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<!doctype html>
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<title>CASTLE | About</title>
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<li><a class="active" href="about.html">About</a></li>
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<h3><mark>About Us</mark></h3>
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<span class="sub_heading2">About the database</span>
<h3>CASTLE</h3>
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<p>CASTLE is a collection of synthetic lethal data for various pathogenic organisms, generated computationally. CASTLE is freely available for non-commercial use. It is maintained by the <a href="https://home.iitm.ac.in/kraman/lab/" target="_blank"><font color="darkblue">Computational Systems Biology Lab</font></a> at the Indian Institute of Technology, Madras.</font> </p>
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<h3>Synthetic Lethals</h3>
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<p>Synthetic Lethals are sets of reactions/genes, in which only the simultaneous deletion of all reactions/genes in the set will abate growth and lead to the subsequent death of the organism. Figure on left, outlines the logic of synthetic lethality:
when there are two genes/reactions in a given set, the deletion of both reactions/genes is required to kill the organism.</p>
<p>The lethals in this database were identified using an <i>in silico</i> approach, applying a parallel version of the Fast-SL algorithm (for MATLAB) to genome-scale metabolic network reconstructions taken from the <a href="http://bigg.ucsd.edu/" target="_blank"><font color="darkblue">BIGG</font></a> and <a href="https://www.vmh.life/" target="_blank"><font color="darkblue">VMH</font></a> databases. The Fast-SL algorithm is available at:</p>
<a href="https://github.com/RamanLab/FastSL" target="_blank" class="boxed-btn">Our GitHub</a>
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<center><h1>How do I use CASTLE?</h1></center><br>
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The full list of available organisms can be browsed from the home page and the search bar can be used to find specific organisms. Beside the organism’s name, the number of each type of lethal is displayed. Each of these numbers correspond to a table containing the specific reactions/genes. Each of these reactions/genes can be selected to reveal supplementary information about that reaction/gene. The following convention is used:
</p>
<br><br>
<table width="50%" align="center">
<tr>
<th><center>Convention</center></th>
<th><center>Meaning</center></th>
</tr>
<tr>
<td><center>Jsl</center></td>
<td><center>Single Reaction Lethals</center></td>
</tr>
<tr>
<td><center>Jdl</center></td>
<td><center>Double Reaction Lethals</center></td>
</tr>
<tr>
<td><center>Jtl</center></td>
<td><center>Triple Reaction Lethals</center></td>
</tr>
<tr>
<td><center>Sgd</center></td>
<td><center>Single Gene Lethals</center></td>
</tr>
<tr>
<td><center>Dgd</center></td>
<td><center>Double Gene Lethals</center></td>
</tr>
<tr>
<td><center>Tgd</center></td>
<td><center>Triple Gene Lethals</center></td>
</tr>
</table>
<br><br>
<p class="about_info" style="text-align:justify">Next to the organism’s name, is an icon, which can be selected to download a ZIP file containing the lethal data in all the available formats. <br><br>On each organism’s page, the links in the table can be selected to display the specific genes/reactions identified for each type of lethal. Also, in the table, are icons which represent the available formats for each type of lethal. These icons can be selected to download the respective lethal information. </p>
<br>
<p style="text-align:justify">We have also added a synthetic network comprising all the edges that occur between DGD and TGD in an organism. This is to demonstrate the interconnectedness of the lethal genes inside the metabolic network. This synthetic network can be downloaded either as a .edgelist text file or .png image.</p>
<br>
<h3>Papers related to CASTLE</h3>
<p style="text-align:justify">[1] Pratapa, A., Balachandran, S. & Raman, K. Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks. Bioinformatics 31, 3299–3305 (2015).
<br>
[2] Nijman, S. M. Synthetic lethality: General principles, utility and detection using genetic screens in human cells. FEBS Letters 585, 1–6 (2010).
<br>
[3] Raman, K., Pratapa, A., Mohite, O. & Balachandran, S. Computational Prediction of Synthetic Lethals in Genome-Scale Metabolic Models Using Fast-SL. Methods in Molecular Biology Metabolic Network Reconstruction and Modeling 315–336 (2017). doi:10.1007/978-1-4939-7528-0_14</p><br><br>
<h3>Credits</h3>
<p style="text-align:justify">
This database was developed by the combined efforts of Arjun Raghavan (Student of McMaster University, Hamilton, Canada [Email Id: raghavaa@mcmaster.ca]), S.Sunanda (M.Tech Bioinformatics, SASTRA Deemed To Be University, Thanjavur) and Senthamizhan V (Project Associate, IIT Madras) under the guidance of Dr.Karthik Raman.<br>
<br>
Images Courtesy : Wikipedia
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