Skip to content

Commit

Permalink
Update project and dropdown
Browse files Browse the repository at this point in the history
  • Loading branch information
daniel-manrique committed Mar 4, 2024
1 parent 0ca2d84 commit 8645299
Show file tree
Hide file tree
Showing 3 changed files with 5 additions and 7 deletions.
8 changes: 4 additions & 4 deletions _pages/dropdown.md
Original file line number Diff line number Diff line change
@@ -1,16 +1,16 @@
---
layout: page
title: submenus
title: Others
nav: true
nav_order: 8
dropdown: true
children:
- title: Publications
- title: Books
permalink: /publications/
- title: divider
- title: Projects
- title: Journalism
permalink: /projects/
- title: divider
- title: Blog
- title: YouTube
permalink: /blog/
---
1 change: 0 additions & 1 deletion _projects/1_project.md
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,6 @@ category: image analysis

I am exploring ways to incorporate Point patterns analysis (PPA) for the analysis of microscopy images in neuroscience. PPA allows the investigation of the spatial arrangement/distribution of cells, like neurons and neuroglia, in the healthy and disease central nervous system. Indeed, it has application in multiple biomedical fields. I perform point pattern analysis using the [spatstat](https://spatstat.org/download.html) package in R-programming language.

</div>
<div class="row">
<div class="col-sm mt-3 mt-md-0">
{% include figure.liquid loading="eager" path="assets/img/Pointanalysis.png" title="PPA" class="img-fluid rounded z-depth-1" %}
Expand Down
3 changes: 1 addition & 2 deletions _projects/2_project.md
Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,11 @@ title: Topological data analysis for neuroscience
description: Implementation of Topological Data Analysis (TDA) to examine the spatial arrangement/distribution of cells.
img: assets/img/TDAimg.jpg
importance: 2
category: category: image analysis
category: image analysis
---

Topological data analysis (TDA) is an approach that uses algebraic topology to analyze complex data sets, including point clouds. With TDA, the user can evaluate the degree of noise, variability, and complexity, as well as identifying topological features such as holes, loops, and voids in the point clouds at different scales. This approach is based on tools like vietoris-rips complexes and persistent homology that allow to visualize complex topological structures.

</div>
<div class="row">
<div class="col-sm mt-3 mt-md-0">
{% include figure.liquid loading="eager" path="assets/img/TDAimg.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
Expand Down

0 comments on commit 8645299

Please sign in to comment.