A graph-based gene selection method for medical diagnosis problems using a many-objective PSO algorithm
Abstract Background Gene expression data play an important role in bioinformatics applications. Although there may be a large number of features in such data, they mainly tend to contain only a few samples. This can negatively impact the performance of data mining and machine learning algorithms. On...
Saved in:
Main Authors: | Saeid Azadifar, Ali Ahmadi |
---|---|
Format: | article |
Language: | EN |
Published: |
BMC
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/4f6d1f5c1a824aa78b4cbd82b91abf86 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Novel Calibration Step in Gene Co-Expression Network Construction
by: Niloofar Aghaieabiane, et al.
Published: (2021) -
CARACTERIZACIÓN Y CLASIFICACIÓN BOTÁNICA DE VEINTIDOS LÍNEAS DE MANÍ (Arachis hypogaea L.) EVALUADAS EN LA PROVINCIA DE ÑUBLE, CHILE
by: Zapata,Nelson, et al.
Published: (2017) -
Signal Control Period Division Method Based on Locally Linear Embedding and Particle Swarm Optimization Combined With K-Means Clustering
by: Xiujuan Tian, et al.
Published: (2021) -
A Many-Objective Simultaneous Feature Selection and Discretization for LCS-Based Gesture Recognition
by: Martin J.-D. Otis, et al.
Published: (2021) -
Actionable health app evaluation: translating expert frameworks into objective metrics
by: Sarah Lagan, et al.
Published: (2020)