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        <h1>IDP phase separation</h1>

        <div class="project">
            <div class="project-text">
                On <a href="https://github.com/jwessen">my GitHub page</a>, you can find <a href="https://github.com/jwessen/IDP_phase_separation">repository</a> with Python codes related to my computational research on intrinsically disordered protein (IDP) phase separation. These codes implement a field-theoretic model of polyampholytes interacting through long-range electrostatic forces and short-range excluded volume. This is a simple but widely studied model that captures many features of electrostatically driven IDP phase separation.  <br> <br>

                Key scripts include:
                <ul>
                    <li>
                         <a href="https://github.com/jwessen/IDP_phase_separation/blob/main/RPA_polyampholytes.py">RPA_polyampholytes.py</a>: This code can be used for computing the coexistence curve (binodal) in the random phase approximation (RPA). </li>
                    <li>
                        <a href="https://github.com/jwessen/IDP_phase_separation/blob/main/FTS_polyampholytes.py">FTS_polyampholytes.py</a>: This code defines the basic object and functions for fully fluctuation field-theoretic simulations (FTS). </li>
                    <li>
                        <a href="https://github.com/jwessen/IDP_phase_separation/blob/main/FTS_trajectories_MPI.py">FTS_trajectories_MPI.py</a>: This code can be used for running parallelized FTS to compute the chemical potential and osmotic pressure at different bulk polymer densities. </li>
                    <li>
                        <a href="https://github.com/jwessen/IDP_phase_separation/blob/main/FTS_analyze_trajectories.py">FTS_analyze_trajectories.py</a>: This script analyzes the output files from FTS_trajectories_MPI.py to compute the coexistence curve.
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                A detailed user guide is provided in this <a href="https://github.com/jwessen/IDP_phase_separation/blob/main/rpa_fts_guide.pdf">PDF</a>. The codes in this repository are published as a part of the following book chapter, wherein the theory, methods and key references are provided:
                <ul>
                    <li>
                        <strong>Numerical Techniques for Applications of Analytical Theories to Sequence-Dependent Phase Separations of Intrinsically Disordered Proteins</strong><br>
                        Y.-H. Lin*, J. Wessén*, T. Pal*, S. Das and H. S. Chan (*equal contribution)<br>
                        In: Zhou, HX., Spille, JH., Banerjee, P.R. (eds) Phase-Separated Biomolecular Condensates (2023). Methods in Molecular Biology, vol 2563. Humana, New York, NY.<br>
                        <u>DOI</u>: <a href="https://doi.org/10.1007/978-1-0716-2663-4_3">doi.org/10.1007/978-1-0716-2663-4_3</a><br>
                        <u>Preprint</u>: <a href="https://doi.org/10.48550/arXiv.2201.01920">arXiv:2201.01920</a>
                    </li>
                </ul>
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                <figure style="text-align: center;">
                    <img src="images/rpa_phase_diag.png" alt="RPA phase diagrams" style="max-width: 100%; height: auto;">
                    <figcaption>
                        <em>
                            Figure 1: An example polyampholyte phase diagram produced by the RPA_polyampholytes.py code.
                        </em>
                    </figcaption>
                </figure>

                <figure style="text-align: center;">
                    <img src="images/snapshot.png" alt="FTS snapshot" style="max-width: 80%; height: auto;">
                    <figcaption>
                        <em>
                            Figure 2: A snapshot of the polymer bead density field operator in a field-theoretic simulation produced by the FTS_polyampholytes.py code.
                        </em>
                    </figcaption>
                </figure>
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