Results 291 to 300 of about 2,170,661 (326)

Evaluating Hyperparameter Optimization in Machine Learning Algorithms for Cancer Driver Gene Classification

Anais da I Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região Sul (ERAMIA-RS 2025)
Cancer driver genes (CDGs) play a central role in tumorigenesis and represent important targets for diagnosis and therapy. In this study, we evaluate the impact of hyperparameter optimization on the predictive performance of traditional machine learning algorithms using multi-omics data. We perform systematic searches across different configurations to
Ana Laura Schardosim, Kamille Konarzewski, Renan Soares de Andrades, Mariana Recamonde-Mendoza   +3 more
openaire   +1 more source

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

2023
Abstract In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based ...
Wei Zhang, Xianglin Zhang, Qiao Liu, Lei Wei, Xu Qiao, Rui Gao, Zhiping Liu, Xiaowo Wang   +7 more
openaire   +1 more source

Evaluation and Improving Hypergraph Based Learning Algorithm over Data Integration Problem for Cancer Related Genes

2012 International Conference on Advances in Computing and Communications, 2012
Reliable predictive model build using semi supervised learning utilising classification algorithm has evolved rapidly in successful cancer treatment. In order to optimise the data integration problem, such as hypergraph based learning to integrate microarray gene expressions and protein interactions for predicting cancer outcome, novice optimization ...
Seena Mary Augusty, Sminu Izudheen
openaire   +1 more source

Performance Evaluation of Subspace-based Algorithm in Selecting Differentially Expressed Genes and Classification of Tissue Types from Microarray Data

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
This paper presents the implementation and evaluation of subspace-based clustering algorithm for robust selection of differentially expressed genes as well as the classification of tissue types from microarray data. The performance of the proposed algorithm is compared against other well known clustering algorithms and the quality of clusters is ...
Jahangheer S. Shaik, Mohammed Yeasin
openaire   +1 more source

DPEBic: detecting essential proteins in gene expressions using encoding and biclustering algorithm

, 2021
Anooja Ali, Vishwanath R. Hulipalled, S. Patil, Raees Abdulkader   +3 more
semanticscholar   +1 more source

Hybridization of Moth flame optimization algorithm and quantum computing for gene selection in microarray data

Journal of Ambient Intelligence and Humanized Computing, 2020
Ali Dabba, A. Tari, S. Meftali
semanticscholar   +1 more source

Examing and Evaluating Dimension Reduction Algorithms for Classifying Alzheimer’s Diseases using Gene Expression Data

2021 17th International Conference on Mobility, Sensing and Networking (MSN), 2021
Shunbao Li, Po Yang 0001, Vitaveska Lanfranchi   +2 more
openaire   +1 more source

Gene expression programming algorithm based on multi-threading evaluator

Journal of Computer Applications, 2013
Sheng-qiao NI, Chang-jie TANG, Ning YANG, Jie ZUO   +3 more
openaire   +1 more source

Artificial bee colony algorithm with gene recombination for numerical function optimization

Applied Soft Computing, 2017
G. Li, Laizhong Cui, Xianghua Fu, Zhenkun Wen, N. Lu, Jian Lu   +5 more
semanticscholar   +1 more source

Gene selection and classification of microarray data method based on mutual information and moth flame algorithm.

Expert Systems With Applications, 2021
Ali Dabba, Abdelkamel Tari, Samy Meftali   +2 more
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