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                <strong>Title: </strong>Prediction of RNA – RNA interface using Graph theory
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                A majority of viral and prokaryotic systems involve RNA-RNA interactions that are often mediated by interactions between residues in the single stranded regions of the RNA. Though sequence based analysis of the RNA interacting partners is available, there is a dearth of knowledge at the structure level. This project is aimed at predicting the possible RNA – RNA interactions in systems such as mRNA and viral genomic RNA. Here we would be representing the RNA secondary structure as a graph, thereby reducing the computational burden of scanning the entire RNA space. Students will be exposed to the mathematical nuances in graph theory and its application in predicting RNA – RNA interactions.
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                <strong>Requisites: </strong>Student should have a basic understanding of Biology and high competence in Mathematics. Students are expected to be highly proficient in computer programming. Student will be working in the department of Biological Sciences and department of Mathematics.
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                <strong>Details of Investigators</strong>
                <div class="investigator">
                    <em><NAME>,</em> Ph.D.
                    <div class="info">
                        Department of Biological Science
                        <br> BITS-Pilani, K. K. Birla Goa Campus
                        <br> Email: <a href="mailto:<EMAIL>"><EMAIL></a>
                        <br> Phone: +91 832 2580 394
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                    <em><NAME>, </em>Ph.D.
                    <div class="info">
                        Department of Mathematics
                        <br> BITS-Pilani, K. K. Birla Goa Campus
                        <br> Email: <a href="mailto:<EMAIL>"><EMAIL>.in</a>
                        <br> Phone: +91 832 2580 452
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            function() {<commit_msg>Update project4.html<commit_after><!doctype html>
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        <div class="project">
            <div class="title">
                <strong>Title: </strong>Prediction of RNA – RNA interface using Graph theory
            </div>
            <div class="contents">
                A majority of viral and prokaryotic systems involve RNA-RNA interactions that are often mediated by interactions between residues in the single stranded regions of the RNA. Though sequence based analysis of the RNA interacting partners is available, there is a dearth of knowledge at the structure level. This project is aimed at predicting the possible RNA – RNA interactions in systems such as mRNA and viral genomic RNA. Here we would be representing the RNA secondary structure as a graph, thereby reducing the computational burden of scanning the entire RNA space. Students will be exposed to the mathematical nuances in graph theory and its application in predicting RNA – RNA interactions.
            </div>
            <div class="requisites">
                <strong>Requisites: </strong>Student should have a basic understanding of Biology and high competence in Mathematics. Students are expected to be highly proficient in computer programming. Student will be working in the department of Biological Sciences and department of Mathematics.
            </div>
            <div class="investigators">
                <strong>Details of Investigators</strong>
                <div class="investigator">
                    <em><NAME>,</em> Ph.D.
                    <div class="info">
                        Department of Biological Science
                        <br> BITS-Pilani, K. K. Birla Goa Campus
                        <br> Email: <a href="mailto:<EMAIL>"><EMAIL></a>
                        <br> Phone: +91 832 2580 394
                    </div>
                </div>
                <div class="investigator">
                    <em><NAME>, </em>Ph.D.
                    <div class="info">
                        Department of Mathematics
                        <br> BITS-Pilani, K. K. Birla Goa Campus
                        <br> Email: <a href="mailto:<EMAIL>"><EMAIL></a>
                        <br> Phone: +91 832 2580 452
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