Latent Space Studies
26
Variational Autoencoder
Chaos and Complexity in Cancer
1
Chaos and Complexity in Cancer
Theory
2
Theoretical Framework
3
The Cell as a Complex System
4
Cancer as a Complex Adaptive System
5
Summary of Theoretical Framework
Methods
6
Ramaswamy dataset
7
Filtering of Microarrays
8
Preprocessing Workflow for Global Cancer Expression Data
9
Analysis Pipeline Overview
10
Complexity and Entropy Measures
Results and Discussion: Carcinomas
11
Comparison Report: BLAD/TCC
12
Comparison Report: BR/BRAD
13
Comparison Report: COL/COADREAD
14
Comparison Report: KID/RCC
15
Comparison Report: LU/LUAD
16
Comparison Report: OV/OVAD
17
Comparison Report: PA/PAAD
18
Comparison Report: UT/EAC
Results and Discussion: Blastomas
19
Comparison Report: Brain/GBM
20
Comparison Report: Brain/MB
Results and Discussion: Lymphomas
21
Comparison Report: GC/FL
22
Comparison Report: GC/LBCL
Results and Discussion: Leukemias
23
Comparison Report: PB/B-ALL
24
Comparison Report: PB/T-ALL
Latent Space Studies
25
PCA of Cancer samples
26
Variational Autoencoder
27
Latent Space with Centroids
Conclusions
28
UpSet Plots by Group
29
Complexity and Entropy Patterns in Cancer Categories: A Comparative Analysis
Table of contents
26.1
Variational Autoencoder
Latent Space Studies
26
Variational Autoencoder
26
Variational Autoencoder
26.1
Variational Autoencoder
VAE Training Curve
VAE Loss Components
Latent Variables Histogram
25
PCA of Cancer samples
27
Latent Space with Centroids
