<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mathematical Biology |</title><link>https://anthbapt.github.io/tags/mathematical-biology/</link><atom:link href="https://anthbapt.github.io/tags/mathematical-biology/index.xml" rel="self" type="application/rss+xml"/><description>Mathematical Biology</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 01 Nov 2024 00:00:00 +0000</lastBuildDate><image><url>https://anthbapt.github.io/media/icon_hu_da05098ef60dc2e7.png</url><title>Mathematical Biology</title><link>https://anthbapt.github.io/tags/mathematical-biology/</link></image><item><title>Cell-cell communications</title><link>https://anthbapt.github.io/projects/graph-rwr/</link><pubDate>Fri, 01 Nov 2024 00:00:00 +0000</pubDate><guid>https://anthbapt.github.io/projects/graph-rwr/</guid><description>&lt;p&gt;This project explores the use of random walk with restart (RWR) on tissue neighbourhood graphs to define cell–cell communication in the spatial transcriptomics context.&lt;/p&gt;
&lt;p&gt;Key contributions:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Synthetic data generator&lt;/strong&gt;: Simulation of ligand-receptor signalling for benchmarking&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Practical methods&lt;/strong&gt;: Scalable RWR-based inference of communication patterns in spatial transcriptomics data&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>