✨ Add info about vuegen and MicW2Graph. Also, replace sebas' photo and add marco's photo (#7)

Author: sayalaruano

1research.md

@@ -10,6 +10,18 @@ permalink: /research/
 
 **Building High-quality Knowledge Graphs.** Using and developing Knowledge Graph technologies and methods to structured data and to connect them to existing biological knowledge. These structures facilitate analysis and interpretation of complex data. We are contributing to a groundbreaking field by developing tools and methods to build, assess and investigate Knowledge Graphs and applying them to solve challenges in biology and health.
 
+<div style="text-align: center; margin-bottom: 20px;">
+  <a href="https://github.com/Multiomics-Analytics-Group/MicW2Graph" target="_blank">
+    <img src="https://raw.githubusercontent.com/Multiomics-Analytics-Group/MicW2Graph/main/images/MicW2Graph_logo.svg" alt="MicW2Graph_logo" width="250px">
+  </a>
+</div>
+
+In this project, we investigated the microbiome of the **wastewater treatment** (WWT) process to build **MicW2Graph**, an open-source **knowledge graph** that integrates metagenomic and metatranscriptomic information with their biological context, including biological processes, environmental and phenotypic features, chemical compounds, and additional metadata. We developed a workflow to collect meta-omics datasets from [MGnify](https://www.ebi.ac.uk/metagenomics) and infer potential interactions among microorganisms through **microbial association networks**. MicW2Graph enables the investigation of research questions related to WWT, focusing on aspects such as microbial connections, community memberships, and potential ecological functions.
+
+The following figure shows the general workflow of the MicW2Graph project:
+
+![MicW2Graph Abstract](https://raw.githubusercontent.com/Multiomics-Analytics-Group/MicW2Graph/main/images/Methods_MicW2Graph.svg)
+
 ------------------------
 
 ## Graph Machine Learning
@@ -44,4 +56,6 @@ permalink: /research/
 ****
 
 
-# Publications
+# Publications
+
+Ayala-Ruano, S., Webel, H., & Santos, A. (2025). _VueGen: Automating the generation of scientific reports_. bioRxiv. [https://doi.org/10.1101/2025.03.05.641152](https://doi.org/10.1101/2025.03.05.641152)

3people.md

@@ -133,7 +133,7 @@ permalink: /people/
 
   <div class="column">
     <div class="card">
-      <img src="{{ site.baseurl }}/public/assets/asar.jpeg" alt="Sebastian" style="width:45%">
+      <img src="{{ site.baseurl }}/public/assets/asar.jpg" alt="Sebastian" style="width:70%">
       <div class="container">
         <h2>Sebastian Ayala Ruano</h2>
         <p class="title">Research Assistant</p>

4tools.md

@@ -24,7 +24,7 @@ Understanding host-parasite interactions is vital for tackling infectious diseas
 ### Giardia intestinalis Predicted PPI
 <iframe src="{{ site.baseurl }}/public/Gi_network.html" width="600" height="450" style="border:0;"></iframe>
 
-## Analytics Core (Acore) Library
+# Analytics Core (Acore) Library
 
 Acore, short for analytics core, is an open-source Python library 
 to preprocess and analyse multi-omics data. It includes functionality related to preprocessing, e.g. for 
@@ -37,3 +37,18 @@ Especially recipes will help to get started and explore several options for data
 Check out current recipes and the core libary documentation at 
 [analytics-core.readthedocs.io](https://analytics-core.readthedocs.io/).
 
+<div style="text-align: center; margin-bottom: 20px;">
+  <a href="https://github.com/Multiomics-Analytics-Group/vuegen" target="_blank">
+    <img src="https://raw.githubusercontent.com/Multiomics-Analytics-Group/vuegen/main/docs/images/vuegen_logo.svg" alt="VueGen" width="250px">
+  </a>
+</div>
+
+**VueGen** is a tool that automates the creation of **reports** from bioinformatics outputs, allowing researchers with minimal coding experience to communicate their results effectively. With VueGen, users can produce reports by simply specifying a directory containing output files, such as plots, tables, networks, Markdown text, HTML components, and API calls, along with the report format. Supported formats include **documents** (PDF, HTML, DOCX, ODT), **presentations** (PPTX, Reveal.js), **Jupyter notebooks**, and [Streamlit](https://streamlit.io/) **web applications**.
+
+An overview of the VueGen workflow is shown in the figure below:
+
+![VueGen Abstract](https://raw.githubusercontent.com/Multiomics-Analytics-Group/vuegen/main/docs/images/vuegen_graph_abstract.png)
+
+VueGen offers various implementation options for both non-technical and experienced users. It is available as a [Python package](https://pypi.org/project/vuegen/), [Docker image](https://quay.io/repository/dtu_biosustain_dsp/vuegen), [nf-core module](https://github.com/Multiomics-Analytics-Group/nf-vuegen/), and [cross-platform desktop application](https://github.com/Multiomics-Analytics-Group/vuegen/releases/tag/v0.3.2) with a user-friendly interface, making it accessible and customizable for different user needs and expertise levels.
+
+The documentation is available at [vuegen.readthedocs.io](https://vuegen.readthedocs.io/), where you can find detailed information of the package’s classes and functions, installation and execution instructions, and case studies to demonstrate its functionality.