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accessibility.html
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accessibility.html
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<div class="row" id="introduction">
<div class="colW600">
State-of-the-art RNA-RNA interaction prediction algorithms take
the accessibility of the interacting regions into account. That is,
a penalty corrects the interaction scoring for how
much the interaction sites are involved in intramolecular base pairs.
This can be expressed by reverting unpaired probabilities $P^{u}_{i,j}$ into
pseudo energy scores via $-RT\log(P^{u}_{i,j})$ that represent the amount
of energy (within the structure ensemble) to unfold a region $i..j$
in order to make it accessible for intermolecular RNA-RNA interactions
<a href="https://dx.doi.org/10.1093/bioinformatics/btl024">(Ulrike Mückstein et al., 2006)</a>.
<br>
<br>
Here, we extend the
<a href="index.jsp?toolName=hybrid-only">hybrid-only approach</a>
towards the integration of an accessibility-based scoring. To this end, the
<a href="index.jsp?toolName=McCaskill">simplified McCaskill approach</a>
is used to compute unpaired probabilities $P^{u}$. The penalties are
used in a post-processing step to correct the hybridization energies in
order to identify the interaction that optimizes the combination of
hybridization and accessibility scoring.
</div>
<div class="colW150">
<img alt="accessibility-based RNA-RNA interaction" src="accessibility-120x90.png" width=120 height=90 >
</div>
</div>
<div id="inputContainer">
<div class="row">
<div class="colW250" style="font-size: 120%; vertical-align: bottom; ">RNA sequence $S^1$:</div>
<div class="colW400">
<input data-bind="value: rawSeq" class="userInput"
placeholder="Example 'GCACG'" onkeydown="validate(event)"
style="text-transform:uppercase">
</div>
</div>
<div class="row">
<div class="colW250" style="font-size: 120%; vertical-align: bottom; ">RNA sequence $S^2$:<br>
<span style="font-size:70%;">(Computation uses reversed sequence $\overleftarrow{S^2}$)</span>
</div>
<div class="colW400">
<input data-bind="value: rawSeq2" class="userInput"
placeholder="Example 'GCACG'" onkeydown="validate(event)"
style="text-transform:uppercase">
</div>
</div>
<div class="row">
<div class="colW250" style="font-size: 120%">Minimal loop length $l$:</div>
<div class="colW400">
<select data-bind="value: loopLength" id="ll" style="width:40px;">
<option value=0>0</option>
<option value=1>1</option>
<option value=2>2</option>
<option value=3>3</option>
</select>
<label for="ll" style="margin-left:10px;">i.e. minimal number of enclosed positions</label>
</div>
</div>
<div class="row">
<div class="colW250" style="font-size: 120%">Energy weight of base pair $E_{bp}$:</div>
<div class="colW400">
<input data-bind="value: input.energy" id="energy" type="range" max="2" min="-2" step="(max - min) / 100">
<label for="energy" data-bind="text: input.energy"></label>
</div>
</div>
<div class="row">
<div class="colW250" style="font-size: 120%">'Normalized' temperature $RT$:</div>
<div class="colW400">
<input data-bind="value: input.energy_normal" id="energy_normal" type="range" max="5" min="1" step="(max - min) / 100">
<label for="energy_normal" data-bind="text: input.energy_normal"></label>
</div>
</div>
<div>
The following recursions are used to compute the interactions that
show an optimal combination of hybridization and accessibility.
To this end, first the maximal number of base pairs $D^{i,k}_{j,l}$ for all
interaction sites are computed using the
<a href="index.jsp?toolName=hybrid-only">hybrid-only approach</a>.
Furthermore, the unpaired probabilities $P^{u1}$ and $P^{u2}$ are
tabularized for both sequences $S^1$ and $\overleftarrow{S^2}$, resp., using the
<a href="index.jsp?toolName=McCaskill">simplified McCaskill approach</a>.
<br>
Given these values, the accessibility-incorporating interaction scorings
are computed and stored in table $I$. A non-zero entry $I^{i,k}_{j,l}$
represents the combined scoring for an interaction of
$S^1_{i..k}$ with $\overleftarrow{S^2_{j..l}}$ with
left/right most base pairs $(S^1_i,\overleftarrow{S^2_j})$/$(S^1_k,\overleftarrow{S^2_l})$, respectively.
</div>
<div id="recursion" data-bind="text: latex()[0]"></div>
<div id="rec_select" style="display: none;">rnaup</div>
</div>
<div id="output">
<h2>Visualization of interacting base pairs (selected structure)</h2>
<div>
Due to the four-dimensionality of $I$, we only list the optimal
hybrid structures (up to 15). On selection, the intermolecular base pairs are
visualized. If all entries $I^{i,k}_{j,l}$ show negative scores,
no favorable interaction is possible since intramolecular base pairs
dominate the individual structures (too hight penalties for
possible interaction sites). Therefore, the structure list might be
empty.
</div>
<div class="row" style="margin:0;">
<div class="colW300" style="margin:0; overflow-x:auto;">
<table id="structures">
<thead>
<tr><th id="structTableHeading">Possible Structures</th></tr>
</thead>
<tbody data-bind="foreach: { data: tracebacks, as: 'tb' }">
<tr><td id="structTableCells" data-bind="text: tb.structure, event: {mousedown:$parent.clickStructure4d}"></td></tr>
</tbody>
</table>
</div>
<div class="colW400" style="margin:0;">
<div id="4dVisual" class="hybridVisual"></div>
</div>
</div>
<div style="font-weight:bold;">
Energy of selection:
<span id="output_value"></span>
</div>
<div>
The box provides an ASCII representation of the interacting
base pairs of the selected structure with $S^{1}$ on top and $S^{2}$
on the bottom.
Note, sequence $S^{2}$ is reversed (running from right ($5'$) to left
($3'$)) within this representation.
Note further, if no interacting
base pairs are present, no visualization is done.
</div>
</div>
<div id="output">
<h2>Accessibility</h2>
<div>
The <a href="index.jsp?toolName=McCaskill">simplified McCaskill approach</a>
is used in order to compute the unpaired probabilities $P^{u}$ for each of
the two sequences. Please refer to the according page for details.
These are used to compute according energy penalties $ED$ to make an
interacting site $i..j$ accessible, i.e. $ED_{i,j} = -RT\cdot\log(P^{u}_{i,j})$.
In the following, the penalties for $S^1$ and $\overleftarrow{S^2}$ are
visualized in dotplot format, i.e. the larger the dot the higher is
the penalty for the respective subsequence to form an interaction.
</div>
<div style="font-weight:bold;">Penalties $ED^{1}$ to make site in $S^{1}$ accessible:</div>
<div id="dotplot_seq1" class="dotplotContainer"></div>
<div style="font-weight:bold;">Penalties $ED^{2}$ to make site in $\overleftarrow{S^2}$ accessible:</div>
<div id="dotplot_seq2" class="dotplotContainer"></div>
</div>
<script src="js/visualize.js"></script>