as an open resource material for the students and for those who wish to know about bionformatics. This blog contains video tutorials, tips, bioinformatics software downloads, articles on bioinformatics and career opportunities.

Modelling a protein through automatic comparative modelling servers

It is possible to a model a protein if we have more than 50% identical residues in an alignment between the target and a template protein. The modelling process has following steps

>> Choosing a suitable template sequences
>> Algining template and target sequences
>> Building backbone
>> constructing loop and generating side chains


Finding suitable template is usually done by performing a BLAST search against the sequences in the PDB, the respoistory for protein sturcture obtained by X-ray crystallography and NMR. All sequences in the PDb with an E-value of Blast below a certain treshold are considered as candidates for the template. The alignment between template and target sequences should atleast contain 30% identities and most important it should have existence of conserved regions. A mulitple sequence alignment with same family members of the template or several template sequences may also be constructed. This step requires some manual correction of the alignment in order to obtain a reliable model.Several methods are used for loop building and side chain reconstruction.



When no suitable template is available for comparative modeling, de novo modeling methods (also called ab initio modeling) may be used. The success rate with such modeling is considerably lower than that with comparative modeling. The accuracy of de novo models is too low for problems requiring high-resolution structure information."


Automatic Comparative modelling servers

Ready made Perl scripts to manipulate biological data

The Scriptome is a minimal-learning toolbox for manipulating biological data especially for biologists.
There are currently six tool categories: Calculate, Change, Choose, Fetch, Merge, and Sort. Popular tools include:
- Choosing lines where the value in a given column exceeds a certain threshold. This can be especially useful with files larger than Excel's limit of 65535 lines.
- Merging files together based on shared values in certain columns. This tool essentially performs a SQL join.
- Changing FASTA files to a tabular format. The output can be viewed in Excel, or filtered with other Scriptome tools.

Each tool is a short Perl script embedded in a one-line shell command. These tools can be cut and pasted from the website onto the command line. The tools' simplicity makes it possible to develop tools rapidly, to keep up with biologists' changing needs.

The Scriptome requires no installation at all on UNIX and Macintosh, since Perl is standard on those platforms. Windows users need only a one-click installation of Perl from ActiveState. A few tools also require Bioperl.


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